TY - JOUR AU - Wang, Jeffrey B. AU - Hassan, Umair AU - Bruss, Joel E. AU - Oya, Hiroyuki AU - Uitermarkt, Brandt D. AU - Trapp, Nicholas T. AU - Gander, Phillip E. AU - Howard, Matthew A. AU - Keller, Corey J. AU - Boes, Aaron D. TI - Effects of transcranial magnetic stimulation on the human brain recorded with intracranial electrocorticography JF - MOLECULAR PSYCHIATRY J2 - MOL PSYCHIATR PY - 2024 PG - 13 SN - 1359-4184 DO - 10.1038/s41380-024-02405-y UR - https://m2.mtmt.hu/api/publication/34610438 ID - 34610438 AB - Transcranial magnetic stimulation (TMS) is increasingly used as a noninvasive technique for neuromodulation in research and clinical applications, yet its mechanisms are not well understood. Here, we present the neurophysiological effects of TMS using intracranial electrocorticography (iEEG) in neurosurgical patients. We first evaluated safety in a gel-based phantom. We then performed TMS-iEEG in 22 neurosurgical participants with no adverse events. We next evaluated intracranial responses to single pulses of TMS to the dorsolateral prefrontal cortex (dlPFC) (N = 10, 1414 electrodes). We demonstrate that TMS is capable of inducing evoked potentials both locally within the dlPFC and in downstream regions functionally connected to the dlPFC, including the anterior cingulate and insular cortex. These downstream effects were not observed when stimulating other distant brain regions. Intracranial dlPFC electrical stimulation had similar timing and downstream effects as TMS. These findings support the safety and promise of TMS-iEEG in humans to examine local and network-level effects of TMS with higher spatiotemporal resolution than currently available methods. LA - English DB - MTMT ER - TY - JOUR AU - Barbosa, D.A.N. AU - Gattas, S. AU - Salgado, J.S. AU - Kuijper, F.M. AU - Wang, A.R. AU - Huang, Y. AU - Kakusa, B. AU - Leuze, C. AU - Luczak, A. AU - Rapp, P. AU - Malenka, R.C. AU - Hermes, D. AU - Miller, K.J. AU - Heifets, B.D. AU - Bohon, C. AU - McNab, J.A. AU - Halpern, C.H. TI - An orexigenic subnetwork within the human hippocampus JF - NATURE J2 - NATURE VL - 621 PY - 2023 IS - 7978 SP - 381 EP - 388 PG - 8 SN - 0028-0836 DO - 10.1038/s41586-023-06459-w UR - https://m2.mtmt.hu/api/publication/34227757 ID - 34227757 N1 - Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, United States Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States Université Paris Cité, Paris, France Assistance Publique des Hôpitaux de Paris, Paris, France Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB, Canada Department of Military & Emergency Medicine, Uniformed Services University, Bethesda, MD, United States Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States Nancy Pritzker Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States Department of Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, United States Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States Department of Surgery, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, United States Export Date: 31 October 2023 CODEN: NATUA Correspondence Address: Halpern, C.H.; Department of Neurosurgery, United States; email: casey.halpern@pennmedicine.upenn.edu LA - English DB - MTMT ER - TY - JOUR AU - Barbosa, Daniel A. N. AU - Gattas, Sandra AU - Salgado, Juliana S. AU - Kuijper, Fiene Marie AU - Wang, Allan R. AU - Huang, Yuhao AU - Kakusa, Bina AU - Leuze, Christoph AU - Luczak, Artur AU - Rapp, Paul AU - Malenka, Robert C. AU - Hermes, Dora AU - Miller, Kai J. AU - Heifets, Boris D. AU - Bohon, Cara AU - Mcnab, Jennifer A. AU - Halpern, Casey H. TI - An orexigenic subnetwork within the human hippocampus JF - NATURE J2 - NATURE PY - 2023 PG - 26 SN - 0028-0836 DO - 10.1038/s41586-023-06459 UR - https://m2.mtmt.hu/api/publication/34281661 ID - 34281661 AB - Only recently have more specific circuit-probing techniques become available to inform previous reports implicating the rodent hippocampus in orexigenic appetitive processing1-4. This function has been reported to be mediated at least in part by lateral hypothalamic inputs, including those involving orexigenic lateral hypothalamic neuropeptides, such as melanin-concentrating hormone5,6. This circuit, however, remains elusive in humans. Here we combine tractography, intracranial electrophysiology, cortico-subcortical evoked potentials, and brain-clearing 3D histology to identify an orexigenic circuit involving the lateral hypothalamus and converging in a hippocampal subregion. We found that low-frequency power is modulated by sweet-fat food cues, and this modulation was specific to the dorsolateral hippocampus. Structural and functional analyses of this circuit in a human cohort exhibiting dysregulated eating behaviour revealed connectivity that was inversely related to body mass index. Collectively, this multimodal approach describes an orexigenic subnetwork within the human hippocampus implicated in obesity and related eating disorders.An appetite-regulating subnetwork in humans involving the lateral hypothalamus and the dorsolateral hippocampus is implicated in obesity and related eating disorders. LA - English DB - MTMT ER - TY - JOUR AU - Bernabei, John M. AU - Li, Adam AU - Revell, Andrew Y. AU - Smith, Rachel J. AU - Gunnarsdottir, Kristin M. AU - Ong, Ian Z. AU - Davis, Kathryn A. AU - Sinha, Nishant AU - Sarma, Sridevi AU - Litt, Brian TI - Quantitative approaches to guide epilepsy surgery from intracranial EEG JF - BRAIN J2 - BRAIN PY - 2023 PG - 11 SN - 0006-8950 DO - 10.1093/brain/awad007 UR - https://m2.mtmt.hu/api/publication/33893852 ID - 33893852 N1 - Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, United States Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States Department of Computer Science, Columbia University, New York, NY 10027, United States Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, United States Neuroengineering Program, University of Alabama at Birmingham, Birmingham, AL 35294, United States Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, United States Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States Cited By :3 Export Date: 31 October 2023 CODEN: BRAIA Correspondence Address: Li, A.500 W 120th St, Mudd Building, United States; email: Adam.Li@Columbia.edu Correspondence Address: Bernabei, J.3320 Smith Walk Room 301, United States; email: John.Bernabei@Pennmedicine.upenn.edu AB - Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated widespread interest in methods to quantitatively guide epilepsy surgery from intracranial EEG (iEEG). Many patients fail to achieve seizure freedom, in part due to the challenges in subjective iEEG interpretation. To address this clinical need, quantitative iEEG analytics have been developed using a variety of approaches, spanning studies of seizures, interictal periods, and their transitions, and encompass a range of techniques including electrographic signal analysis, dynamical systems modeling, machine learning and graph theory. Unfortunately, many methods fail to generalize to new data and are sensitive to differences in pathology and electrode placement. Here, we critically review selected literature on computational methods of identifying the epileptogenic zone from iEEG. We highlight shared methodological challenges common to many studies in this field and propose ways that they can be addressed. One fundamental common pitfall is a lack of open-source, high-quality data, which we specifically address by sharing a centralized high-quality, well-annotated, multicentre dataset consisting of >100 patients to support larger and more rigorous studies. Ultimately, we provide a road map to help these tools reach clinical trials and hope to improve the lives of future patients.Bernabei et al. provide an update on quantitative methods for guiding epilepsy surgery using intracranial EEG. They identify challenges which have prevented successful clinical translation of these methods, and offer potential solutions, including the release of a new dataset with more than 100 patients to support larger and more rigorous studies. LA - English DB - MTMT ER - TY - JOUR AU - Cometa, Andrea AU - d'Orio, Piergiorgio AU - Revay, Martina AU - Bottoni, Franco AU - Repetto, Claudia AU - Russo, Giorgio Lo AU - Cappa, Stefano F. AU - Moro, Andrea AU - Micera, Silvestro AU - Artoni, Fiorenzo TI - Event-related causality in stereo-EEG discriminates syntactic processing of noun phrases and verb phrases JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 20 PY - 2023 IS - 2 PG - 16 SN - 1741-2560 DO - 10.1088/1741-2552/accaa8 UR - https://m2.mtmt.hu/api/publication/33893851 ID - 33893851 N1 - Export Date: 31 October 2023 CODEN: JNEOB Correspondence Address: Artoni, F.; The BioRobotics Institute, Viale Rinaldo Piaggio 34, Italy; email: fiorenzo.artoni@unige.ch AB - Objective. Syntax involves complex neurobiological mechanisms, which are difficult to disentangle for multiple reasons. Using a protocol able to separate syntactic information from sound information we investigated the neural causal connections evoked by the processing of homophonous phrases, i.e. with the same acoustic information but with different syntactic content. These could be either verb phrases (VP) or noun phrases. Approach. We used event-related causality from stereo-electroencephalographic recordings in ten epileptic patients in multiple cortical and subcortical areas, including language areas and their homologous in the non-dominant hemisphere. The recordings were made while the subjects were listening to the homophonous phrases. Main results. We identified the different networks involved in the processing of these syntactic operations (faster in the dominant hemisphere) showing that VPs engage a wider cortical and subcortical network. We also present a proof-of-concept for the decoding of the syntactic category of a perceived phrase based on causality measures. Significance. Our findings help unravel the neural correlates of syntactic elaboration and show how a decoding based on multiple cortical and subcortical areas could contribute to the development of speech prostheses for speech impairment mitigation. LA - English DB - MTMT ER - TY - JOUR AU - Cornblath, Eli J. J. AU - Lucas, Alfredo AU - Armstrong, Caren AU - Greenblatt, Adam S. S. AU - Stein, Joel M. M. AU - Hadar, Peter N. N. AU - Raghupathi, Ramya AU - Marsh, Eric AU - Litt, Brian AU - Davis, Kathryn A. A. AU - Conrad, Erin C. C. TI - Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue JF - EPILEPSIA J2 - EPILEPSIA VL - 64 PY - 2023 IS - 4 SP - 1021 EP - 1034 PG - 14 SN - 0013-9580 DO - 10.1111/epi.17528 UR - https://m2.mtmt.hu/api/publication/33865809 ID - 33865809 N1 - Department of Neurology, Perelman School of Medicine, Philadelphia, PA, United States Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, PA, United States Pediatric Epilepsy Program, Children's Hospital of Philadelphia, Philadelphia, PA, United States Department of Radiology, Perelman School of Medicine, Philadelphia, PA, United States Department of Pediatrics, Perelman School of Medicine, Philadelphia, PA, United States Export Date: 30 October 2023 CODEN: EPILA Correspondence Address: Cornblath, E.J.; Department of Neurology, United States; email: eli.cornblath@pennmedicine.upenn.edu AB - ObjectiveMeasuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. MethodsWe studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. ResultsWe found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SignificanceThese findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue. LA - English DB - MTMT ER - TY - JOUR AU - Dou, Y. AU - Xia, J. AU - Fu, M. AU - Cai, Y. AU - Meng, X. AU - Zhan, Y. TI - Identification of epileptic networks with graph convolutional network incorporating oscillatory activities and evoked synaptic responses JF - NEUROIMAGE J2 - NEUROIMAGE VL - 284 PY - 2023 SN - 1053-8119 DO - 10.1016/j.neuroimage.2023.120439 UR - https://m2.mtmt.hu/api/publication/34539630 ID - 34539630 N1 - The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Department of Neurosurgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China Export Date: 29 January 2024 CODEN: NEIME Correspondence Address: Meng, X.; Department of Neurosurgery, China; email: dr_mengxh@163.com LA - English DB - MTMT ER - TY - JOUR AU - Huang, H. AU - Gregg, N.M. AU - Valencia, G.O. AU - Brinkmann, B.H. AU - Lundstrom, B.N. AU - Worrell, G.A. AU - Miller, K.J. AU - Hermes, D. TI - Electrical Stimulation of Temporal and Limbic Circuitry Produces Distinct Responses in Human Ventral Temporal Cortex JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 43 PY - 2023 IS - 24 SP - 4434 EP - 4447 PG - 14 SN - 0270-6474 DO - 10.1523/JNEUROSCI.1325-22.2023 UR - https://m2.mtmt.hu/api/publication/34170893 ID - 34170893 N1 - Mayo Clinic Medical Scientist Training Program, Mayo Clinic, Rochester, MN 55905, United States Department of Neurology, Mayo Clinic, Rochester, MN 55905, United States Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, United States Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, United States Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN 55905, United States Cited By :1 Export Date: 29 January 2024 CODEN: JNRSD Correspondence Address: Hermes, D.; Department of Neurology, United States; email: hermes.dora@mayo.edu AB - The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC. We recorded intracranial EEG data in 5 patients (3 female) implanted with intracranial electrodes for epilepsy surgery evaluation. Pairs of electrodes were stimulated with single-pulse electrical stimulation, and corticocortical evoked potential responses were measured at electrodes in the collateral sulcus and lateral occipitotemporal sulcus of the VTC. Using a novel unsupervised machine learning method, we uncovered 2-4 distinct response shapes, termed basis profile curves (BPCs), at each measurement electrode in the 11-500 ms after stimulation interval. Corticocortical evoked potentials of unique shape and high amplitude were elicited following stimulation of several regions and classified into a set of four consensus BPCs across subjects. One of the consensus BPCs was primarily elicited by stimulation of the hippocampus; another by stimulation of the amygdala; a third by stimulation of lateral cortical sites, such as the middle temporal gyrus; and the final one by stimulation of multiple distributed sites. Stimulation also produced sustained high-frequency power decreases and low-frequency power increases that spanned multiple BPC categories. Characterizing distinct shapes in stimulation responses provides a novel description of connectivity to the VTC and reveals significant differences in input from cortical and limbic structures. LA - English DB - MTMT ER - TY - JOUR AU - Nemati, S.S. AU - Sadeghi, L. AU - Dehghan, G. AU - Sheibani, N. TI - Lateralization of the hippocampus: A review of molecular, functional, and physiological properties in health and disease JF - BEHAVIOURAL BRAIN RESEARCH J2 - BEHAV BRAIN RES VL - 454 PY - 2023 SN - 0166-4328 DO - 10.1016/j.bbr.2023.114657 UR - https://m2.mtmt.hu/api/publication/34227755 ID - 34227755 N1 - Department of Biology, Faculty of Natural Sciences, University of Tabriz, Tabriz, 51666-16471, Iran Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, United States Export Date: 31 October 2023 CODEN: BBRED Correspondence Address: Sadeghi, L.; Department of Biology, Iran; email: l.sadeghi@tabrizu.ac.ir LA - English DB - MTMT ER - TY - JOUR AU - Parmigiani, S. AU - Ross, J.M. AU - Cline, C.C. AU - Minasi, C.B. AU - Gogulski, J. AU - Keller, C.J. TI - Reliability and Validity of Transcranial Magnetic Stimulation–Electroencephalography Biomarkers JF - BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING J2 - BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGINING VL - In press PY - 2023 SP - In press SN - 2451-9022 DO - 10.1016/j.bpsc.2022.12.005 UR - https://m2.mtmt.hu/api/publication/34079558 ID - 34079558 N1 - Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, StanfordCalifornia, United States Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California, United States Wu Tsai Neuroscience Institute, Stanford, California, United States Department of Clinical Neurophysiology, HUS Diagnostic Center, Clinical Neurosciences, Helsinki University Hospital and University of Helsinki, Helsinki, Finland Export Date: 28 July 2023 Correspondence Address: Keller, C.J.; Department of Psychiatry and Behavioral Sciences, Stanford; email: ckeller1@stanford.edu AB - Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field. © 2022 LA - English DB - MTMT ER - TY - JOUR AU - Seguin, Caio AU - Sporns, Olaf AU - Zalesky, Andrew TI - Brain network communication: concepts, models and applications JF - NATURE REVIEWS NEUROSCIENCE J2 - NAT REV NEUROSCI VL - 24 PY - 2023 IS - 9 SP - 557 EP - 574 PG - 18 SN - 1471-003X DO - 10.1038/s41583-023-00718-5 UR - https://m2.mtmt.hu/api/publication/34132462 ID - 34132462 N1 - Funding Agency and Grant Number: Australian Research Council [DP170101815]; National Institute of Health [R01 122957]; National Health and Medical Research Council of Australia [APP1118153] Funding text: AcknowledgementsC.S. acknowledges support from the Australian Research Council (grant number DP170101815). O.S. acknowledges support from the National Institute of Health (R01 122957). A.Z. acknowledges support from the National Health and Medical Research Council of Australia (APP1118153). AB - Developments in connectomics and network neuroscience over the past 20 years have led to new ways of investigating communication in complex brain networks. In this Review, Seguin, Sporns and Zalesky discuss the current landscape of models of brain network communication. Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models. LA - English DB - MTMT ER - TY - JOUR AU - Valencia, G.O. AU - Gregg, N.M. AU - Huang, H. AU - Lundstrom, B.N. AU - Brinkmann, B.H. AU - Attia, T.P. AU - Van, Gompel J.J. AU - Bernstein, M.A. AU - In, M.-H. AU - Huston, J. III AU - Worrell, G.A. AU - Miller, K.J. AU - Hermes, D. TI - Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 43 PY - 2023 IS - 39 SP - 6697 EP - 6711 PG - 15 SN - 0270-6474 DO - 10.1523/JNEUROSCI.2201-22.2023 UR - https://m2.mtmt.hu/api/publication/34227756 ID - 34227756 N1 - Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN 55902, United States Department of Neurology, Mayo Clinic Rochester, Rochester, MN 55902, United States Mayo Clinic Medical Scientist Training Program, Mayo Clinic Rochester, Rochester, MN 55902, United States Department of Neurologic Surgery, Mayo Clinic Rochester, Rochester, MN 55902, United States Department of Radiology, Mayo Clinic Rochester, Rochester, MN 55902, United States Export Date: 31 October 2023 CODEN: JNRSD Correspondence Address: Hermes, D.; Department of Physiology and Biomedical Engineering, United States; email: Hermes.Dora@mayo.edu LA - English DB - MTMT ER - TY - JOUR AU - Wu, D. AU - Schaper, F.L.W.V.J. AU - Jin, G. AU - Qi, L. AU - Du, J. AU - Wang, X. AU - Wang, Y. AU - Xu, C. AU - Wang, X. AU - Yu, T. AU - Fox, M.D. AU - Ren, L. TI - Human anterior thalamic stimulation evoked cortical potentials align with intrinsic functional connectivity JF - NEUROIMAGE J2 - NEUROIMAGE VL - 277 PY - 2023 SN - 1053-8119 DO - 10.1016/j.neuroimage.2023.120243 UR - https://m2.mtmt.hu/api/publication/34225839 ID - 34225839 N1 - Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China National Center for Neurological Disorders, Beijing, 100053, China Center of Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States Department of Pharmacy Phase I Clinical Trial Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China Berenson–Allen Center for Non-invasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA 02115, United States Martinos Center for Biomedical Imaging, Departments of Neurology and Radiology, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02115, United States Havard Medical School, Boston, MA 02115, United States Chinese Institute for Brain Research, Beijing, 102206, China Cited By :1 Export Date: 30 October 2023 CODEN: NEIME Correspondence Address: Ren, L.; Department of Neurology, No.45, Changchun Street, China; email: renlk2022@outlook.com LA - English DB - MTMT ER - TY - JOUR AU - Xie, Tao AU - Foutz, Thomas J. AU - Adamek, Markus AU - Swift, James R. AU - Inman, Cory S. AU - Manns, Joseph R. AU - Leuthardt, Eric C. AU - Willie, Jon T. AU - Brunner, Peter TI - Single-pulse electrical stimulation artifact removal using the novel matching pursuit-based artifact reconstruction and removal method (MPARRM) JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 20 PY - 2023 IS - 6 PG - 13 SN - 1741-2560 DO - 10.1088/1741-2552/ad1385 UR - https://m2.mtmt.hu/api/publication/34610439 ID - 34610439 AB - Objective. Single-pulse electrical stimulation (SPES) has been widely used to probe effective connectivity. However, analysis of the neural response is often confounded by stimulation artifacts. We developed a novel matching pursuit-based artifact reconstruction and removal method (MPARRM) capable of removing artifacts from stimulation-artifact-affected electrophysiological signals. Approach. To validate MPARRM across a wide range of potential stimulation artifact types, we performed a bench-top experiment in which we suspended electrodes in a saline solution to generate 110 types of real-world stimulation artifacts. We then added the generated stimulation artifacts to ground truth signals (stereoelectroencephalography signals from nine human subjects recorded during a receptive speech task), applied MPARRM to the combined signal, and compared the resultant denoised signal with the ground truth signal. We further applied MPARRM to artifact-affected neural signals recorded from the hippocampus while performing SPES on the ipsilateral basolateral amygdala in nine human subjects. Main results. MPARRM could remove stimulation artifacts without introducing spectral leakage or temporal spread. It accommodated variable stimulation parameters and recovered the early response to SPES within a wide range of frequency bands. Specifically, in the early response period (5-10 ms following stimulation onset), we found that the broadband gamma power (70-170 Hz) of the denoised signal was highly correlated with the ground truth signal ( R=0.98 +/- 0.02 , Pearson), and the broadband gamma activity of the denoised signal faithfully revealed the responses to the auditory stimuli within the ground truth signal with 94%+/- 1.47% sensitivity and 99%+/- 1.01% specificity. We further found that MPARRM could reveal the expected temporal progression of broadband gamma activity along the anterior-posterior axis of the hippocampus in response to the ipsilateral amygdala stimulation. Significance. MPARRM could faithfully remove SPES artifacts without confounding the electrophysiological signal components, especially during the early-response period. This method can facilitate the understanding of the neural response mechanisms of SPES. LA - English DB - MTMT ER - TY - CHAP AU - Adkisson, P. AU - Fridman, G.Y. AU - Steinhardt, C.R. ED - Riccardo, Barbieri TI - Difference in Network Effects of Pulsatile and Galvanic Stimulation T2 - 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) VL - 2022-July PB - IEEE CY - Piscataway (NJ) SN - 9781728127828 PY - 2022 SP - 3093 EP - 3099 PG - 7 DO - 10.1109/EMBC48229.2022.9871812 UR - https://m2.mtmt.hu/api/publication/34227766 ID - 34227766 N1 - Export Date: 31 October 2023 Correspondence Address: Adkisson, P.; Johns Hopkins School of Medicine, United States; email: paul.wesley.adkisson@gmail.com LA - English DB - MTMT ER - TY - JOUR AU - Baek, Kwangyeol AU - Park, Chae Ri AU - Jang, Siwan AU - Shim, Woo Hyun AU - Kim, Young Ro TI - Anesthetic modulations dissociate neuroelectric characteristics between sensory-evoked and spontaneous activities across bilateral rat somatosensory cortical laminae JF - SCIENTIFIC REPORTS J2 - SCI REP VL - 12 PY - 2022 IS - 1 SN - 2045-2322 DO - 10.1038/s41598-022-13759-0 UR - https://m2.mtmt.hu/api/publication/33001901 ID - 33001901 N1 - Funding Agency and Grant Number: National Institutes of Health [1R21EY02637901, 5R01MH111438-03]; Korea government [HI18C2383, 2021R1A1C2007251]; Basic Science Research Program through the National Research Foundation (NRF) of Korea - Ministry of Education [2018R1A6A3A01013571]; Ministry of Science and ICT (MSIT) through the NRF of Korea [2021H1D3A2A01099707]; Institute of Information & communications Technology Planning & Evaluation (IITP) - Korea government (MSIT) [2020-0-01450]; Pusan National University; BK21 Four program, Korean Southeast Center for the 4th Industrial Revolution Leader Education - Ministry of Education of South Korea Funding text: This research was supported by grants from the National Institutes of Health (1R21EY02637901 and 5R01MH111438-03), grants of the Korea government (grant number: HI18C2383 and 2021R1A1C2007251), Basic Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Education (2018R1A6A3A01013571), the Brain Pool program funded by the Ministry of Science and ICT (MSIT) through the NRF of Korea (2021H1D3A2A01099707), Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2020-0-01450, Artificial Intelligence Convergence Research Center [Pusan National University]), Pusan National University Research Grant 2019 and the BK21 Four program, Korean Southeast Center for the 4th Industrial Revolution Leader Education funded by Ministry of Education of South Korea. We also thank the Biomedical Computing core facility at the ConveRgence mEDIcine research cenTer (CREDIT), Asan Medical Center for their technical support and instrumentation. LA - English DB - MTMT ER - TY - JOUR AU - Boulogne, Sebastien AU - Pizzo, Francesca AU - Chatard, Benoit AU - Roehri, Nicolas AU - Catenoix, Helene AU - Ostrowsky-Coste, Karine AU - Giusiano, Bernard AU - Guenot, Marc AU - Carron, Romain AU - Bartolomei, Fabrice AU - Rheims, Sylvain TI - Functional connectivity and epileptogenicity of nodular heterotopias: A single-pulse stimulation study JF - EPILEPSIA J2 - EPILEPSIA VL - 63 PY - 2022 IS - 4 SP - 961 EP - 973 PG - 13 SN - 0013-9580 DO - 10.1111/epi.17168 UR - https://m2.mtmt.hu/api/publication/33007471 ID - 33007471 N1 - Department of Functional Neurology and Epileptology, Hospices Civils de Lyon and University of Lyon, Lyon, France Lyon's Neurosciences Research Center, INSERM U1028, CNRS 5292, Lyon, France Lyon 1 University, Villeurbanne, France Inserm, INS, Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, France Epileptology and Cerebral Rythmology Department, Assistance Publique – Hôpitaux de Marseille, Marseille, France Epileptology, Sleep Disorders and Functional Pediatric Neurology, Hospices Civils de Lyon and University of Lyon, Lyon, France Department of Functional Neurosurgery, Hospices Civils de Lyon and University of Lyon, Lyon, France Department of Functional Neurosurgery, Assistance Publique –Hôpitaux de Marseille, Marseille, France Cited By :4 Export Date: 31 October 2023 CODEN: EPILA Correspondence Address: Boulogne, S.; Department of Functional Neurology and Epileptology, France; email: sebastien.boulogne@chu-lyon.fr AB - Objective Nodular heterotopias (NHs) are malformations of cortical development associated with drug-resistant focal epilepsy with frequent poor surgical outcome. The epileptogenic network is complex and can involve the nodule, the overlying cortex, or both. Single-pulse electrical stimulation (SPES) during stereo-electroencephalography (SEEG) allows the investigation of functional connectivity between the stimulated and responsive cortices by eliciting cortico-cortical evoked potentials (CCEPs). We used SPES to analyze the NH connectome and its relation to the epileptogenic network organization. Methods We retrospectively studied 12 patients with NH who underwent 1 Hz or 0.2 Hz SPES of NH during SEEG. Outbound connectivity (regions where CCEPs were elicited by NH stimulation) and inbound connectivity (regions where stimulation elicited CCEPs in the NH) were searched. SEEG channels were then classified as "heterotopic" (located within the NH), "connected" (located in normotopic cortex and showing connectivity with the NH), and "unconnected." We used the epileptogenicity index (EI) to quantify implication of channels in the seizure-onset zone and to classify seizures as heterotopic, normotopic, and normo-heterotopic. Results One hundred thirty-five outbound and 72 inbound connections were found. Three patients showed connectivity between hippocampus and NH, and seven patients showed strong internodular connectivity. A total of 39 seizures were analyzed: 23 normo-heterotopic, 12 normotopic, and 4 heterotopic. Logistic regression found that "connected" channels were significantly (p = 8.4e-05) more likely to be epileptogenic than "unconnected" channels (odds ratio 4.71, 95% confidence interval (CI) [2.17, 10.21]) and heterotopic channels were also significantly (p = .024) more epileptogenic than "unconnected" channels (odds ratio 3.29, 95% CI [1.17, 9.23]). Significance SPES reveals widespread connectivity between NH and normotopic regions. Those connected regions show higher epileptogenicity. SPES might be useful to assess NH epileptogenic network. LA - English DB - MTMT ER - TY - JOUR AU - Fan, Joline M. AU - Lee, Anthony T. AU - Kudo, Kiwamu AU - Ranasinghe, Kamalini G. AU - Morise, Hirofumi AU - Findlay, Anne M. AU - Kirsch, Heidi E. AU - Chang, Edward F. AU - Nagarajan, Srikantan S. AU - Rao, Vikram R. TI - Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy JF - BRAIN COMMUNICATIONS J2 - BRAIN COMMUN VL - 4 PY - 2022 IS - 3 PG - 12 SN - 2632-1297 DO - 10.1093/braincomms/fcac104 UR - https://m2.mtmt.hu/api/publication/33007467 ID - 33007467 N1 - Funding Agency and Grant Number: National Institutes of Health [TL1TR001871-05, T32EB001631, R01EB022717, R01NS100440, R01AG062196, R01DC013979, R01DC176960, R01DC017091, K08AG058749]; DOD CDMRP grant [W81XWH1810741]; Larry L. Hillblom Foundation [2019-A-013SUP]; Alzheimer's Association [AARG-21849773]; UCSF; Doris Duke Physician Scientist Fellowship; Ernest Gallo Foundation Distinguished Professorship in Neurology at UCSF; Ricoh's MEG Research Group; UCOP [MRP17-454755] Funding text: Research reported in this publication was supported by National Institutes of Health grants under the award numbers: TL1TR001871-05, T32EB001631, R01EB022717, R01NS100440, R01AG062196, R01DC013979, R01DC176960, R01DC017091, and K08AG058749. Additional support was provided by a UCOP grant MRP17-454755, a DOD CDMRP grant W81XWH1810741, a grant from the Larry L. Hillblom Foundation 2019-A-013SUP, a grant from the Alzheimer's Association AARG-21849773, and a research contract between Ricoh's MEG Research Group and UCSF. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the funding agencies. J.M.F. is supported under the Doris Duke Physician Scientist Fellowship. V.R.R. is supported by the Ernest Gallo Foundation Distinguished Professorship in Neurology at UCSF. AB - Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (>= 50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, p(fdr) < 0.001; beta, p(fdr) < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.To prognosticate outcomes with neurostimulation for epilepsy, Fan et al. investigate functional network connectivity measured non-invasively with magnetoencephalography as a novel biomarker for effectiveness of responsive neurostimulation (RNS) therapy. Resting-state functional connectivity in alpha and beta frequency bands predicted response to subsequent RNS therapy and correlated with seizure frequency reduction. LA - English DB - MTMT ER - TY - JOUR AU - Lemarechal, Jean-Didier AU - Jedynak, Maciej AU - Trebaul, Lena AU - Boyer, Anthony AU - Tadel, Francois AU - Bhattacharjee, Manik AU - Deman, Pierre AU - Tuyisenge, Viateur AU - Ayoubian, Leila AU - Hugues, Etienne AU - Chanteloup-Foret, Blandine AU - Saubat, Carole AU - Zouglech, Raouf AU - Mejia, Gina Catalina Reyes AU - Tourbier, Sebastien AU - Hagmann, Patric AU - Adam, Claude AU - Barba, Carmen AU - Bartolomei, Fabrice AU - Blauwblomme, Thomas AU - Curot, Jonathan AU - Dubeau, Francois AU - Francione, Stefano AU - Garces, Mercedes AU - Hirsch, Edouard AU - Landre, Elizabeth AU - Liu, Sinclair AU - Maillard, Louis AU - Metsahonkala, Eeva-Liisa AU - Mindruta, Ioana AU - Nica, Anca AU - Pail, Martin AU - Petrescu, Ana Maria AU - Rheims, Sylvain AU - Rocamora, Rodrigo AU - Schulze-Bonhage, Andreas AU - Szurhaj, William AU - Taussig, Delphine AU - Valentin, Antonio AU - Wang, Haixiang AU - Kahane, Philippe AU - George, Nathalie AU - David, Olivier TI - A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials JF - BRAIN J2 - BRAIN VL - 145 PY - 2022 IS - 5 SP - 1653 EP - 1667 PG - 15 SN - 0006-8950 DO - 10.1093/brain/awab362 UR - https://m2.mtmt.hu/api/publication/33007469 ID - 33007469 N1 - Funding Agency and Grant Number: European Research Council under the European Union [616268 F-TRACT]; European Union [785907, 945539]; French `Investissements d'avenir' programme [ANR-11-INBS-0006, ANR-10-IAIHU-06]; Swiss National Science Foundation [CRSII5_170873] Funding text: The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 616268 F-TRACT, the European Union's Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 785907 and 945539 (Human Brain Project SGA2 and SGA3) and from the French `Investissements d'avenir' programme under grant numbers ANR-11-INBS-0006 and ANR-10-IAIHU-06. P.H. was supported by Swiss National Science Foundation grant #CRSII5_170873. AB - Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings. LA - English DB - MTMT ER - TY - JOUR AU - Luo, Lu AU - Chen, Guanpeng AU - Li, Siqi AU - Wang, Jing AU - Wang, Qian AU - Fang, Fang TI - Distinct roles of theta and gamma rhythms in inter-areal interaction in human visual cortex revealed by cortico-cortical evoked potentials JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 15 PY - 2022 IS - 5 SP - 1048 EP - 1050 PG - 3 SN - 1935-861X DO - 10.1016/j.brs.2022.07.056 UR - https://m2.mtmt.hu/api/publication/33231072 ID - 33231072 N1 - Funding Agency and Grant Number: National Science and Technology Innovation 2030 Major Program [2022ZD0204802, 2022ZD0204804]; National Natural Science Foundation of China [31930053, 32171039]; Beijing Academy of Artificial Intelligence (BAAI) Funding text: This work was supported by the National Science and Technology Innovation 2030 Major Program (2022ZD0204802, 2022ZD0204804) and the National Natural Science Foundation of China (31930053, 32171039) and Beijing Academy of Artificial Intelligence (BAAI). LA - English DB - MTMT ER - TY - JOUR AU - Mercier, Manuel R. AU - Dubarry, Anne-Sophie AU - Tadel, Francois AU - Avanzini, Pietro AU - Axmacher, Nikolai AU - Cellier, Dillan AU - Del Vecchio, Maria AU - Hamilton, Liberty S. AU - Hermes, Dora AU - Kahana, Michael J. AU - Knight, Robert T. AU - Llorens, Anais AU - Megevand, Pierre AU - Melloni, Lucia AU - Miller, Kai J. AU - Piai, Vitoria AU - Puce, Aina AU - Ramsey, Nick F. AU - Schwiedrzik, Caspar M. AU - Smith, Sydney E. AU - Stolk, Arjen AU - Swann, Nicole C. AU - Vansteensel, Mariska J. AU - Voytek, Bradley AU - Wang, Liang AU - Lachaux, Jean-Philippe AU - Oostenveld, Robert TI - Advances in human intracranial electroencephalography research, guidelines and good practices JF - NEUROIMAGE J2 - NEUROIMAGE VL - 260 PY - 2022 PG - 61 SN - 1053-8119 DO - 10.1016/j.neuroimage.2022.119438 UR - https://m2.mtmt.hu/api/publication/33167383 ID - 33167383 N1 - Funding Agency and Grant Number: EU [798853]; NIH/NIBIB [R01EB026299]; NIMH/NIH [R01MH122258]; NIH/NINDS [2 R01 NS021135, 1U19NS107609-01]; NIH/NIDCD [U01 DC016686]; NWO [17619]; Swiss National Science Foundation [167836, 194507]; Max Planck Society; Emmy Noether Program of the German Research Foundation [SCHW1683/2-1] Funding text: RM is supported by EU-REA H2020 MSCA -IF 798853. FT is supported by NIH/NIBIB R01EB026299. DH is supported by NIMH/NIH R01MH122258. RTK is supported by NIH/NINDS 2 R01 NS021135, NIH/NINDS 1U19NS107609-01. NFR and MJV are supported by NIH/NIDCD U01 DC016686 and NWO 17619. PM is supported by Swiss National Science Foundation grants 167836 and 194507. LM is supported by the Max Planck Society. AP is supported by NIH/NIBIB R01EB030896. CMS is supported by the Emmy Noether Program of the German Research Foundation (SCHW1683/2-1). AB - Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. M the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (H) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (Hi) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research. LA - English DB - MTMT ER - TY - JOUR AU - Moorjani, Samira AU - Walvekar, Sarita AU - Fetz, Eberhard E. AU - Perlmutter, Steve I TI - Movement-dependent electrical stimulation for volitional strengthening of cortical connections in behaving monkeys JF - PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA J2 - P NATL ACAD SCI USA VL - 119 PY - 2022 IS - 27 PG - 12 SN - 0027-8424 DO - 10.1073/pnas.2116321119 UR - https://m2.mtmt.hu/api/publication/33231077 ID - 33231077 N1 - Funding Agency and Grant Number: NIH [RR00166, NS12542]; NSF Center for Neurotechnology Grant [EEC-1028725] Funding text: We thank Larry Shupe and Jatin Sonavane for provid-ing programming, hardware, and software assistance. We also thank Rebekah Schaefer, Andrew Bogaard, and Robert Robinson for assistance with animal care, handling, training, and surgeries. This research used statistical consulting resour-ces provided by the Center for Statistics and the Social Sciences at the University ofWashington. We especially thank Sara LaPlante for assistance with linear-mixed-model analyses. This work was supported by NIH Grants RR00166 and NS12542 and NSF Center for Neurotechnology Grant EEC-1028725. AB - Correlated activity of neurons can lead to long-term strengthening or weakening of the connections between them. In addition, the behavioral context, imparted by execution of physical movements or the presence of a reward, can modulate the plasticity induced by Hebbian mechanisms. In the present study, we have combined behavior and induced neuronal correlations to strengthen connections in the motor cortex of adult behaving monkeys. Correlated activity was induced using an electrical-conditioning protocol in which stimuli gated by voluntary movements were used to produce coactivation of neurons at motor-cortical sites involved in those movements. Delivery of movement-dependent stimulation resulted in small increases in the strength of associated cortical connections immediately after conditioning. Remarkably, when paired with further repetition of the movements that gated the conditioning stimuli, there were substantially larger gains in the strength of cortical connections, which occurred in a use-dependent manner, without delivery of additional conditioning stimulation. In the absence of such movements, little change was observed in the strength of motor-cortical connections. Performance of the motor behavior in the absence of conditioning also did not produce any changes in connectivity. Our results show that combining movement-gated stimulation with further natural use of the "conditioned" pathways after stimulation ends can produce use-dependent strengthening of connections in adult primates, highlighting an important role for behavior in cortical plasticity. Our data also provide strong support for combining movement-gated stimulation with use-dependent physical rehabilitation for strengthening connections weakened by a stroke or spinal cord injury. LA - English DB - MTMT ER - TY - JOUR AU - Parmigiani, S. AU - Mikulan, E. AU - Russo, S. AU - Sarasso, S. AU - Zauli, F. M. AU - Rubino, A. AU - Cattani, A. AU - Fecchio, M. AU - Giampiccolo, D. AU - Lanzone, J. AU - D'Orio, P. AU - Del Vecchio, M. AU - Avanzini, P. AU - Nobili, L. AU - Sartori, I AU - Massimini, M. AU - Pigorini, A. TI - Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 15 PY - 2022 IS - 3 SP - 664 EP - 675 PG - 12 SN - 1935-861X DO - 10.1016/j.brs.2022.04.007 UR - https://m2.mtmt.hu/api/publication/32961414 ID - 32961414 N1 - Department of Biomedical and Clinical Sciences “L. Sacco” Università degli Studi di Milano, Milan, Italy Department of Philosophy “Piero Martinetti”, Università degli Studi di Milano, Milan, Italy “Claudio Munari” Epilepsy Surgery Centre, Azienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda, Milan, Italy Department of Mathematics & Statistics, Boston University, Boston, MA, United States Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States Department of Neurosurgery, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom Institute of Neurosciences, Cleveland Clinic London, London, United Kingdom Department of Systems Medicine, Neuroscience, University of Rome Tor Vergata, Rome, Italy Istituti Clinici Scientifici Maugeri, IRCCS, Neurorehabilitation Department of Milano Institute, Milan, Italy Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy Department of Medicine and Surgery, Unit of Neuroscience, University of Parma, Parma, Italy Child Neuropsychiatry, IRCCS Istituto G. Gaslini, Genova, Italy Department of Neuroscience, DINOGMI, University of Genoa, Genoa, Italy Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research, Toronto, Canada Department of Biomedical, Surgical and Dental Sciences, University of Milano, Milan, Italy Cited By :5 Export Date: 30 October 2023 Correspondence Address: Pigorini, A.; Department of Biomedical and Clinical Sciences “L. Sacco” Università degli Studi di MilanoItaly; email: andrea.pigorini@unimi.it AB - Background: Cortico-cortical evoked potentials (CCEPs) recorded by stereo-electroencephalography (SEEG) are a valuable tool to investigate brain reactivity and effective connectivity. However, invasive recordings are spatially sparse since they depend on clinical needs. This sparsity hampers systematic comparisons across-subjects, the detection of the whole-brain effects of intracortical stimulation, as well as their relationships to the EEG responses evoked by non-invasive stimuli. Objective: To demonstrate that CCEPs recorded by high-density electroencephalography (hd-EEG) provide additional information with respect SEEG alone and to provide an open, curated dataset to allow for further exploration of their potential. Methods: The dataset encompasses SEEG and hd-EEG recordings simultaneously acquired during Single Pulse Electrical Stimulation (SPES) in drug-resistant epileptic patients (N 1/4 36) in whom stimulations were delivered with different physical, geometrical, and topological parameters. Differences in CCEPs were assessed by amplitude, latency, and spectral measures. Results: While invasively and non-invasively recorded CCEPs were generally correlated, differences in pulse duration, angle and stimulated cortical area were better captured by hd-EEG. Further, intracranial stimulation evoked site-specific hd-EEG responses that reproduced the spectral features of EEG responses to transcranial magnetic stimulation (TMS). Notably, SPES, albeit unperceived by subjects, elicited scalp responses that were up to one order of magnitude larger than the responses typically evoked by sensory stimulation in awake humans. Conclusions: CCEPs can be simultaneously recorded with SEEG and hd-EEG and the latter provides a reliable descriptor of the effects of SPES as well as a common reference to compare the whole-brain LA - English DB - MTMT ER - TY - JOUR AU - Parvizi, Josef AU - Veit, Michael J. AU - Barbosa, Daniel A. N. AU - Kucyi, Aaron AU - Perry, Claire AU - Parker, Jonathon J. AU - Shivacharan, Rajat S. AU - Chen, Fengyixuan AU - Yih, Jennifer AU - Gross, James J. AU - Fisher, Robert AU - McNab, Jennifer A. AU - Falco-Walter, Jessica AU - Halpern, Casey H. TI - Complex negative emotions induced by electrical stimulation of the human hypothalamus JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 15 PY - 2022 IS - 3 SP - 615 EP - 623 PG - 9 SN - 1935-861X DO - 10.1016/j.brs.2022.04.008 UR - https://m2.mtmt.hu/api/publication/33007466 ID - 33007466 N1 - Funding Agency and Grant Number: Na-tional Science Foundation [BCS1358907] Funding text: Acknowledgments We thank members of the Stanford Epilepsy Monitoring Unit for assistance with data collection. This work was supported by Na-tional Science Foundation [BCS1358907] . AB - Background: Stimulation of the ventromedial hypothalamic region in animals has been reported to cause attack behavior labeled as sham-rage without offering information about the internal affective state of the animal being stimulated. Objective: To examine the causal effect of electrical stimulation near the ventromedial region of the human hypothalamus on the human subjective experience and map the electrophysiological connectivity of the hypothalamus with other brain regions. Methods: We examined a patient (Subject S20_150) with intracranial electrodes implanted across 170 brain regions, including the hypothalamus. We combined direct electrical stimulation with tractography, cortico-cortical evoked potentials (CCEP), and functional connectivity using resting state intracranial electroencephalography (EEG). Results: Recordings in the hypothalamus did not reveal any epileptic abnormalities. Electrical stimulations near the ventromedial hypothalamus induced profound shame, sadness, and fear but not rage or anger. When repeated single-pulse stimulations were delivered to the hypothalamus, significant responses were evoked in the amygdala, hippocampus, ventromedial-prefrontal and orbitofrontal cortices, anterior cingulate, as well as ventral-anterior and dorsal-posterior insula. The time to first peak of these evoked responses varied and earliest propagations correlated best with the measures of resting-state EEG connectivity and structural connectivity. Conclusion: This patient's case offers details about the affective state induced by the stimulation of the human hypothalamus and provides causal evidence relevant to current theories of emotion. The complexity of affective state induced by the stimulation of the hypothalamus and the profile of hypothalamic electrophysiological connectivity suggest that the hypothalamus and its connected structures ought to be seen as causally important for human affective experience. (c) 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). LA - English DB - MTMT ER - TY - JOUR AU - Patel, Prachi AU - Khalijhinejad, Bahar AU - Herrero, Jose L. AU - Bickel, Stephan AU - Mehta, Ashesh D. AU - Mesgarani, Nima TI - Improved speech hearing in noise with invasive electrical brain stimulation JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 42 PY - 2022 IS - 17 PG - 31 SN - 0270-6474 DO - 10.1523/JNEUROSCI.1468-21.2022 UR - https://m2.mtmt.hu/api/publication/33006199 ID - 33006199 N1 - Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, United States Department of Electrical Engineering, Columbia University, New York, NY 10027, United States Hofstra Northwell School of Medicine, New York, NY 11549, United States Feinstein Institute for Medical Research, New York, NY 11030, United States Cited By :1 Export Date: 30 October 2023 CODEN: JNRSD Correspondence Address: Mesgarani, N.; Mortimer B. Zuckerman Mind Brain Behavior Institute, United States; email: nima@ee.columbia.edu AB - Speech perception in noise is a challenging everyday task with which many listeners have difficulty. Here, we report a case in which electrical brain stimulation of implanted intracranial electrodes in the left planum temporale (PT) of a neurosurgical patient significantly and reliably improved subjectivequality (up to 50%) and objective intelligibility (up to 97%) of speech in noise perception. Stimulation resulted in a selective enhancement of speech sounds compared to the background noises. Thereceptive fields of the PT sites whose stimulation improved speech perception were tuned to spectrally broad and rapidly changing sounds. Corticocortical evoked potential analysis revealed that the PT sites were located between the sites in Heschl's gyrus (HG) and the superior temporal gyrus (STG). Moreover, the discriminability of speech from nonspeech sounds increased in population neural responses from HG to the PT to the STG sites. These findings causally implicate the PT in background noise suppression and may point to a novel potential neuroprosthetic solution to assist in the challenging task of speech perception in noise.SignificanceSpeech perception in noise remains a challenging task for many individuals. Here, we present a case in which the electrical brain stimulation of intracranially implanted electrodes in the planum temporale of a neurosurgical patient significantly improved both the subjective quality (up to 50%) and objective intelligibility (up to 97%) of speech perception in noise. Stimulation resulted in a selective enhancement of speech sounds compared to the background noises. Our local and network-level functional analyses placed the planum temporale sites in between the sites in the primary auditory areas in Heschl's gyrus and nonprimary auditory areas in the superior temporal gyrus. These findings causally implicate planum temporale in acoustic scene analysis and suggest potential neuroprosthetic applications to assist hearing in noise. LA - English DB - MTMT ER - TY - JOUR AU - Paulk, Angelique C. AU - Zelmann, Rina AU - Crocker, Britni AU - Widge, Alik S. AU - Dougherty, Darin D. AU - Eskandar, Emad N. AU - Weisholtz, Daniel S. AU - Richardson, R. Mark AU - Cosgrove, G. Rees AU - Williams, Ziv M. AU - Cash, Sydney S. TI - Local and distant cortical responses to single pulse intracranial stimulation in the human brain are differentially modulated by specific stimulation parameters JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 15 PY - 2022 IS - 2 SP - 491 EP - 508 PG - 18 SN - 1935-861X DO - 10.1016/j.brs.2022.02.017 UR - https://m2.mtmt.hu/api/publication/33006200 ID - 33006200 N1 - Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, United States Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States Department of Neurology, Brigham and Women's Hospital, Boston, MA 02114, United States Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA 02114, United States Cited By :12 Export Date: 31 October 2023 Correspondence Address: Paulk, A.C.; Department of Neurology, United States; email: apaulk@mgh.harvard.edu AB - Background: Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses.Objective: To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated.Methods: We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites).Results: Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation.Conclusion: These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy. (C) 2022 The Authors. Published by Elsevier Inc. LA - English DB - MTMT ER - TY - JOUR AU - Ries, S.K. AU - Jordan, K. AU - Knight, R.T. AU - Berger, M. TI - Lesion-Behavior Awake Mapping with Direct Cortical and Subcortical Stimulation JF - NEUROMETHODS J2 - NEUROMETHODS VL - 180 PY - 2022 SP - 257 EP - 270 PG - 14 SN - 0893-2336 DO - 10.1007/978-1-0716-2225-4_14 UR - https://m2.mtmt.hu/api/publication/34227767 ID - 34227767 LA - English DB - MTMT ER - TY - JOUR AU - Sawada, Masahiro AU - Adolphs, Ralph AU - Dlouhy, Brian J. AU - Jenison, Rick L. AU - Rhone, Ariane E. AU - Kovach, Christopher K. AU - Greenlee, Jeremy D. W. AU - Howard, Matthew A. III AU - Oya, Hiroyuki TI - Mapping effective connectivity of human amygdala subdivisions with intracranial stimulation JF - NATURE COMMUNICATIONS J2 - NAT COMMUN VL - 13 PY - 2022 IS - 1 PG - 19 SN - 2041-1723 DO - 10.1038/s41467-022-32644-y UR - https://m2.mtmt.hu/api/publication/33231075 ID - 33231075 N1 - Funding Agency and Grant Number: National Institute of Health [R01_DC004290-20, U01_NS103780, 1S10OD025025-01]; Simons Collaboration on the Global Brain Funding text: Supported by grant from National Institute of Health R01_DC004290-20 to M.A.H., National Institute of Health U01_NS103780 and the Simons Collaboration on the Global Brain to R.A. Thisworkwas conducted on an MRI instrument funded by National Institutes of Health grant 1S10OD025025-01. We thank Kirill V. Nourski, Haiming Chen, Phillip. E. Gander, Christopher Garcia, and Hiroto Kawasaki for help with experiments, John Buatti and Colin P. Derdeyn for MRI scanner logistics, Mark A. Granner for safety monitoring, and Vince A. Magnotta for MRI technical consultation. AB - The amygdala is known to be engaged in emotional and autonomic function, yet the detailed functional connectivity of the human amygdala remains unclear. Here, the authors examine effective connectivity in the amygdala of patients with epilepsy using direct focal electrical stimulation.The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations. LA - English DB - MTMT ER - TY - JOUR AU - Scheid, Brittany H. AU - Bernabei, John M. AU - Khambhati, Ankit N. AU - Mouchtaris, Sofia AU - Jeschke, Jay AU - Bassett, Dani S. AU - Becker, Danielle AU - Davis, Kathryn A. AU - Lucas, Timothy AU - Doyle, Werner AU - Chang, Edward F. AU - Friedman, Daniel AU - Rao, Vikram R. AU - Litt, Brian TI - Intracranial electroencephalographic biomarker predicts effective responsive neurostimulation for epilepsy prior to treatment JF - EPILEPSIA J2 - EPILEPSIA VL - 63 PY - 2022 IS - 3 SP - 652 EP - 662 PG - 11 SN - 0013-9580 DO - 10.1111/epi.17163 UR - https://m2.mtmt.hu/api/publication/33007472 ID - 33007472 N1 - Funding Agency and Grant Number: Mirowski Family Foundation; National Institute of Neurological Disorders and Stroke; Pennsylvania Tobacco Fund; Citizens United for Research in Epilepsy Funding text: Mirowski Family Foundation; National Institute of Neurological Disorders and Stroke; Pennsylvania Tobacco Fund; Citizens United for Research in Epilepsy AB - Objective Despite the overall success of responsive neurostimulation (RNS) therapy for drug-resistant focal epilepsy, clinical outcomes in individuals vary significantly and are hard to predict. Biomarkers that indicate the clinical efficacy of RNS-ideally before device implantation-are critically needed, but challenges include the intrinsic heterogeneity of the RNS patient population and variability in clinical management across epilepsy centers. The aim of this study is to use a multicenter dataset to evaluate a candidate biomarker from intracranial electroencephalographic (iEEG) recordings that predicts clinical outcome with subsequent RNS therapy. Methods We assembled a federated dataset of iEEG recordings, collected prior to RNS implantation, from a retrospective cohort of 30 patients across three major epilepsy centers. Using ictal iEEG recordings, each center independently calculated network synchronizability, a candidate biomarker indicating the susceptibility of epileptic brain networks to RNS therapy. Results Ictal measures of synchronizability in the high-gamma band (95-105 Hz) significantly distinguish between good and poor RNS responders after at least 3 years of therapy under the current RNS therapy guidelines (area under the curve = .83). Additionally, ictal high-gamma synchronizability is inversely associated with the degree of therapeutic response. Significance This study provides a proof-of-concept roadmap for collaborative biomarker evaluation in federated data, where practical considerations impede full data sharing across centers. Our results suggest that network synchronizability can help predict therapeutic response to RNS therapy. With further validation, this biomarker could facilitate patient selection and help avert a costly, invasive intervention in patients who are unlikely to benefit. LA - English DB - MTMT ER - TY - JOUR AU - Smith, Ezra E. AU - Choi, Ki Sueng AU - Veerakumar, Ashan AU - Obatusin, Mosadoluwa AU - Howell, Bryan AU - Smith, Andrew H. AU - Tiruvadi, Vineet AU - Crowell, Andrea L. AU - Riva-Posse, Patricio AU - Alagapan, Sankaraleengam AU - Rozell, Christopher J. AU - Mayberg, Helen S. AU - Waters, Allison C. TI - Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate JF - FRONTIERS IN HUMAN NEUROSCIENCE J2 - FRONT HUM NEUROSCI VL - 16 PY - 2022 PG - 11 SN - 1662-5161 DO - 10.3389/fnhum.2022.939258 UR - https://m2.mtmt.hu/api/publication/33167384 ID - 33167384 N1 - Private Practice, Pima, Tucson, AZ, United States Departments of Psychiatry, Neuroscience, Neurology, Neurosurgery and Radiology, Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States Department of Psychiatry, Schulich School of Medicine and Dentistry, London, ON, Canada Department of Biomedical Engineering, Duke University, Durham, NC, United States Emory University School of Medicine, Atlanta, GA, United States Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA, United States Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States Cited By :3 Export Date: 31 October 2023 Correspondence Address: Waters, A.C.; Departments of Psychiatry, United States; email: allison.waters@mssm.edu AB - Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features-evoked power and phase clustering-in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50-150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4-7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2-4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology. LA - English DB - MTMT ER - TY - JOUR AU - Smith, Rachel J. AU - Hays, Mark A. AU - Kamali, Golnoosh AU - Coogan, Christopher AU - Crone, Nathan E. AU - Kang, Joon Y. AU - Sarma, Sridevi V TI - Stimulating native seizures with neural resonance: a new approach to localize the seizure onset zone JF - BRAIN J2 - BRAIN VL - 145 PY - 2022 IS - 11 SP - 3886 EP - 3900 PG - 15 SN - 0006-8950 DO - 10.1093/brain/awac214 UR - https://m2.mtmt.hu/api/publication/33687758 ID - 33687758 N1 - Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, United States Department of Neurology, Johns Hopkins University, Baltimore, MD 21287, United States Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, United States Cited By :3 Export Date: 20 June 2023 CODEN: BRAIA Correspondence Address: Smith, R.J.318 Hackerman Hall 3400 N. Charles St, United States; email: rsmit249@jhu.edu AB - Successful outcomes in epilepsy surgery rely on the accurate localization of the seizure onset zone. Localizing the seizure onset zone is often a costly and time-consuming process wherein a patient undergoes intracranial EEG monitoring, and a team of clinicians wait for seizures to occur. Clinicians then analyse the intracranial EEG before each seizure onset to identify the seizure onset zone and localization accuracy increases when more seizures are captured. In this study, we develop a new approach to guide clinicians to actively elicit seizures with electrical stimulation. We propose that a brain region belongs to the seizure onset zone if a periodic stimulation at a particular frequency produces large amplitude oscillations in the intracranial EEG network that propagate seizure activity. Such responses occur when there is 'resonance' in the intracranial EEG network, and the resonant frequency can be detected by observing a sharp peak in the magnitude versus frequency response curve, called a Bode plot. To test our hypothesis, we analysed single-pulse electrical stimulation response data in 32 epilepsy patients undergoing intracranial EEG monitoring. For each patient and each stimulated brain region, we constructed a Bode plot by estimating a transfer function model from the intracranial EEG 'impulse' or single-pulse electrical stimulation response. The Bode plots were then analysed for evidence of resonance. First, we showed that when Bode plot features were used as a marker of the seizure onset zone, it distinguished successful from failed surgical outcomes with an area under the curve of 0.83, an accuracy that surpassed current methods of analysis with cortico-cortical evoked potential amplitude and cortico-cortical spectral responses. Then, we retrospectively showed that three out of five native seizures accidentally triggered in four patients during routine periodic stimulation at a given frequency corresponded to a resonant peak in the Bode plot. Last, we prospectively stimulated peak resonant frequencies gleaned from the Bode plots to elicit seizures in six patients, and this resulted in an induction of three seizures and three auras in these patients. These findings suggest neural resonance as a new biomarker of the seizure onset zone that can guide clinicians in eliciting native seizures to more quickly and accurately localize the seizure onset zone. Inducing seizures with electrical stimulation could help clinicians localize the seizure onset zone in patients with epilepsy. Smith et al. present a novel method based on neural resonance that can guide clinicians in actively eliciting seizures, thereby expediting the intracranial monitoring process for seizure localization. LA - English DB - MTMT ER - TY - JOUR AU - Titov, Oleg AU - Bykanov, Andrey AU - Pitskhelauri, David AU - Danilov, Gleb TI - Neuromonitoring of the language pathways using cortico-cortical evoked potentials: a systematic review and meta-analysis JF - NEUROSURGICAL REVIEW J2 - NEUROSURG REV VL - 45 PY - 2022 IS - 3 SP - 1883 EP - 1894 PG - 12 SN - 0344-5607 DO - 10.1007/s10143-021-01718-8 UR - https://m2.mtmt.hu/api/publication/32961415 ID - 32961415 N1 - Funding Agency and Grant Number: Russian Foundation for Basic Research [19-29-01231] Funding text: The reported study was supported by the Russian Foundation for Basic Research (grant number 19-29-01231). AB - Cortico-cortical evoked potentials (CCEPs) are a surge in activity of one cortical zone caused by stimulation of another cortical zone. Recording of CCEP may be a useful method of intraoperative monitoring of the brain pathways, particularly of the language-related tracts. We aimed to conduct a systematic review and meta-analysis, dedicated to the clinical question: Does the CCEP recording effectively predict the postoperative speech deficits in neurosurgical patients? We conducted language-restricted PubMed, Google Scholar, Scopus, and Cochrane database search for eligible studies of CCEP published until March 2021. There were 4 articles (3 case series and 1 case report), which met our inclusion/exclusion criteria. A total of 32 patients (30 cases of tumors and 2 cavernomas) included in the analysis were divided into two cohorts - quantitative and qualitative, in accordance with the method of evaluating changes in the amplitude of CCEP after the lesion resection and postoperative alterations in speech function. Quantitative variables were studied using the Spearman rank correlation coefficient. Categorical variables were compared in groups by Fisher's exact test. We found a strong positive correlation between the decrease in the N1 wave amplitude and the severity of postoperative speech deficits (quantitative cohort: r = 0.57, p = 0.01; qualitative cohort: p = 0.02). Thus, the CCEP method using the N1 wave amplitude as a marker enables to effectively predict postoperative speech outcomes. Nevertheless, the low level of evidence for the included works indicated the necessity for additional research on this issue. LA - English DB - MTMT ER - TY - JOUR AU - Togo, Masaya AU - Matsumoto, Riki AU - Usami, Kiyohide AU - Kobayashi, Katsuya AU - Takeyama, Hirofumi AU - Nakae, Takuro AU - Shimotake, Akihiro AU - Kikuchi, Takayuki AU - Yoshida, Kazumichi AU - Matsuhashi, Masao AU - Kunieda, Takeharu AU - Miyamoto, Susumu AU - Takahashi, Ryosuke AU - Ikeda, Akio TI - Distinct connectivity patterns in human medial parietal cortices: Evidence from standardized connectivity map using cortico-cortical evoked potential JF - NEUROIMAGE J2 - NEUROIMAGE VL - 263 PY - 2022 PG - 14 SN - 1053-8119 DO - 10.1016/j.neuroimage.2022.119639 UR - https://m2.mtmt.hu/api/publication/33229822 ID - 33229822 N1 - Funding Agency and Grant Number: Ministry of Education, Culture, Sports, Science and Technology (MEXT) KAKENHI; Ministry of Education, Culture, Sports, Science and Technology (MEXT) KAKENHI [18K19514, 20H05471, 22H04777, 22H02945, 20K16575, 19H03574] Funding text: This work was supported by the Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) KAKENHI. RM reports grants from MEXT, KAKENHI 18K19514, 20H05471, 22H04777, 22H02945, MT reports grants from 20K16575, and AI reports grants from 19H03574. We would like to thank Prof. Naoyuki Sato for his technical advice and help in performing the per-mutation test. AB - The medial parietal cortices are components of the default mode network (DMN), which are active in the resting state. The medial parietal cortices include the precuneus and the dorsal posterior cingulate cortex (dPCC). Few studies have mentioned differences in the connectivity in the medial parietal cortices, and these differences have not yet been precisely elucidated. Electrophysiological connectivity is essential for understanding cortical function or functional differences. Since little is known about electrophysiological connections from the medial parietal cortices in humans, we evaluated distinct connectivity patterns in the medial parietal cortices by constructing a standardized connectivity map using cortico-cortical evoked potential (CCEP). This study included nine patients with partial epilepsy or a brain tumor who underwent chronic intracranial electrode placement covering the medial parietal cortices. Single-pulse electrical stimuli were delivered to the medial parietal cortices (38 pairs of electrodes). Responses were standardized using the z-score of the baseline activity, and a response density map was constructed in the Montreal Neurological Institutes (MNI) space. The precuneus tended to connect with the inferior parietal lobule (IPL), the occipital cortex, superior parietal lobule (SPL), and the dorsal premotor area (PMd) (the four most active regions, in descending order), while the dPCC tended to connect to the middle cingulate cortex, SPL, precuneus, and IPL. The connectivity pattern differs significantly between the precuneus and dPCC stimulation ( p < 0.05). Regarding each part of the medial parietal cortices, the distributions of parts of CCEP responses resembled those of the functional connectivity database. Based on how the dPCC was connected to the medial frontal area, SPL, and IPL, its connectivity pattern could not be explained by DMN alone, but suggested a mixture of DMN and the frontoparietal cognitive network. These findings improve our understanding of the connectivity profile within the medial parietal cortices. The electrophysiological connectivity is the basis of propagation of electrical activities in patients with epilepsy. In addition, it helps us to better understand the epileptic network arising from the medial parietal cortices. LA - English DB - MTMT ER - TY - JOUR AU - Vlachos, Ioannis AU - Kugiumtzis, Dimitris AU - Palus, Milan TI - Phase-based causality analysis with partial mutual information from mixed embedding JF - CHAOS J2 - CHAOS VL - 32 PY - 2022 IS - 5 PG - 17 SN - 1054-1500 DO - 10.1063/5.0087910 UR - https://m2.mtmt.hu/api/publication/33231079 ID - 33231079 N1 - Funding Agency and Grant Number: Czech Science Foundation [GF21-14727K]; Czech Academy of Sciences Funding text: This study was supported by the Czech Science Foundation (Project No. GF21-14727K) and by the Czech Academy of Sciences, Praemium Academiae, awarded to M. Palus. AB - Instantaneous phases extracted from multivariate time series can retain information about the relationships between the underlying mechanisms that generate the series. Although phases have been widely used in the study of nondirectional coupling and connectivity, they have not found similar appeal in the study of causality. Herein, we present a new method for phase-based causality analysis, which combines ideas from the mixed embedding technique and the information-theoretic approach to causality in coupled oscillatory systems. We then use the introduced method to investigate causality in simulated datasets of bivariate, unidirectionally paired systems from combinations of Rossler, Lorenz, van der Pol, and Mackey-Glass equations. We observe that causality analysis using the phases can capture the true causal relation for coupling strength smaller than the analysis based on the amplitudes can capture. On the other hand, the causality estimation based on the phases tends to have larger variability, which is attributed more to the phase extraction process than the actual phase-based causality method. In addition, an application on real electroencephalographic data from an experiment on elicited human emotional states reinforces the usefulness of phases in causality identification. Published under an exclusive license by AIP Publishing. LA - English DB - MTMT ER - TY - JOUR AU - Wendt, Karen AU - Denison, Timothy AU - Foster, Gaynor AU - Krinke, Lothar AU - Thomson, Alix AU - Wilson, Saydra AU - Widge, Alik S. TI - Physiologically informed neuromodulation JF - JOURNAL OF THE NEUROLOGICAL SCIENCES J2 - J NEUROL SCI VL - 434 PY - 2022 PG - 8 SN - 0022-510X DO - 10.1016/j.jns.2021.120121 UR - https://m2.mtmt.hu/api/publication/33007468 ID - 33007468 N1 - Funding Agency and Grant Number: Minnesota Medical Discovery Team on Addictions [UH3NS100548, R01MH119384, R01NS113804, R01MH123634, R01MH124687]; MnDRIVE Brain Conditions Initiative [MC_UU_00003/3]; National Institutes of Health; Medical Research Council Funding text: Acknowledgements ASW acknowledges support from the Minnesota Medical Discovery Team on Addictions, the MnDRIVE Brain Conditions Initiative, and the National Institutes of Health (projects UH3NS100548, R01MH119384, R01NS113804, R01MH123634, and R01MH124687) . Tim Denison and Karen Wendt acknowledge support from the Medical Research Council (project MC_UU_00003/3) . AB - The rapid evolution of neuromodulation techniques includes an increasing amount of research into stimulation paradigms that are guided by patients' neurophysiology, to increase efficacy and responder rates. Treatment personalisation and target engagement have shown to be effective in fields such as Parkinson's disease, and closed-loop paradigms have been successfully implemented in cardiac defibrillators. Promising avenues are being explored for physiologically informed neuromodulation in psychiatry. Matching the stimulation frequency to individual brain rhythms has shown some promise in transcranial magnetic stimulation (TMS). Matching the phase of those rhythms may further enhance neuroplasticity, for instance when combining TMS with electroencephalographic (EEG) recordings. Resting-state EEG and event-related potentials may be useful to demonstrate connectivity between stimulation sites and connected areas. These techniques are available today to the psychiatrist to diagnose underlying sleep disorders, epilepsy, or lesions as contributing factors to the cause of depression. These technologies may also be useful in assessing the patient's brain network status prior to deciding on treatment options. Ongoing research using invasive recordings may allow for future identification of mood biomarkers and network structure. A core limitation is that biomarker research may currently be limited by the internal heterogeneity of psychiatric disorders according to the current DSM-based classifications. New approaches are being developed and may soon be validated. Finally, care must be taken when incorporating closed loop capabilities into neuromodulation systems, by ensuring the safe operation of the system and understanding the physiological dynamics. Neurophysiological tools are rapidly evolving and will likely define the next generation of neuromodulation therapies. LA - English DB - MTMT ER - TY - JOUR AU - Crocker, Britni AU - Ostrowski, Lauren AU - Williams, Ziv M. AU - Dougherty, Darin D. AU - Eskandar, Emad N. AU - Widge, Alik S. AU - Chu, Catherine J. AU - Cash, Sydney S. AU - Paulk, Angelique C. TI - Local and distant responses to single pulse electrical stimulation reflect different forms of connectivity JF - NEUROIMAGE J2 - NEUROIMAGE VL - 237 PY - 2021 PG - 11 SN - 1053-8119 DO - 10.1016/j.neuroimage.2021.118094 UR - https://m2.mtmt.hu/api/publication/32277679 ID - 32277679 N1 - Funding Agency and Grant Number: NINDS [K24-NS08856801A1]; Tiny Blue Dot Foundation; United States Department of Energy Computational Sciences Graduate Fellowship [DE-FG0297ER25308]; U.S. Army Research Office and Defense Advanced Research Projects Agency (DARPA) [W911NF-14-2-0045] Funding text: We would like to especially thank the patients who participated for their time and help. We thank Erica Johnson, Gavin Belok, Kara Farnes, Jessica Chang, Daniel Soper, and Mia Borzello for technical assistance, particularly in the MRI reconstruction and registration, and Enterprise Research Infrastructure & Services at Partners Healthcare for their indepth support and for the provision of the ERISOne Linux Computing Cluster. This work was supported by NINDS-K24 [K24-NS08856801A1]; the Tiny Blue Dot Foundation; and the United States Department of Energy Computational Sciences Graduate Fellowship [DE-FG0297ER25308] to BC. This research was sponsored by the U.S. Army Research Office and Defense Advanced Research Projects Agency (DARPA) under Cooperative Agreement Number W911NF-14-2-0045 issued by ARO contracting office in support of DARPA's SUBNETS Program. The views, opinions, and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. AB - Measuring connectivity in the human brain involves innumerable approaches using both noninvasive (fMRI, EEG) and invasive (intracranial EEG or iEEG) recording modalities, including the use of external probing stimuli, such as direct electrical stimulation. To examine how different measures of connectivity correlate with one another, we compared 'passive' measures of connectivity during resting state conditions to the more 'active' probing measures of connectivity with single pulse electrical stimulation (SPES). We measured the network engagement and spread of the cortico-cortico evoked potential (CCEP) induced by SPES at 53 out of 104 total sites across the brain, including cortical and subcortical regions, in patients with intractable epilepsy (N = 11) who were undergoing intracranial recordings as a part of their clinical care for identifying seizure onset zones. We compared the CCEP network to functional, effective, and structural measures of connectivity during a resting state in each patient. Functional and effective connectivity measures included correlation or Granger causality measures applied to stereoEEG (sEEGs) recordings. Structural connectivity was derived from diffusion tensor imaging (DTI) acquired before intracranial electrode implant and monitoring (N = 8). The CCEP network was most similar to the resting state voltage correlation network in channels near to the stimulation location. In contrast, the distant CCEP network was most similar to the DTI network. Other connectivity measures were not as similar to the CCEP network. These results demonstrate that different connectivity measures, including those derived from active stimulation-based probing, measure different, complementary aspects of regional interrelationships in the brain. LA - English DB - MTMT ER - TY - JOUR AU - Filipiak, Patryk AU - Almairac, Fabien AU - Papadopoulo, Theodore AU - Fontaine, Denys AU - Mondot, Lydiane AU - Chanalet, Stephane AU - Deriche, Rachid AU - Clerc, Maureen AU - Wassermann, Demian TI - Towards linking diffusion MRI based macro- and microstructure measures with cortico-cortical transmission in brain tumor patients JF - NEUROIMAGE J2 - NEUROIMAGE VL - 226 PY - 2021 PG - 14 SN - 1053-8119 DO - 10.1016/j.neuroimage.2020.117567 UR - https://m2.mtmt.hu/api/publication/32277694 ID - 32277694 N1 - Funding Agency and Grant Number: ANR/NSF [ANR-16-NEUC-0002] Funding text: This work has received funding from the ANR/NSF award NeuroRef ANR-16-NEUC-0002 AB - We aimed to link macro- and microstructure measures of brain white matter obtained from diffusion MRI with effective connectivity measures based on a propagation of cortico-cortical evoked potentials induced with intrasurgical direct electrical stimulation. For this, we compared streamline lengths and log-transformed ratios of streamlines computed from presurgical diffusion-weighted images, and the delays and amplitudes of N1 peaks recorded intrasurgically with electrocorticography electrodes in a pilot study of 9 brain tumor patients. Our results showed positive correlation between these two modalities in the vicinity of the stimulation sites (Pearson coefficient 0.54 +/- 0.13 for N1 delays, and 0.47 +/- 0.23 for N1 amplitudes), which could correspond to the neural propagation via U-fibers. In addition, we reached high sensitivities (0.78 +/- 0.07) and very high specificities (0.93 +/- 0.03) in a binary variant of our comparison. Finally, we used the structural connectivity measures to predict the effective connectivity using a multiple linear regression model, and showed a significant role of brain microstructure-related indices in this relation. LA - English DB - MTMT ER - TY - JOUR AU - Gronlier, Eloise AU - Vendramini, Estelle AU - Volle, Julien AU - Wozniak-Kwasniewska, Agata AU - Santos, Noelia Anton AU - Coizet, Veronique AU - Duveau, Venceslas AU - David, Olivier TI - Single-pulse electrical stimulation methodology in freely moving rat JF - JOURNAL OF NEUROSCIENCE METHODS J2 - J NEUROSCI METH VL - 353 PY - 2021 PG - 9 SN - 0165-0270 DO - 10.1016/j.jneumeth.2021.109092 UR - https://m2.mtmt.hu/api/publication/32277683 ID - 32277683 N1 - Funding Agency and Grant Number: European Research Council [790093]; Region Auvergne-Rhone-Alpes; "Association Nationale Recherche Technologie" (ANRT, CIFRE, France) [2017/1269] Funding text: Authors gratefully acknowledge the support of European Research Council (ERC-2017-PoC, Grant ID 790093, "EXCITATOR: Active probing of brain excitability by electrical micro-stimulations for drug discovery"). This work was funded by Region Auvergne-Rhone-Alpes under the grant agreement 2017 FRI Transfert EXCILAB. The study was also supported by "Association Nationale Recherche Technologie" (ANRT, CIFRE no 2017/1269, France). AB - Background: Cortico-cortical evoked potentials (CCEP) are becoming popular to infer brain connectivity and cortical excitability in implanted refractory epilepsy patients. Our goal was to transfer this methodology to the freely moving rodent.New method: CCEP were recorded on freely moving Sprague-Dawley rats, from cortical and subcortical areas using depth electrodes. Electrical stimulation was applied using 1 ms biphasic current pulse, cathodic first, at a frequency of 0.5 Hz, with intensities ranging from 0.2 to 0.8 mA. Data were then processed in a similar fashion to human clinical studies, which included epoch selection, artefact correction and smart averaging.Results: For a large range of tested intensities, we recorded CCEPs with very good signal to noise ratio and reproducibility between animals, without any behavioral modification. The CCEP were composed of different components according to recorded and stimulated sites, similarly to human recordings. Comparison with existing methods: We minimally adapted a clinically-motivated methodology to a freely moving rodent model to achieve high translational relevance of future preclinical studies.Conclusions: Our results indicate that the CCEP methodology can be applied to freely moving rodents and transferred to preclinical research. This will be of interest to address various neuroscientific questions, in physiological and pathological conditions. LA - English DB - MTMT ER - TY - JOUR AU - Guo, Zhihao AU - Zhao, Baotian AU - Hu, Wenhan AU - Zhang, Chao AU - Wang, Xiu AU - Wang, Yao AU - Liu, Chang AU - Mo, Jiajie AU - Sang, Lin AU - Ma, Yanshan AU - Shao, Xiaoqiu AU - Zhang, Jianguo AU - Zhang, Kai TI - Effective connectivity among the hippocampus, amygdala, and temporal neocortex in epilepsy patients: A cortico-cortical evoked potential study JF - EPILEPSY & BEHAVIOR J2 - EPILEPSY BEHAV VL - 115 PY - 2021 PG - 7 SN - 1525-5050 DO - 10.1016/j.yebeh.2020.107661 UR - https://m2.mtmt.hu/api/publication/32277272 ID - 32277272 N1 - Funding Agency and Grant Number: National Natural Science Foundation of China [81771399, 81701276]; Beijing Municipal Science & Technology Commission [Z171100001017069]; Capital's Funds for Health Improvement and Research [2020-41076] Funding text: This study was supported by the National Natural Science Foundation of China (No. 81771399, 81701276), the Beijing Municipal Science & Technology Commission (Z171100001017069) and the Capital's Funds for Health Improvement and Research (2020-41076). AB - Objective: Mesial temporal lobe epilepsy (MTLE) is one of the most common types of intractable epilepsy. The hippocampus and amygdala are two crucial structures of the mesial temporal lobe and play important roles in the epileptogenic network of MTLE. This study aimed to explore the effective connectivity among the hippocampus, amygdala, and temporal neocortex and to determine whether differences in effective connectivity exist between MTLE patients and non-MTLE patients.Methods: This study recruited 20 patients from a large cohort of drug-resistant epilepsy patients, of whom 14 were MTLE patients. Single-pulse electrical stimulation (SPES) was performed to acquire cortico-cortical evoked potentials (CCEPs). The root mean square (RMS) was used as the metric of the magnitude of CCEP to represent the effective connectivity. We then conducted paired and independent sample t-tests to assess the directionality of the effective connectivity.Results: In both MTLE patients and non-MTLE patients, the directional connectivity from the amygdala to the hippocampus was stronger than that from the hippocampus to the amygdala (P < 0.01); the outward connectivity from the amygdala to the cortex was stronger than the inward connectivity from the cortex to the amygdala (P < 0.01); the amygdala had stronger connectivity to the neocortex than the hippocampus (P < 0.01). In MTLE patients, the neocortex had stronger connectivity to the hippocampus than to the amygdala (P < 0.01). No significant differences in directional connectivity were noted between the two groups.Conclusions: A unique effective connectivity pattern among the hippocampus, amygdala, and temporal neocortex was identified through CCEPs analysis. This study may aid in our understanding of physiological and pathological networks in the brain and inspire neurostimulation protocols for neurological and psychiatric disorders. (C) 2020 Elsevier Inc. All rights reserved. LA - English DB - MTMT ER - TY - JOUR AU - Hermann, Bruce P. AU - Struck, Aaron F. AU - Busch, Robyn M. AU - Reyes, Anny AU - Kaestner, Erik AU - McDonald, Carrie R. TI - Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy JF - NATURE REVIEWS NEUROLOGY J2 - NAT REV NEUROL VL - 17 PY - 2021 IS - 12 SP - 731 EP - 746 PG - 16 SN - 1759-4758 DO - 10.1038/s41582-021-00555-z UR - https://m2.mtmt.hu/api/publication/33007475 ID - 33007475 N1 - Funding Agency and Grant Number: National Institutes of Health (NIH) [KL2 TR000440, R01 NS097719, R01 NS065838, R21 NS107739, T32 MH018399, R01 NS111022, F31 NS111883-01] Funding text: The authors acknowledge funding from National Institutes of Health (NIH) KL2 TR000440 (R.M.B.), NIH R01 NS097719 (R.M.B.), NIH R01 NS065838 (C.R.M.), NIH R21 NS107739 (C.R.M.), NIH T32 MH018399 (E.K.), NIH R01 NS111022 (A.F.S. and B.P.H.) and NIH F31 NS111883-01 (A.R.). The authors thank M. L. Smith for reading of a pre-submission draft. AB - Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.This Review offers a novel theoretical perspective on the neurobehavioural comorbidities of adult and childhood epilepsy, involving new analytical approaches, derivation of new taxonomies and consideration of the diverse forces that influence cognition and behaviour in individuals with epilepsy. LA - English DB - MTMT ER - TY - JOUR AU - Kudela, Pawel AU - Anderson, William S. TI - Impact of gyral geometry on cortical responses to surface electrical stimulation: insights from experimental and modeling studies JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 18 PY - 2021 IS - 4 PG - 14 SN - 1741-2560 DO - 10.1088/1741-2552/ac1ed3 UR - https://m2.mtmt.hu/api/publication/32219280 ID - 32219280 N1 - Funding Agency and Grant Number: US Army Research Office [W911NF-20-1-0183] Funding text: This work was supported by US Army Research Office grant W911NF-20-1-0183. AB - Objective. Invasive simultaneous stimulation and recording from intracranial electrodes and microwire arrays were used to investigate direct cortical responses to single pulses of electrical stimulation in humans. Approach. Microwire contacts measured surface potentials in cortical microdomains at a distance of 2-6 mm from the intracranial electrode. Direct cortical responses to stimulation (<20 ms) consisted of a larger surface negative potentials. Main results. The latencies of these responses were directly or inversely correlated with distances between the intracranial electrode and microwire contacts. We hypothesize that surface negative potentials reflected local synchronous depolarization of apical dendrites of pyramidal neurons in cortical microdomains in the superficial cortical layer and resulted from the activation of gray matter axons that delivered excitatory inputs to apical dendrites after cortical stimulation. We further hypothesized that the positive or inverse distance-latency correlations of the recorded negative responses were measured depending on whether activation of neurons originated at one (crown) or multiple (crown, lip, bank) sites throughout the gyrus simultaneously. The inverse distance-latency correlations then reflected the spatiotemporal superposition of different nearby sources of neuronal recruitment in the gyrus. To prove this hypothesis, we built an anatomically informed and biophysically realistic cortical network model and simulated early responses of cortical neurons to electrical stimulation in this cortical network model. The model simulations yielded negative potentials in simulated microdomains in the cortical model consistent with those recorded from humans. The model predicted sensitivity of cortical responses to the alignment of the stimulating electrode and microwire array with respect to the cortical gyrus and confirmed that gyral geometry has a major impact on direct neuronal recruitment, the timing, and the time course of neuronal activation in cortical microdomains. Significance. In this work, we demonstrated how the high-resolution forward network models can be used for better understanding and detailed prediction of cortical stimulation effects. Accurate predictive modeling tools are needed for the progress of brain stimulation therapies. LA - English DB - MTMT ER - TY - JOUR AU - Mariani, Valeria AU - Balestrini, Simona AU - Gozzo, Francesca AU - Pelliccia, Veronica AU - Mai, Roberto AU - Francione, Stefano AU - Sartori, Ivana AU - Cardinale, Francesco AU - Tassi, Laura TI - Intracerebral electrical stimulations of the temporal lobe: A stereoelectroencephalography study JF - EUROPEAN JOURNAL OF NEUROSCIENCE J2 - EUR J NEUROSCI VL - 54 PY - 2021 IS - 4 SP - 5368 EP - 5383 PG - 16 SN - 0953-816X DO - 10.1111/ejn.15377 UR - https://m2.mtmt.hu/api/publication/32277693 ID - 32277693 N1 - Funding Agency and Grant Number: Epilepsy Society; Muir Maxwell Trust Funding text: We thank Ms. Ghazala Mirza for the linguistic revision. SB was supported by the Epilepsy Society and The Muir Maxwell Trust. AB - The functional anatomy of the anteromesial portion of the temporal lobe and its involvement in epilepsy can be explored by means of intracerebral electrical stimulations. Here, we aimed to expand the knowledge of its physiological and pathophysiological symptoms by conducting the first large-sample systematic analysis of 1529 electrical stimulations of this anatomical region. We retrospectively analysed all clinical manifestations induced by intracerebral electrical stimulations in 173 patients with drug-resistant focal epilepsy with at least one electrode implanted in this area. We found that high-frequency stimulations were more likely to evoke electroclinical manifestations (p < .0001) and also provoked 'false positive' seizures. Multimodal symptoms were associated with EEG electrical modification (after discharge) (p < .0001). Visual symptoms were not associated with after discharge (p = .0002) and were mainly evoked by stimulation of the hippocampus (p = .009) and of the parahippocampal gyrus (p = .0212). 'False positive seizures' can be evoked by stimulation of the hippocampus, parahippocampal gyrus and amygdala, likely due to their intrinsic low epileptogenic threshold. Visual symptoms evoked in the hippocampus and parahippocampal gyrus, without EEG changes, are physiological symptoms and suggest involvement of these areas in the visual ventral stream. Our findings provide meaningful guidance in the interpretation of intracranial EEG studies of the temporal lobe. LA - English DB - MTMT ER - TY - JOUR AU - Miller, Kai J. AU - Mueller, Klaus-Robert AU - Hermes, Dora TI - Basis profile curve identification to understand electrical stimulation effects in human brain networks JF - PLOS COMPUTATIONAL BIOLOGY J2 - PLOS COMPUT BIOL VL - 17 PY - 2021 IS - 9 PG - 20 SN - 1553-734X DO - 10.1371/journal.pcbi.1008710 UR - https://m2.mtmt.hu/api/publication/33006203 ID - 33006203 N1 - Funding Agency and Grant Number: Van Wagenen Fellowship; Brain Research Foundation with a Fay/Frank Seed Grant; Brain & Behavior Research Foundation; NARSAD Young Investigator Grant; NIH-NCATS CTSA [KL2 TR002379]; NIH-NIMH CRCNS [R01MH122258-01]; Institute of Information & Communications Technology Planning & Evaluation (IITP) - Korea Government [2017-0-00451, 2019-0-00079]; German Ministry for Education and Research (BMBF) [01IS14013A-E, 01GQ1115, 01GQ0850, 01IS18025A, 031L0207D, 01IS18037A]; German Research Foundation (DFG) [EXC 2046/1, 390685689] Funding text: KJM was supported by the Van Wagenen Fellowship, the Brain Research Foundation with a Fay/Frank Seed Grant, and the Brain & Behavior Research Foundation with a NARSAD Young Investigator Grant. This work was also supported by NIH-NCATS CTSA KL2 TR002379 (KJM). DH was supported by the NIH-NIMH CRCNS R01MH122258-01. Manuscript contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. KRM was supported in part by the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User's Intentions using Deep Learning) and (No. 2019-0-00079, Artificial Intelligence Graduate School Program, Korea University), and by the German Ministry for Education and Research (BMBF) under Grants 01IS14013A-E, 01GQ1115, 01GQ0850, 01IS18025A, 031L0207D and 01IS18037A; the German Research Foundation (DFG) under Grant Math+, EXC 2046/1, Project ID 390685689. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AB - Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique "basis profile curves " (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome. LA - English DB - MTMT ER - TY - JOUR AU - Mofakham, Sima AU - Fry, Adam AU - Adachi, Joseph AU - Stefancin, Patricia L. AU - Duong, Tim Q. AU - Saadon, Jordan R. AU - Winans, Nathan J. AU - Sharma, Himanshu AU - Feng, Guanchao AU - Djuric, Petar M. AU - Mikell, Charles B. TI - Electrocorticography reveals thalamic control of cortical dynamics following traumatic brain injury JF - COMMUNICATIONS BIOLOGY J2 - COMMUN BIOL VL - 4 PY - 2021 IS - 1 PG - 10 SN - 2399-3642 DO - 10.1038/s42003-021-02738-2 UR - https://m2.mtmt.hu/api/publication/33007473 ID - 33007473 N1 - Funding Agency and Grant Number: Neurosurgery Department, Stony Brook EEG center; National Science Foundation through the Growing Convergence Research (NSF) [2021002]; Renaissance School of Medicine at Stony Brook University [63845]; Office of the Vice President for Research at Stony Brook University; Stony Brook University Hospital Funding text: We thank Susan Fiore, Dr. Il Memming Park, Josue Nasser, Dr. Ramin Parsey, Dr. Christine DeLorenzo, Dr. Raphael Davis, Dr. Elliot H. Smith, Dr. Justine Liang, Dr. Helen Hsieh, Bradley Ashcroft, and Dr. John Anthony Servider for their helpful comments and discussions. We also thank the Neurosurgery Department, Stony Brook EEG center, and Stony Brook University Hospital for providing support. This work was supported by the National Science Foundation through the Growing Convergence Research (NSF Award 2021002), a Targeted Research Opportunity Program FUSION award (63845) from the Renaissance School of Medicine at Stony Brook University, as well as seed grant funding from the Office of the Vice President for Research at Stony Brook University. AB - To begin to uncover the mechanisms underlying the return of consciousness following traumatic brain injury, Mofakham et al. recorded local field potentials from depth cortical regions in these patients. They found that thalamic input to the cortex plays a role in mediating the cortical dynamics associated with recovery of consciousness.The return of consciousness after traumatic brain injury (TBI) is associated with restoring complex cortical dynamics; however, it is unclear what interactions govern these complex dynamics. Here, we set out to uncover the mechanism underlying the return of consciousness by measuring local field potentials (LFP) using invasive electrophysiological recordings in patients recovering from TBI. We found that injury to the thalamus, and its efferent projections, on MRI were associated with repetitive and low complexity LFP signals from a highly structured phase space, resembling a low-dimensional ring attractor. But why do thalamic injuries in TBI patients result in a cortical attractor? We built a simplified thalamocortical model, which connotes that thalamic input facilitates the formation of cortical ensembles required for the return of cognitive function and the content of consciousness. These observations collectively support the view that thalamic input to the cortex enables rich cortical dynamics associated with consciousness. LA - English DB - MTMT ER - TY - CHAP AU - Osborn, Luke E. AU - McMullen, David P. AU - Christie, Breanne P. AU - Kudela, Pawel AU - Thomas, Tessy M. AU - Thompson, Margaret C. AU - Nickl, Robert W. AU - Anaya, Manuel AU - Srihari, Sahana AU - Crone, Nathan E. AU - Wester, Brock A. AU - Celnik, Pablo A. AU - Cantarero, Gabriela L. AU - Tenore, Francesco V AU - Fifer, Matthew S. TI - Intracortical microstimulation of somatosensory cortex generates evoked responses in motor cortex T2 - 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER) PB - IEEE CY - New York, New York CY - Piscataway (NJ) SN - 9781728143378 T3 - International IEEE EMBS Conference on Neural Engineering, ISSN 1948-3546 PY - 2021 SP - 53 EP - 56 PG - 4 DO - 10.1109/NER49283.2021.9441123 UR - https://m2.mtmt.hu/api/publication/32277266 ID - 32277266 N1 - Funding Agency and Grant Number: Defense Advanced Research Projects Agency (DARPA); Johns Hopkins University Applied Physics Laboratory (JHU/APL) Postdoctoral Fellowship Funding text: This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA) and the Johns Hopkins University Applied Physics Laboratory (JHU/APL) Postdoctoral Fellowship. The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. AB - The complex nature of neural connections throughout the cerebral cortex has led to broad interest in understanding cortical functional networks of tactile perception and sensorimotor integration. Cortico-cortical evoked potentials (CCEPs) can be used as physiological markers to study and map cerebral networks in the brain. In a human participant with bi-hemispheric microelectrode array implants in sensorimotor regions of the brain, we found that intracortical microstimulation (ICMS) of the primary somatosensory cortex can lead to evoked responses in the motor cortex in the same hemisphere, indicating connectivity between these sensorimotor regions. Single ICMS pulses were not consciously perceived, but elicited a rapid evoked potential approximately 20 ms after stimulus onset. Multi-pulse ICMS trains, perceived as tactile sensations in the thumb, sustained over an approximately 33 ms period, led to a delayed evoked response roughly 80 ms after stimulus onset. This work is important not only for better understanding the functional relationship between cortical areas, specifically somatosensory and motor cortices, but also to provide insight on pathways where neuromodulation techniques could be employed for rehabilitation or mitigation of sensorimotor neurodegenerative effects. LA - English DB - MTMT ER - TY - JOUR AU - Scangos, Katherine W. AU - Khambhati, Ankit N. AU - Daly, Patrick M. AU - Makhoul, Ghassan S. AU - Sugrue, Leo P. AU - Zamanian, Hashem AU - Liu, Tony X. AU - Rao, Vikram R. AU - Sellers, Kristin K. AU - Dawes, Heather E. AU - Starr, Philip A. AU - Krystal, Andrew D. AU - Chang, Edward F. TI - Closed-loop neuromodulation in an individual with treatment-resistant depression JF - NATURE MEDICINE J2 - NAT MED VL - 27 PY - 2021 IS - 10 SP - 1696 EP - + PG - 13 SN - 1078-8956 DO - 10.1038/s41591-021-01480-w UR - https://m2.mtmt.hu/api/publication/33007474 ID - 33007474 N1 - Funding Agency and Grant Number: National Institutes of Health [K23NS110962]; NARSAD Young Investigator grant from the Brain & Behavior Research Foundation; 1907 Trailblazer Award; Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at UCSF Funding text: This work was supported by a National Institutes of Health award no. K23NS110962 (K.W.S.), NARSAD Young Investigator grant from the Brain & Behavior Research Foundation (K.W.S.), 1907 Trailblazer Award (K.W.S.) and a Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at UCSF (K.W.S., A.D.K., E.F.C., L.P.S., A.N.K., P.M.S., G.S.M., H.Z., T.X.L., V.R.R., K.K.S. and H.E.D.). AB - Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as major depression. It could be optimized by identifying neural biomarkers that trigger therapy selectively when symptom severity is elevated. We developed an approach that first used multi-day intracranial electrophysiology and focal electrical stimulation to identify a personalized symptom-specific biomarker and a treatment location where stimulation improved symptoms. We then implanted a chronic deep brain sensing and stimulation device and implemented a biomarker-driven closed-loop therapy in an individual with depression. Closed-loop therapy resulted in a rapid and sustained improvement in depression. Future work is required to determine if the results and approach of this n-of-1 study generalize to a broader population. LA - English DB - MTMT ER - TY - JOUR AU - Shahabi, Hossein AU - Taylor, Kenneth AU - Hirfanoglu, Tugba AU - Koneru, Shreekanth AU - Bingaman, William AU - Kobayashi, Katsuya AU - Kobayashi, Masako AU - Joshi, Anand AU - Leahy, Richard M. AU - Mosher, John C. AU - Bulacio, Juan AU - Nair, Dileep TI - Effective connectivity differs between focal cortical dysplasia types I and II JF - EPILEPSIA J2 - EPILEPSIA VL - 62 PY - 2021 IS - 11 SP - 2753 EP - 2765 PG - 13 SN - 0013-9580 DO - 10.1111/epi.17064 UR - https://m2.mtmt.hu/api/publication/32277692 ID - 32277692 N1 - Funding Agency and Grant Number: National Institutes of Health [R01NS089212, U01EB023820, R01EB026299] Funding text: National Institutes of Health, Grant/Award Number: R01NS089212, U01EB023820 and R01EB026299 AB - Objective To determine whether brain connectivity differs between focal cortical dysplasia (FCD) types I and II. Methods We compared cortico-cortical evoked potentials (CCEPs) as measures of effective brain connectivity in 25 FCD patients with drug-resistant focal epilepsy who underwent intracranial evaluation with stereo-electroencephalography (SEEG). We analyzed the amplitude and latency of CCEP responses following ictal-onset single-pulse electrical stimulation (iSPES). Results In comparison to FCD type II, patients with type I demonstrated significantly larger responses in the electrodes near the ictal-onset zone (<50 mm). These findings persisted when controlling for the location of the epileptogenic zone, as noted in patients with temporal lobe epilepsies, as well as controlling for seizure type, as noted in patients with focal to bilateral tonic-clonic seizures (FBTCS). In type II, the root mean square (RMS) of CCEP responses dropped substantially from the early segment (10-60 ms) to the middle and late segments (60-600 ms). The middle and late CCEP latency segments showed the largest differences between FCD types I and II. Significance Focal cortical dysplasia type I may have a greater degree of cortical hyperexcitability as compared with FCD type II. In addition, FCD type II displays a more restrictive area of hyperexcitability in both temporal and spatial domains. In patients with FBTCS and type I FCD, the increased amplitudes of RMS in the middle and late CCEP periods appear consistent with the cortico-thalamo-cortical network involvement of FBTCS. The notable differences in degree and extent of hyperexcitability may contribute to the different postsurgical seizure outcomes noted between these two pathological substrates. LA - English DB - MTMT ER - TY - JOUR AU - Sonoda, Masaki AU - Silverstein, Brian H. AU - Jeong, Jeong-Won AU - Sugiura, Ayaka AU - Nakai, Yasuo AU - Mitsuhashi, Takumi AU - Rothermel, Robert AU - Luat, Aimee F. AU - Sood, Sandeep AU - Asano, Eishi TI - Six-dimensional dynamic tractography atlas of language connectivity in the developing brain JF - BRAIN J2 - BRAIN VL - 144 PY - 2021 SP - 3340 EP - 3354 PG - 15 SN - 0006-8950 DO - 10.1093/brain/awab225 UR - https://m2.mtmt.hu/api/publication/33007470 ID - 33007470 N1 - Funding Agency and Grant Number: NIH [NS064033, NS089659] Funding text: This work was supported by NIH grants NS064033 (to E.A.) and NS089659 (to J.-W.J.). Part number: 11 AB - During a verbal conversation, our brain moves through a series of complex linguistic processing stages: sound decoding, semantic comprehension, retrieval of semantically coherent words, and overt production of speech outputs. Each process is thought to be supported by a network consisting of local and long-range connections bridging between major cortical areas. Both temporal and extratemporal lobe regions have functional compartments responsible for distinct language domains, including the perception and production of phonological and semantic components.This study provides quantitative evidence of how directly connected inter-lobar neocortical networks support distinct stages of linguistic processing across brain development. Novel six-dimensional tractography was used to intuitively visualize the strength and temporal dynamics of direct inter-lobar effective connectivity between cortical areas activated during each linguistic processing stage.We analysed 3401 non-epileptic intracranial electrode sites from 37 children with focal epilepsy (aged 5-20 years) who underwent extra-operative electrocorticography recording. Principal component analysis of auditory naming-related high-gamma modulations determined the relative involvement of each cortical area during each linguistic processing stage. To quantify direct effective connectivity, we delivered single-pulse electrical stimulation to 488 temporal and 1581 extratemporal lobe sites and measured the early cortico-cortical spectral responses at distant electrodes. Mixed model analyses determined the effects of naming-related high-gamma co-augmentation between connecting regions, age, and cerebral hemisphere on the strength of effective connectivity independent of epilepsy-related factors.Direct effective connectivity was strongest between extratemporal and temporal lobe site pairs, which were simultaneously activated between sentence offset and verbal response onset (i.e. response preparation period); this connectivity was approximately twice more robust than that with temporal lobe sites activated during stimulus listening or overt response. Conversely, extratemporal lobe sites activated during overt response were equally connected with temporal lobe language sites. Older age was associated with increased strength of inter-lobar effective connectivity especially between those activated during response preparation. The arcuate fasciculus supported approximately two-thirds of the direct effective connectivity pathways from temporal to extratemporal auditory language-related areas but only up to half of those in the opposite direction. The uncinate fasciculus consisted of <2% of those in the temporal-to-extratemporal direction and up to 6% of those in the opposite direction. We, for the first time, provided an atlas which quantifies and animates the strength, dynamics, and direction specificity of inter-lobar neural communications between language areas via the white matter pathways. Language-related effective connectivity may be strengthened in an age-dependent manner even after the age of 5. LA - English DB - MTMT ER - TY - JOUR AU - Veit, Mike J. AU - Kucyi, Aaron AU - Hu, Wenhan AU - Zhang, Chao AU - Zhao, Baotian AU - Guo, Zhihao AU - Yang, Bowen AU - Sava-Segal, Clara AU - Perry, Claire AU - Zhang, Jianguo AU - Zhang, Kai AU - Parvizi, Josef TI - Temporal order of signal propagation within and across intrinsic brain networks JF - PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA J2 - P NATL ACAD SCI USA VL - 118 PY - 2021 IS - 48 PG - 5 SN - 0027-8424 DO - 10.1073/pnas.2105031118 UR - https://m2.mtmt.hu/api/publication/32961416 ID - 32961416 N1 - Funding Agency and Grant Number: NIH [1R21NS113024]; National Natural Science Foundation of China [81771399, 81701276]; China Scholarship Council [201908110041]; Canadian Institutes of Health Research Funding text: We thank members of the Tiantan team for assistance with data collection. This work was supported by NIH research grant 1R21NS113024 (to J.P.); National Natural Science Foundation of China (Grants 81771399 and 81701276 to K.Z.); China Scholarship Council (Grant 201908110041 to C.Z.); and Banting Fellowship from the Canadian Institutes of Health Research (to A.K.). AB - We studied the temporal dynamics of activity within and across functional MRI (fMRI)-derived nodes of intrinsic resting-state networks of the human brain using intracranial electroencephalography (iEEG) and repeated single-pulse electrical stimulation (SPES) in neurosurgical subjects implanted with intracranial electrodes. We stimulated and recorded from 2,133 and 2,372 sites, respectively, in 29 subjects. We found that N1 and N2 segments of the evoked responses are associated with intra- and internetwork communications, respectively. In a separate cognitive experiment, evoked electrophysiological responses to visual target stimuli occurred with less temporal separation across pairs of electrodes that were located within the same fMRI-defined resting-state networks compared with those located across different resting-state networks. Our results suggest intranetwork prior to internetwork information processing at the subsecond timescale. LA - English DB - MTMT ER - TY - JOUR AU - Yang, Yuxiao AU - Qiao, Shaoyu AU - Sani, Omid G. AU - Sedillo, J. Isaac AU - Ferrentino, Breonna AU - Pesaran, Bijan AU - Shanechi, Maryam M. TI - Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation JF - NATURE BIOMEDICAL ENGINEERING J2 - NAT BIOMED ENG VL - 5 PY - 2021 IS - 4 PG - 25 SN - 2157-846X DO - 10.1038/s41551-020-00666-w UR - https://m2.mtmt.hu/api/publication/32277695 ID - 32277695 N1 - Funding Agency and Grant Number: Army Research Office [W911NF-16-1-0368]; UK Ministry of Defence; UK Engineering and Physical Research Council under the Multidisciplinary University Research Initiative; US National Institutes of Health BRAIN [R01-NS104923]; Defense Advanced Research Projects Agency [W911NF-14-2-0043]; Army Research Office contracting office in support of the DARPA SUBNETS programme Funding text: We acknowledge support of the Army Research Office under contract W911NF-16-1-0368 (to M.M.S.) as part of the collaboration between the US Department of Defense, the UK Ministry of Defence and the UK Engineering and Physical Research Council under the Multidisciplinary University Research Initiative. We also acknowledge support of US National Institutes of Health BRAIN grant R01-NS104923 (to B.P. and M.M.S.). Finally, the we acknowledge the Defense Advanced Research Projects Agency under Cooperative Agreement Number W911NF-14-2-0043 (to M.M.S. and B.P.), issued by the Army Research Office contracting office in support of the DARPA SUBNETS programme. The views, opinions and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the US Government. We thank B. Goodell, C. Gray, J. E. Kleinbart and A. Orsborn for assistance with chamber and microdrive system design; S. Frey and B. Hynes for custom modifications to the Brainsight system; R. Shewcraft, J. Choi, M. Rubiano, Y. Jang and O. Martin for help with animal preparation and care; and K. Brown for help with MRI analysis. AB - Direct electrical stimulation can modulate the activity of brain networks for the treatment of several neurological and neuropsychiatric disorders and for restoring lost function. However, precise neuromodulation in an individual requires the accurate modelling and prediction of the effects of stimulation on the activity of their large-scale brain networks. Here, we report the development of dynamic input-output models that predict multiregional dynamics of brain networks in response to temporally varying patterns of ongoing microstimulation. In experiments with two awake rhesus macaques, we show that the activities of brain networks are modulated by changes in both stimulation amplitude and frequency, that they exhibit damping and oscillatory response dynamics, and that variabilities in prediction accuracy and in estimated response strength across brain regions can be explained by an at-rest functional connectivity measure computed without stimulation. Input-output models of brain dynamics may enable precise neuromodulation for the treatment of disease and facilitate the investigation of the functional organization of large-scale brain networks. LA - English DB - MTMT ER - TY - JOUR AU - Deslauriers-Gauthier, Samuel AU - Costantini, Isa AU - Deriche, Rachid TI - Non-invasive inference of information flow using diffusion MRI, functional MRI, and MEG JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 17 PY - 2020 IS - 4 PG - 10 SN - 1741-2560 DO - 10.1088/1741-2552/ab95ec UR - https://m2.mtmt.hu/api/publication/31425921 ID - 31425921 N1 - Funding Agency and Grant Number: European Research Council (ERC)under the European Union's Horizon 2020 research and innovation program(ERC Advanced Grant) [694665]; 16 NIH Institutes and Centers [1U54MH091657]; McDonnell Center for Systems Neuroscience at Washington University Funding text: This work has received funding from the European Research Council (ERC)under the European Union's Horizon 2020 research and innovation program(ERC Advanced Grant agreement No. 694665 : CoBCoM-Computational Brain Connectivity Mapping). Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. AB - Objective. To infer information flow in the white matter of the brain and recover cortical activity using functional MRI, diffusion MRI, and MEG without a manual selection of the white matter connections of interest.Approach. A Bayesian network which encodes the priors knowledge of possible brain states is built from imaging data. Diffusion MRI is used to enumerate all possible connections between cortical regions. Functional MRI is used to prune connections without manual intervention and increase the likelihood of specific regions being active. MEG data is used as evidence into this network to obtain a posterior distribution on cortical regions and connections.Main results. We show that our proposed method is able to identify connections associated with the a sensory-motor task. This allows us to build the Bayesian network with no manual selection of connections of interest. Using sensory-motor MEG evoked response as evidence into this network, our method identified areas known to be involved in a visuomotor task. In addition, information flow along white matter fiber bundles connecting those regions was also recovered.Significance. Current methods to estimate white matter information flow are extremely invasive, therefore limiting our understanding of the interaction between cortical regions. The proposed method makes use of functional MRI, diffusion MRI, and M/EEG to infer communication between cortical regions, therefore opening the door to the non-invasive exploration of information flow in the white matter. LA - English DB - MTMT ER - TY - JOUR AU - File, Bálint AU - Nánási, Tibor AU - Tóth, E. AU - Bokodi, Virág AU - Tóth, Brigitta AU - Hajnal, Boglárka Zsófia AU - Balogh-Kardos, Zsófia Klára AU - Entz, László AU - Erőss, Loránd AU - Ulbert, István AU - Fabó, Dániel TI - Reorganization of Large-Scale Functional Networks during Low-Frequency Electrical Stimulation of the Cortical Surface JF - INTERNATIONAL JOURNAL OF NEURAL SYSTEMS J2 - INT J NEURAL SYST VL - 30 PY - 2020 IS - 3 PG - 15 SN - 0129-0657 DO - 10.1142/S0129065719500229 UR - https://m2.mtmt.hu/api/publication/30868010 ID - 30868010 N1 - Funding Agency and Grant Number: Hungarian Brain Research Program Grants [2017-1.2.1-NKP-2017-00002]; European Social Fund [EFOP-3.6.3-VEKOP-16-2017-00002] Funding text: BF is supported by the Hungarian Brain Research Program Grants (Grant Nos. 2017-1.2.1-NKP-2017-00002) and the European Social Fund (EFOP-3.6.3-VEKOP-16-2017-00002). The authors are willing to share their data upon personal request. First and second authors contributed equally. LA - English DB - MTMT ER - TY - JOUR AU - Guo, Zhi-hao AU - Zhao, Bao-tian AU - Toprani, Sheela AU - Hu, Wen-han AU - Zhang, Chao AU - Wang, Xiu AU - Sang, Lin AU - Ma, Yan-shan AU - Shao, Xiao-qiu AU - Razavi, Babak AU - Parvizi, Josef AU - Fisher, Robert AU - Zhang, Jian-guo AU - Zhang, Kai TI - Epileptogenic network of focal epilepsies mapped with cortico-cortical evoked potentials JF - CLINICAL NEUROPHYSIOLOGY J2 - CLIN NEUROPHYSIOL VL - 131 PY - 2020 IS - 11 SP - 2657 EP - 2666 PG - 10 SN - 1388-2457 DO - 10.1016/j.clinph.2020.08.012 UR - https://m2.mtmt.hu/api/publication/31689181 ID - 31689181 N1 - Funding Agency and Grant Number: National Natural Science Foundation of China [81771399, 81701276]; Beijing Municipal Science & Technology Commission [Z171100001017069]; Capital's Funds for Health Improvement and Research [2020-4-1076] Funding text: This study was supported by the National Natural Science Foundation of China (No. 81771399, 81701276), the Beijing Municipal Science & Technology Commission (Z171100001017069) and the Capital's Funds for Health Improvement and Research (2020-4-1076). AB - Objective: The goal of this study was to investigate the spatial extent and functional organization of the epileptogenic network through cortico-cortical evoked potentials (CCEPs) in patients being evaluated with intracranial stereoelectroencephalography.Methods: Weretrospectively included 25 patients. Wedivided the recorded sites into three regions: epileptogenic zone (EZ); propagation zone (PZ); and noninvolved zone (NIZ). The root mean square of the amplitudes was calculated to reconstruct effective connectivity network. Wealso analyzed the N1/N2 amplitudes to explore the responsiveness influenced by epileptogenicity. Prognostic analysis was performed by comparing intra-region and inter-region connectivity between seizure-free and non-seizure-free groups.Results: Our results confirmed that stimulation of the EZ caused the strongest responses on other sites within and outside the EZ. Moreover, wefound a hierarchical connectivity pattern showing the highest connectivity strength within EZ, and decreasing connectivity gradient from EZ, PZ to NIZ. Prognostic analysis indicated a stronger intra-EZ connection in the seizure-free group.Conclusion: The EZ showed highest excitability and dominantly influenced other regions. Quantitative CCEPs can be useful in mapping epileptic networks and predicting surgical outcome.Significance: The generated computational connectivity model may enhance our understanding of epileptogenic networks and provide useful information for surgical planning and prognosis prediction. (C) 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved. LA - English DB - MTMT ER - TY - JOUR AU - Hebbink, Jurgen AU - van Gils, Stephan A. AU - Meijer, Hil G. E. TI - On analysis of inputs triggering large nonlinear neural responses Slow-fast dynamics in the Wendling neural mass model JF - COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION J2 - COMMUN NONLIN SCI NUMER SIMULAT VL - 83 PY - 2020 PG - 10 SN - 1007-5704 DO - 10.1016/j.cnsns.2019.105103 UR - https://m2.mtmt.hu/api/publication/31425920 ID - 31425920 N1 - Funding Agency and Grant Number: ZonMW/Dutch Epilepsy Foundation Translational Research [95104015] Funding text: J.H. is supported by ZonMW/Dutch Epilepsy Foundation Translational Research grant 95104015. AB - Many applications in neuroscience, such as electrical and magnetic stimulation, can be modelled as short transient input to non-linear dynamical systems. In excitable systems, small input yields more or less linear responses, while for increasing stimulation strength large non-linear responses may show up suddenly. A challenging task is to determine the transition between the two different response types.In this work we consider such a transition between normal and pathological responses in a model of coupled Wendling neural masses as we encountered in a previous study. First, the different timescales of inhibition in this model allow a slow-fast analysis. This reveals two different dynamical regimes for the systems' response. Second, the two response types are separated by a high-dimensional stable manifold of a saddle slow manifold. Large pathological responses appear if the fast subsystem escapes from this manifold to another attractor. The typical fast oscillations seen during the pathological responses are explained by the bifurcation diagram of the fast subsystem. Under normal conditions these oscillations are suppressed by slow inhibition. External stimulation temporarily releases the fast subsystem from this slow inhibition. The critical response can be formulated as a boundary value problem with one free parameter and can be used to study the dependency of the transition between the two response types upon the system parameters. (C) 2019 Elsevier B.V. All rights reserved. LA - English DB - MTMT ER - TY - JOUR AU - Hebbink, Jurgen AU - Huiskamp, Geertjan AU - van Gils, Stephan A. AU - Leijten, Frans S. S. AU - Meijer, Hil G. E. TI - Pathological responses to single-pulse electrical stimuli in epilepsy: The role of feedforward inhibition JF - EUROPEAN JOURNAL OF NEUROSCIENCE J2 - EUR J NEUROSCI VL - 51 PY - 2020 IS - 4 SP - 1122 EP - 1136 PG - 15 SN - 0953-816X DO - 10.1111/ejn.14562 UR - https://m2.mtmt.hu/api/publication/31023490 ID - 31023490 N1 - Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands Department of Applied Mathematics and Technical Medical Centre, University of Twente, Enschede, Netherlands Cited By :1 Export Date: 18 August 2020 CODEN: EJONE Correspondence Address: Hebbink, J.; Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Centre UtrechtNetherlands; email: g.j.hebbink@utwente.nl AB - Delineation of epileptogenic cortex in focal epilepsy patients may profit from single-pulse electrical stimulation during intracranial EEG recordings. Single-pulse electrical stimulation evokes early and delayed responses. Early responses represent connectivity. Delayed responses are a biomarker for epileptogenic cortex, but up till now, the precise mechanism generating delayed responses remains elusive. We used a data-driven modelling approach to study early and delayed responses. We hypothesized that delayed responses represent indirect responses triggered by early response activity and investigated this for 11 patients. Using two coupled neural masses, we modelled early and delayed responses by combining simulations and bifurcation analysis. An important feature of the model is the inclusion of feedforward inhibitory connections. The waveform of early responses can be explained by feedforward inhibition. Delayed responses can be viewed as second-order responses in the early response network which appear when input to a neural mass falls below a threshold forcing it temporarily to a spiking state. The combination of the threshold with noisy background input explains the typical stochastic appearance of delayed responses. The intrinsic excitability of a neural mass and the strength of its input influence the probability at which delayed responses to occur. Our work gives a theoretical basis for the use of delayed responses as a biomarker for the epileptogenic zone, confirming earlier clinical observations. The combination of early responses revealing effective connectivity, and delayed responses showing intrinsic excitability, makes single-pulse electrical stimulation an interesting tool to obtain data for computational models of epilepsy surgery. LA - English DB - MTMT ER - TY - JOUR AU - Kamali, Golnoosh AU - Smith, Rachel June AU - Hays, Mark AU - Coogan, Christopher AU - Crone, Nathan E. AU - Kang, Joon Y. AU - Sarma, Sridevi V. TI - Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials JF - FRONTIERS IN NEUROLOGY J2 - FRONT NEUR VL - 11 PY - 2020 PG - 15 SN - 1664-2295 DO - 10.3389/fneur.2020.579961 UR - https://m2.mtmt.hu/api/publication/33255128 ID - 33255128 N1 - Funding Agency and Grant Number: NIH NCCIH [RO1AT009401]; NIH IRACDA Program via the ASPIRE program at Johns Hopkins University; NIH NINDS R21 [R21NS103113] Funding text: This work was supported by the NIH NCCIH Grant RO1AT009401, the NIH IRACDA Program via the ASPIRE program at Johns Hopkins University, and the NIH NINDS R21 (R21NS103113). AB - Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent "peak gain" of the system as measured by the H infinity norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest "floor gain" (gain at which the dipped H infinity 3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes. LA - English DB - MTMT ER - TY - JOUR AU - Kundu, Bornali AU - Davis, Tyler S. AU - Philip, Brian AU - Smith, Elliot H. AU - Arain, Amir AU - Peters, Angela AU - Newman, Blake AU - Butson, Christopher R. AU - Rolston, John D. TI - A systematic exploration of parameters affecting evoked intracranial potentials in patients with epilepsy JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 13 PY - 2020 IS - 5 SP - 1232 EP - 1244 PG - 13 SN - 1935-861X DO - 10.1016/j.brs.2020.06.002 UR - https://m2.mtmt.hu/api/publication/31686218 ID - 31686218 N1 - Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, United States Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, United States Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States Cited By :6 Export Date: 21 October 2022 Correspondence Address: Rolston, J.D.; Department of Neurosurgery, 175 N. Medical Drive East, United States; email: neuropub@hsc.utah.edu Tradenames: SPM12 Manufacturers: Ad-Tech Medical, United States AB - Background: Brain activity is constrained by and evolves over a network of structural and functional connections. Corticocortical evoked potentials (CCEPs) have been used to measure this connectivity and to discern brain areas involved in both brain function and disease. However, how varying stimulation parameters influences the measured CCEP across brain areas has not been well characterized. Objective: To better understand the factors that influence the amplitude of the CCEPs as well as evoked gamma-band power (70-150 Hz) resulting from single-pulse stimulation via cortical surface and depth electrodes. Methods: CCEPs from 4370 stimulation-response channel pairs were recorded across a range of stimulation parameters and brain regions in 11 patients undergoing long-term monitoring for epilepsy. A generalized mixed-effects model was used to model cortical response amplitudes from 5 to 100 ms post-stimulation. Results: Stimulation levels <5.5 mA generated variable CCEPs with low amplitude and reduced spatial spread. Stimulation at >= 5.5 mA yielded a reliable and maximal CCEP across stimulation-response pairs over all regions. These findings were similar when examining the evoked gamma-band power. The amplitude of both measures was inversely correlated with distance. CCEPs and evoked gamma power were largest when measured in the hippocampus compared with other areas. Larger CCEP size and evoked gamma power were measured within the seizure onset zone compared with outside this zone.Conclusion: These results will help guide future stimulation protocols directed at quantifying network connectivity across cognitive and disease states. (C) 2020 The Authors. Published by Elsevier Inc. LA - English DB - MTMT ER - TY - JOUR AU - Liang, Zhenhu AU - Cheng, Lei AU - Shao, Shuai AU - Jin, Xing AU - Yu, Tao AU - Sleigh, Jamie W. AU - Li, Xiaoli TI - Information Integration and Mesoscopic Cortical Connectivity during Propofol Anesthesia JF - ANESTHESIOLOGY J2 - ANESTHESIOLOGY VL - 132 PY - 2020 IS - 3 SP - 504 EP - 524 PG - 21 SN - 0003-3022 DO - 10.1097/ALN.0000000000003015 UR - https://m2.mtmt.hu/api/publication/33255170 ID - 33255170 N1 - Funding Agency and Grant Number: National Natural Science Foundation of China [81230023, 61673333] Funding text: This study was supported by National Natural Science Foundation of China grant No. 81230023 (Beijing, China; to Dr. Li) and grant No. 61673333 (to Dr. Liang). AB - Background: The neurophysiologic mechanisms of propofol-induced loss of consciousness have been studied in detail at the macro (scalp electroencephalogram) and micro (spiking or local field potential) scales. However, the changes in information integration and cortical connectivity during propofol anesthesia at the mesoscopic level (the cortical scale) are less clear. Methods: The authors analyzed electrocorticogram data recorded from surgical patients during propofol-induced unconsciousness (n = 9). A new information measure, genuine permutation cross mutual information, was used to analyze how electrocorticogram cross-electrode coupling changed with electrode-distances in different brain areas (within the frontal, parietal, and temporal regions, as well as between the temporal and parietal regions). The changes in cortical networks during anesthesia-at nodal and global levels-were investigated using clustering coefficient, path length, and nodal efficiency measures. Results: In all cortical regions, and in both wakeful and unconscious states (early and late), the genuine permutation cross mutual information and the percentage of genuine connections decreased with increasing distance, especially up to about 3 cm. The nodal cortical network metrics (the nodal clustering coefficients and nodal efficiency) decreased from wakefulness to unconscious state in the cortical regions we analyzed. In contrast, the global cortical network metrics slightly increased in the early unconscious state (the time span from loss of consciousness to 200 s after loss of consciousness), as compared with wakefulness (normalized average clustering coefficient: 1.05 +/- 0.01 vs. 1.06 +/- 0.03, P = 0.037; normalized average path length: 1.02 +/- 0.01 vs. 1.04 +/- 0.01, P = 0.021). Conclusions: The genuine permutation cross mutual information reflected propofol-induced coupling changes measured at a cortical scale. Loss of consciousness was associated with a redistribution of the pattern of information integration; losing efficient global information transmission capacity but increasing local functional segregation in the cortical network. LA - English DB - MTMT ER - TY - JOUR AU - Mazurek, Kevin A. AU - Richardson, David AU - Abraham, Nicholas AU - Foxe, John J. AU - Freedman, Edward G. TI - Utilizing High-Density Electroencephalography and Motion Capture Technology to Characterize Sensorimotor Integration While Performing Complex Actions JF - IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING J2 - IEEE T NEUR SYS REH VL - 28 PY - 2020 IS - 1 SP - 287 EP - 296 PG - 10 SN - 1534-4320 DO - 10.1109/TNSRE.2019.2941574 UR - https://m2.mtmt.hu/api/publication/31425916 ID - 31425916 N1 - Funding Agency and Grant Number: Roberta K. Courtman Revocable Trust; University of Rochester Clinical and Translational Science Institute (CTSI) Career Development Program (KL2), NIH [5KL2TR001999] Funding text: This work was supported in part by a Grant from the Roberta K. Courtman Revocable Trust (EGF). The work of K. A. Mazurek was supported by the University of Rochester Clinical and Translational Science Institute (CTSI) Career Development Program (KL2), NIH, under Grant 5KL2TR001999. AB - Studies of sensorimotor integration often use sensory stimuli that require a simple motor response, such as a reach or a grasp. Recent advances in neural recording techniques, motion capture technologies, and time-synchronization methods enable studying sensorimotor integration using more complex sensory stimuli and performed actions. Here, we demonstrate that prehensile actions that require using complex sensory instructions for manipulating different objects can be characterized using high-density electroencephalography and motion capture systems. In 20 participants, we presented stimuli in different sensory modalities (visual, auditory) containing different contextual information about the object with which to interact. Neural signals recorded near motor cortex and posterior parietal cortex discharged based on both the instruction delivered and object manipulated. Additionally, kinematics of the wrist movements could be discriminated between participants. These findings demonstrate a proof-of-concept behavioral paradigm for studying sensorimotor integration of multidimensional sensory stimuli to perform complex movements. The designed framework will prove vital for studying neural control of movements in clinical populations in which sensorimotor integration is impaired due to information no longer being communicated correctly between brain regions (e.g. stroke). Such a framework is the first step towards developing a neural rehabilitative system for restoring function more effectively. LA - English DB - MTMT ER - TY - JOUR AU - Nakae, Takuro AU - Matsumoto, Riki AU - Kunieda, Takeharu AU - Arakawa, Yoshiki AU - Kobayashi, Katsuya AU - Shimotake, Akihiro AU - Yamao, Yukihiro AU - Kikuchi, Takayuki AU - Aso, Toshihiko AU - Matsuhashi, Masao AU - Yoshida, Kazumichi AU - Ikeda, Akio AU - Takahashi, Ryosuke AU - Ralph, Matthew A. Lambon AU - Miyamoto, Susumu TI - Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study JF - CEREBRAL CORTEX J2 - CEREB CORTEX VL - 30 PY - 2020 IS - 8 SP - 4633 EP - 4650 PG - 18 SN - 1047-3211 DO - 10.1093/cercor/bhaa065 UR - https://m2.mtmt.hu/api/publication/31685308 ID - 31685308 N1 - Funding Agency and Grant Number: Ministry of Education, Culture, Sports, Science, and Technology [15H05874, 17H05907]; Japan Society for the Promotion of Science [17K10892, 18H02709, 18K19514, 19K17033, 19K18424]; Medical Research Council, UK [MR/R023883/1]; MRC [MR/R023883/1] Funding Source: UKRI Funding text: Ministry of Education, Culture, Sports, Science, and Technology (grant numbers 15H05874, 17H05907); Japan Society for the Promotion of Science (grant numbers 17K10892, 18H02709, 18K19514, 19K17033, 19K18424); Medical Research Council, UK (MR/R023883/1 to M.A.L.R.). AB - In the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity between the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively in 14 patients who had undergone surgical resection for a brain tumor or epileptic focus. Four-dimensional visualization of the combined CCEP data showed that the pars opercularis (Broca's area) is connected to the posterior temporal cortices and the supramarginal gyrus, whereas the pars orbitalis is connected to the anterior lateral temporal cortices and angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior-posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bidirectionally connected to the temporal or parietal area. This study shows that each IFG subdivision has different connectivity to the temporal lobe with an anterior-posterior gradient and supports the classical connectivity concept of Dejerine; that is, the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double fan-shaped structure anchored at the limen insulae. LA - English DB - MTMT ER - TY - JOUR AU - Novitskaya, Y. AU - Dümpelmann, M. AU - Vlachos, A. AU - Reinacher, P.C. AU - Schulze-Bonhage, A. TI - In vivo-assessment of the human temporal network: Evidence for asymmetrical effective connectivity JF - NEUROIMAGE J2 - NEUROIMAGE VL - 214 PY - 2020 SN - 1053-8119 DO - 10.1016/j.neuroimage.2020.116769 UR - https://m2.mtmt.hu/api/publication/31295717 ID - 31295717 N1 - Epilepsy Center, Department of Neurosurgery, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, Freiburg, 79106, Germany Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Albert Strasse 17, Freiburg, 79104, Germany Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, Freiburg, 79106, Germany Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, Freiburg, 79106, Germany Export Date: 30 April 2020 CODEN: NEIME Correspondence Address: Novitskaya, Y.; Epilepsy Center, Department of Neurosurgery, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, Germany; email: yuliya.novitskaya@gmail.com Funding details: Albert-Ludwigs-Universität Freiburg Funding text 1: This research was supported by the Human Brain Project (Grant: 650003 : Medical informatics platform for stereoelectroencephalography SEEGMIP). The article processing charge was funded by the University of Freiburg in the funding programme Open Access Publishing. LA - English DB - MTMT ER - TY - JOUR AU - Prime, David AU - Woolfe, Matthew AU - Rowlands, David AU - O'Keefe, Steven AU - Dionisio, Sasha TI - Comparing connectivity metrics in cortico-cortical evoked potentials using synthetic cortical response patterns JF - JOURNAL OF NEUROSCIENCE METHODS J2 - J NEUROSCI METH VL - 334 PY - 2020 PG - 15 SN - 0165-0270 DO - 10.1016/j.jneumeth.2019.108559 UR - https://m2.mtmt.hu/api/publication/31422817 ID - 31422817 AB - Background: Cortico-Cortical Evoked Potentials (CCEPs) are a novel low frequency stimulation method used for brain mapping during intracranial epilepsy investigations. Only a handful of metrics have been applied to CCEP data to infer connectivity, and no comparison as to which is best has been performed.New method: We implement a novel method which involved superimposing synthetic cortical responses onto stereoelectroencephalographic (SEEG) data, and use this to compare several metric's ability to detect the simulated patterns. In this we compare two commonly employed metrics currently used in CCEP analysis against eight time series similarity metrics (TSSMs), which have been widely used in machine learning and pattern matching applications.Results: Root Mean Square (RMS), a metric commonly employed in CCEP analysis, was sensitive to a wide variety of response patterns, but insensitive to simulated epileptiform patterns. Autoregressive (AR) coefficients calculated by Burg's method were also sensitive to a wide range of patterns, but were extremely sensitive to epileptiform patterns. Other metrics which employed elastic warping techniques were less sensitive to the simulated response patterns. Comparison with existing methods: Our study is the first to compare CCEP connectivity metrics against one-another. Our results found that RMS, which has been used in many CCEP studies previously, was the most sensitive metric across a wide range of patterns.Conclusions: Our novel method showed that RMS is a robust and sensitive measure, validating much of the findings of the SEEG-CCEP literature to date. Autoregressive coefficients may also be a useful metric to investigate epileptic networks. LA - English DB - MTMT ER - TY - JOUR AU - Rasheed, Waqas AU - Tang, Tong Boon TI - Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM JF - IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING J2 - IEEE T NEUR SYS REH VL - 28 PY - 2020 IS - 1 SP - 83 EP - 93 PG - 11 SN - 1534-4320 DO - 10.1109/TNSRE.2019.2948798 UR - https://m2.mtmt.hu/api/publication/31425919 ID - 31425919 N1 - Funding Agency and Grant Number: Ministry of Education Malaysia [FRGS/1/2014/TK03/UTP/02/02]; National HICoE Grant Funding text: This work was supported in part by the Ministry of Education Malaysia under Grant FRGS/1/2014/TK03/UTP/02/02 and in part by the National HICoE Grant to Centre for Intelligent Signal and Imaging Research (CISIR). AB - Detection and quantification of functional deficits due to moderate traumatic brain injury (mTBI) is crucial for clinical decision-making and timely commencement of functional therapy. In this work, we explore magnetoencephalography (MEG) based functional connectivity features i.e. magnitude squared coherence(MSC) and phase lag index (PLI) to quantify synchronized brain activity patterns as a means to detect functional deficits. We propose a multi-instance one-class support vector machine (SVM) model generated from a healthy control population. Any dispersion from the decision boundary of the model would be identified as an anomaly instance of mTBI case (Glasgow Coma Scale, GCS score between 9 and 13). The decision boundary was optimized by considering the closest anomaly (GCS = 13) from the negative class as a support vector. Validated against magnetic resonance imaging (MRI) data, the proposed model at high beta band yielded an accuracy of 94.19% and a sensitivity of 90.00%, when tested with our mTBI dataset. The results support the suggestion of multi-instance one-class SVM for the detection of mTBI. LA - English DB - MTMT ER - TY - JOUR AU - Ryu, Sang Baek AU - Paulk, Angelique C. AU - Yang, Jimmy C. AU - Ganji, Mehran AU - Dayeh, Shadi A. AU - Cash, Sydney S. AU - Fried, Shelley I AU - Lee, Seung Woo TI - Spatially confined responses of mouse visual cortex to intracortical magnetic stimulation from micro-coils JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 17 PY - 2020 IS - 5 PG - 20 SN - 1741-2560 DO - 10.1088/1741-2552/abbd22 UR - https://m2.mtmt.hu/api/publication/31689443 ID - 31689443 N1 - Funding Agency and Grant Number: NIH NEI [R01-EY029022]; BRAIN Initiative NINDS [U01-NS099700]; Dept. of Defense/CDMRP [VR170089]; NSF-CAREER [1351980]; NSF CMMI award [1728497]; NIH [DP2-EB029757] Funding text: This work was sponsored by the NIH NEI R01-EY029022 to SWL; the BRAIN Initiative NINDS U01-NS099700 and the Dept. of Defense/CDMRP (VR170089) to SIF; NSF-CAREER award #1351980, NSF CMMI award #1728497, and NIH DP2-EB029757 to SAD. The authors declare no conflict of interest. AB - Objective. Electrical stimulation via microelectrodes implanted in cortex has been suggested as a potential treatment for a wide range of neurological disorders. Despite some success however, the effectiveness of conventional electrodes remains limited, in part due to an inability to create specific patterns of neural activity around each electrode and in part due to challenges with maintaining a stable interface. The use of implantable micro-coils to magnetically stimulate the cortex has the potential to overcome these limitations because the asymmetric fields from coils can be harnessed to selectively activate some neurons, e.g. vertically-oriented pyramidal neurons while avoiding others, e.g. horizontally-oriented passing axons. In vitro experiments have shown that activation is indeed confined with micro-coils but their effectiveness in the intact brain of living animals has not been evaluated. Approach. To assess the efficacy of stimulation, a 128-channel custom recording microelectrode array was positioned on the surface of the visual cortex (ECoG) in anesthetized mice and responses to magnetic and electric stimulation were compared. Stimulation was delivered from electrodes or micro-coils implanted through a hole in the center of the recording array at a rate of 200 pulses per second for 100 ms. Main results. Both electric and magnetic stimulation reliably elicited cortical responses, although activation from electric stimulation was spatially expansive, often extending more than 1 mm from the stimulation site, while activation from magnetic stimulation was typically confined to a similar to 300 mu m diameter region around the stimulation site. Results were consistent for stimulation of both cortical layer 2/3 and layer 5 as well as across a range of stimulus strengths. Significance. The improved focality with magnetic stimulation suggests that the effectiveness of cortical stimulation can be improved. Improved focality may be particularly attractive for cortical prostheses that require high spatial resolution, e.g. devices that target sensory cortex, as it may lead to improved acuity. LA - English DB - MTMT ER - TY - JOUR AU - Silverstein, B.H. AU - Asano, E. AU - Sugiura, A. AU - Sonoda, M. AU - Lee, M.-H. AU - Jeong, J.-W. TI - Dynamic tractography: Integrating cortico-cortical evoked potentials and diffusion imaging JF - NEUROIMAGE J2 - NEUROIMAGE VL - 215 PY - 2020 SN - 1053-8119 DO - 10.1016/j.neuroimage.2020.116763 UR - https://m2.mtmt.hu/api/publication/31295716 ID - 31295716 N1 - Translational Neuroscience Program, Wayne State University, Detroit, MI, United States Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, United States Dept. of Neurology, Wayne State University, Children's Hospital of Michigan, Detroit, MI, United States Translational Imaging Laboratory, Wayne State University, Detroit, MI, United States Export Date: 30 April 2020 CODEN: NEIME Correspondence Address: Jeong, J.-W.; Neurology and Translational Neuroscience Program Wayne State University School of Medicine Translational Imaging Laboratory, PET Center, Children's Hospital of Michigan 3901 Beaubien Street DetroitUnited States; email: jjeong@med.wayne.edu Funding details: National Institutes of Health, NIH, R01 NS089659, R01 NS064033 Funding text 1: This work was supported by grants from the National Institutes of Health ( R01 NS089659 to J.J. and R01 NS064033 to E.A.). LA - English DB - MTMT ER - TY - JOUR AU - Srivastava, Pragya AU - Nozari, Erfan AU - Kim, Jason Z. AU - Ju, Harang AU - Zhou, Dale AU - Becker, Cassiano AU - Pasqualetti, Fabio AU - Pappas, George J. AU - Bassett, Danielle S. TI - Models of communication and control for brain networks: distinctions, convergence, and future outlook JF - NETWORK NEUROSCIENCE J2 - NETW NEUROSCI VL - 4 PY - 2020 IS - 4 SP - 1122 EP - 1159 PG - 38 SN - 2472-1751 DO - 10.1162/netn_a_00158 UR - https://m2.mtmt.hu/api/publication/31689444 ID - 31689444 N1 - Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States Department of Mechanical Engineering, University of, California Riverside, Riverside, CA, United States Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, United States Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States Santa Fe Institute, Santa Fe, NM, United States Cited By :4 Export Date: 22 March 2022 Correspondence Address: Bassett, D.S.; Department of Bioengineering, United States; email: dsb@seas.upenn.edu Correspondence Address: Bassett, D.S.; Department of Electrical & Systems Engineering, United States; email: dsb@seas.upenn.edu Correspondence Address: Bassett, D.S.; Department of Physics & Astronomy, United States; email: dsb@seas.upenn.edu Correspondence Address: Bassett, D.S.; Department of Neurology, United States; email: dsb@seas.upenn.edu Correspondence Address: Bassett, D.S.; Department of Psychiatry, United States; email: dsb@seas.upenn.edu Correspondence Address: Bassett, D.S.; Santa Fe InstituteUnited States; email: dsb@seas.upenn.edu Funding details: National Science Foundation, NSF, 1430087, 1441502, 1554488, BCS-1631550, PHY-1554488 Funding details: Office of Naval Research, ONR Funding details: National Institute of Mental Health, NIMH, 2-R01-DC-009209-11, R01-MH107235, R01-MH112847, R21-M MH-106799 Funding details: National Institute of Neurological Disorders and Stroke, NINDS, BCS-1430087, BCS-1441502, R01 NS099348 Funding details: National Institute of Child Health and Human Development, NICHD, 1R01HD086888-01 Funding details: Army Research Office, ARO, W911NF-18-1-0244 Funding details: John D. and Catherine T. MacArthur Foundation Funding details: Alfred P. Sloan Foundation Funding details: Army Research Laboratory, ARL, Bassett-W911NF-14-1-0679, DCIST-W911NF-17-2-0181, Grafton-W911NF-16-1-0474, W911NF-10-2-0022 Funding text 1: This work was primarily supported by the National Science Foundation (BCS-1631550), the Army Research Office (W911NF-18-1-0244), and the Paul G. Allen Family Foundation. We would also like to acknowledge additional support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the ISI Foundation, the Army Research Laboratory (W911NF-10-2-0022), the Army Research Office (Bassett-W911NF-14-1-0679, Grafton-W911NF-16-1-0474, DCIST-W911NF-17-2-0181), the Office of Naval Research, the National Institute of Mental Health (2-R01-DC-009209-11, R01-MH112847, R01-MH107235, R21-M MH-106799), the National Institute of Child Health and Human Development (1R01HD086888-01), National Institute of Neurological Disorders and Stroke (R01 NS099348), and the National Science Foundation (BCS-1441502, BCS-1430087, and NSF PHY-1554488). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. AB - Author SummaryModels of communication in brain networks have been essential in building a quantitative understanding of the relationship between structure and function. More recently, control-theoretic models have also been applied to brain networks to quantify the response of brain networks to exogenous and endogenous perturbations. Mechanistically, both of these frameworks investigate the role of interregional communication in determining the behavior and response of the brain. Theoretically, both of these frameworks share common features, indicating the possibility of combining the two approaches. Drawing on a large body of past and ongoing works, this review presents a discussion of convergence and distinctions between the two approaches, and argues for the development of integrated models at the confluence of the two frameworks, with potential applications to various topics in neuroscience.Recent advances in computational models of signal propagation and routing in the human brain have underscored the critical role of white-matter structure. A complementary approach has utilized the framework of network control theory to better understand how white matter constrains the manner in which a region or set of regions can direct or control the activity of other regions. Despite the potential for both of these approaches to enhance our understanding of the role of network structure in brain function, little work has sought to understand the relations between them. Here, we seek to explicitly bridge computational models of communication and principles of network control in a conceptual review of the current literature. By drawing comparisons between communication and control models in terms of the level of abstraction, the dynamical complexity, the dependence on network attributes, and the interplay of multiple spatiotemporal scales, we highlight the convergence of and distinctions between the two frameworks. Based on the understanding of the intertwined nature of communication and control in human brain networks, this work provides an integrative perspective for the field and outlines exciting directions for future work. LA - English DB - MTMT ER - TY - JOUR AU - Steinhardt, Cynthia R. AU - Sacre, Pierre AU - Sheehan, Timothy C. AU - Wittig, John H. AU - Inati, Sara K. AU - Sarma, Sridevi AU - Zaghloul, Kareem A. TI - Characterizing and predicting cortical evoked responses to direct electrical stimulation of the human brain JF - BRAIN STIMULATION J2 - BRAIN STIMUL VL - 13 PY - 2020 IS - 5 SP - 1218 EP - 1225 PG - 8 SN - 1935-861X DO - 10.1016/j.brs.2020.05.001 UR - https://m2.mtmt.hu/api/publication/31689442 ID - 31689442 N1 - Funding Agency and Grant Number: Intramural Research Program of the National Institute for Neurological Disorders and Stroke; DARPA Restoring Active Memory (RAM) program [N66001-14-2-4032] Funding text: This work was supported by the Intramural Research Program of the National Institute for Neurological Disorders and Stroke and partially supported by the DARPA Restoring Active Memory (RAM) program (Cooperative Agreement N66001-14-2-4032). AB - Background: Direct electrical stimulation of the human brain has been used to successfully treat several neurological disorders, but the precise effects of stimulation on neural activity are poorly understood. Characterizing the neural response to stimulation, however, could allow clinicians and researchers to more accurately predict neural responses, which could in turn lead to more effective stimulation for treatment and to fundamental knowledge regarding neural function.Objective: Here we use a linear systems approach in order to characterize the response to electrical stimulation across cortical locations and then to predict the responses to novel inputs.Methods: We use intracranial electrodes to directly stimulate the human brain with single pulses of stimulation using amplitudes drawn from a random distribution. Based on the evoked responses, we generate a simple model capturing the characteristic response to stimulation at each cortical site. Results: We find that the variable dynamics of the evoked response across cortical locations can be captured using the same simple architecture, a linear time-invariant system that operates separately on positive and negative input pulses of stimulation. We demonstrate that characterizing the response to stimulation using this simple and tractable model of evoked responses enables us to predict the responses to subsequent stimulation with single pulses with novel amplitudes, and the compound response to stimulation with multiple pulses.Conclusion: Our data suggest that characterizing the response to stimulation in an approximately linear manner can provide a powerful and principled approach for predicting the response to direct electrical stimulation. (C) 2020 The Author(s). Published by Elsevier Inc. LA - English DB - MTMT ER - TY - JOUR AU - Sugiura, A. AU - Silverstein, B.H. AU - Jeong, J.-W. AU - Nakai, Y. AU - Sonoda, M. AU - Motoi, H. AU - Asano, E. TI - Four-dimensional map of direct effective connectivity from posterior visual areas JF - NEUROIMAGE J2 - NEUROIMAGE VL - 210 PY - 2020 SN - 1053-8119 DO - 10.1016/j.neuroimage.2020.116548 UR - https://m2.mtmt.hu/api/publication/31406151 ID - 31406151 N1 - Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, MI 48201, United States Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, MI 48201, United States Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, United States Department of Neurological Surgery, Wakayama Medical University, Wakayama-shi, 6418509, Japan Cited By :1 Export Date: 18 August 2020 CODEN: NEIME Correspondence Address: Asano, E.; Department of Neurodiagnostics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center. 3901 Beaubien St., United States; email: easano@med.wayne.edu LA - English DB - MTMT ER - TY - JOUR AU - Toth, Emilia AU - Chaitanya, Ganne AU - Pati, Sandipan TI - Mapping short-latency cortical responses to electrical stimulation of thalamic motor nuclei by increasing sampling rate - A technical report JF - CLINICAL NEUROPHYSIOLOGY J2 - CLIN NEUROPHYSIOL VL - 131 PY - 2020 IS - 1 SP - 142 EP - 144 PG - 3 SN - 1388-2457 DO - 10.1016/j.clinph.2019.10.015 UR - https://m2.mtmt.hu/api/publication/31425917 ID - 31425917 LA - English DB - MTMT ER - TY - JOUR AU - Uehlin, John P. AU - Smith, William Anthony AU - Pamula, Venkata Rajesh AU - Pepin, Eric P. AU - Perlmutter, Steve AU - Sathe, Visvesh AU - Rudell, Jacques Christophe TI - A Single-Chip Bidirectional Neural Interface With High-Voltage Stimulation and Adaptive Artifact Cancellation in Standard CMOS JF - IEEE JOURNAL OF SOLID-STATE CIRCUITS J2 - IEEE J SOLID-ST CIRC VL - 55 PY - 2020 IS - 7 SP - 1749 EP - 1761 PG - 13 SN - 0018-9200 DO - 10.1109/JSSC.2020.2991524 UR - https://m2.mtmt.hu/api/publication/31425918 ID - 31425918 N1 - Funding Agency and Grant Number: Medtronic; Center for Neurotechnology, under NSF [EEC-1028725] Funding text: This work was supported by Medtronic and the Center for Neurotechnology, under NSF Award Number EEC-1028725. AB - A single-chip, bidirectional brain-computer interface (BBCI) enables neuromodulation through simultaneous neural recording and stimulation. This article presents a prototype BBCI application-specified integrated circuit (ASIC) consisting of a 64-channel time-multiplexed recording frontend, an area-optimized four-channel high-voltage compliant stimulator, and electronics to support the concurrent multichannel stimulus artifact cancellation. Stimulator power generation is integrated on a chip, providing +/- 11-V compliance from low-voltage supplies with a resonant charge pump. Highfrequency (similar to 3 GHz) self-resonant clocking is used to reduce the pumping capacitor area while suppressing the associated switching losses. A 32-tap least mean square (LMS)-based digital adaptive filter achieves 60-dB artifact suppression, enabling simultaneous neural stimulation and recording. The entire chip occupies 4 mm(2) in a 65-nm low power (LP) process and is powered by 2.5-/1.2-V supplies, dissipating 205 mu W in recording and 142 mu W in the stimulation and cancellation back-ends. The stimulation output drivers achieve 31% dc-dc efficiency at a maximum output power of 24 mW. LA - English DB - MTMT ER - TY - JOUR AU - Caldwell, David J. AU - Ojemann, Jeffrey G. AU - Rao, Rajesh P. N. TI - Direct Electrical Stimulation in Electrocorticographic Brain-Computer Interfaces: Enabling Technologies for Input to Cortex JF - FRONTIERS IN NEUROSCIENCE J2 - FRONT NEUROSCI-SWITZ VL - 13 PY - 2019 PG - 16 SN - 1662-4548 DO - 10.3389/fnins.2019.00804 UR - https://m2.mtmt.hu/api/publication/31023491 ID - 31023491 N1 - Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Export Date: 25 January 2020 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, University of WashingtonUnited States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF Funding details: National Institutes of Health, NIH Funding details: RR Funding details: 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Funding Agency and Grant Number: National Science Foundation (NSF) Center for Neurotechnology (CNT) [EEC-1028725]; NSFNational Science Foundation (NSF) [IIS-1514790]; Big Data for Genomics & Neuroscience Training Grant [1T32CA206089-01A1]; Washington Research Foundation Funds for Innovation in Neuroengineering; CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering Funding text: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Export Date: 12 March 2020 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, University of WashingtonUnited States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF Funding details: National Institutes of Health, NIH Funding details: RR Funding details: 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Export Date: 21 March 2020 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, University of WashingtonUnited States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF, 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding details: Washington Research Foundation, WRF Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Cited By :3 Export Date: 10 August 2020 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, University of WashingtonUnited States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF, 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding details: Washington Research Foundation, WRF Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Cited By :7 Export Date: 21 February 2021 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, United States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF, 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding details: Washington Research Foundation, WRF Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Funding Agency and Grant Number: National Science Foundation (NSF) Center for Neurotechnology (CNT) [EEC-1028725]; NSFNational Science Foundation (NSF) [IIS-1514790]; Big Data for Genomics & Neuroscience Training Grant [1T32CA206089-01A1]; Washington Research Foundation Funds for Innovation in Neuroengineering; CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering; NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [T32GM007266, T32GM007266, T32GM007266, T32GM007266, T32GM007266] Funding Source: NIH RePORTER Funding text: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Cited By :8 Export Date: 21 March 2021 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, United States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF, 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding details: National Institute of General Medical Sciences, NIGMS, T32GM007266 Funding details: Washington Research Foundation, WRF Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Funding text 2: The authors would like to thank the patients who dedicated their time and energy to the experiments which allow the field of electrocortigraphic BCIs to move forward, and without whom, this research would not be possible. The authors would also like to thank Jeffrey Herron for valuable conversation and feedback. Funding Agency and Grant Number: National Science Foundation (NSF) Center for Neurotechnology (CNT) [EEC-1028725]; NSFNational Science Foundation (NSF) [IIS-1514790]; Big Data for Genomics & Neuroscience Training Grant [1T32CA206089-01A1]; Washington Research Foundation Funds for Innovation in Neuroengineering; CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering; NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [T32GM007266] Funding Source: NIH RePORTER Funding text: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Department of Bioengineering, University of Washington, Seattle, WA, United States Medical Scientist Training Program, University of Washington, Seattle, WA, United States Center for Neurotechnology, University of Washington, Seattle, WA, United States Department of Neurological Surgery, University of Washington, Seattle, WA, United States Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States Cited By :12 Export Date: 21 September 2021 Correspondence Address: Rao, R.P.N.; Department of Bioengineering, United States; email: rao@cs.washington.edu Funding details: National Science Foundation, NSF, 1028725, 1514790, 1T32CA206089-01A1, EEC-1028725, IIS-1514790 Funding details: National Institute of General Medical Sciences, NIGMS, T32GM007266 Funding details: Washington Research Foundation, WRF Funding text 1: This work was supported by the National Science Foundation (NSF) Center for Neurotechnology (CNT) (Award Number EEC-1028725) and NSF Award Number IIS-1514790. DC was supported by the Big Data for Genomics & Neuroscience Training Grant under Grant Number 1T32CA206089-01A1 and by the Washington Research Foundation Funds for Innovation in Neuroengineering. RR is supported by the CJ and Elizabeth Hwang Endowed Professorship for Computer Science and Engineering and Electrical and Computer Engineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. Funding text 2: The authors would like to thank the patients who dedicated their time and energy to the experiments which allow the field of electrocortigraphic BCIs to move forward, and without whom, this research would not be possible. The authors would also like to thank Jeffrey Herron for valuable conversation and feedback. AB - Electrocorticographic brain computer interfaces (ECoG-BCIs) offer tremendous opportunities for restoring function in individuals suffering from neurological damage and for advancing basic neuroscience knowledge. ECoG electrodes are already commonly used clinically for monitoring epilepsy and have greater spatial specificity in recording neuronal activity than techniques such as electroencephalography (EEG). Much work to date in the field has focused on using ECoG signals recorded from cortex as control outputs for driving end effectors. An equally important but less explored application of an ECoG-BCI is directing input into cortex using ECoG electrodes for direct electrical stimulation (DES). Combining DES with ECoG recording enables a truly bidirectional BCI, where information is both read from and written to the brain. We discuss the advantages and opportunities, as well as the barriers and challenges presented by using DES in an ECoG-BCI. In this article, we review ECoG electrodes, the physics and physiology of DES, and the use of electrical stimulation of the brain for the clinical treatment of disorders such as epilepsy and Parkinson's disease. We briefly discuss some of the translational, regulatory, financial, and ethical concerns regarding ECoG-BCIs. Next, we describe the use of ECoG-based DES for providing sensory feedback and for probing and modifying cortical connectivity. We explore future directions, which may draw on invasive animal studies with penetrating and surface electrodes as well as non-invasive stimulation methods such as transcranial magnetic stimulation (TMS). We conclude by describing enabling technologies, such as smaller ECoG electrodes for more precise targeting of cortical areas, signal processing strategies for simultaneous stimulation and recording, and computational modeling and algorithms for tailoring stimulation to each individual brain. LA - English DB - MTMT ER - TY - JOUR AU - Crowther, Lawrence J. AU - Brunner, Peter AU - Kapeller, Christoph AU - Guger, Christoph AU - Kamada, Kyousuke AU - Bunch, Marjorie E. AU - Frawley, Bridget K. AU - Lynch, Timothy M. AU - Ritaccio, Anthony L. AU - Schalk, Gerwin TI - A quantitative method for evaluating cortical responses to electrical stimulation JF - JOURNAL OF NEUROSCIENCE METHODS J2 - J NEUROSCI METH VL - 311 PY - 2019 SP - 67 EP - 75 PG - 9 SN - 0165-0270 DO - 10.1016/j.jneumeth.2018.09.034 UR - https://m2.mtmt.hu/api/publication/30388857 ID - 30388857 N1 - National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, United States Department of Neurology, Albany Medical College, Albany, NY, United States g.tec Guger Technologies OG, Graz, Austria Department of Neurosurgery, Asahikawa Medical University, Asahikawa, Japan Department of Biomedical Sciences, State University of New York at Albany, Albany, NY, United States Department of Neurology, Mayo Clinic, Jacksonville, FL, United States Cited By :8 Export Date: 18 August 2020 CODEN: JNMED Correspondence Address: Schalk, G.; National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of HealthUnited States; email: gschalk@neurotechcenter.org AB - Background: Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. LA - English DB - MTMT ER - TY - JOUR AU - Hebbink, Jurgen AU - van Blooijs, Dorien AU - Huiskamp, Geertjan AU - Leijten, Frans S. S. AU - van Gils, Stephan A. AU - Meijer, Hil G. E. TI - A Comparison of Evoked and Non-evoked Functional Networks JF - BRAIN TOPOGRAPHY J2 - BRAIN TOPOGR VL - 32 PY - 2019 IS - 3 SP - 405 EP - 417 PG - 13 SN - 0896-0267 DO - 10.1007/s10548-018-0692-1 UR - https://m2.mtmt.hu/api/publication/31021978 ID - 31021978 N1 - Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, Netherlands Department of Applied Mathematics, MIRA Institute for Biomedical Engineering and Technical Medicine, University of Twente, Drienerlolaan 5, Enschede, 7500 AE, Netherlands Cited By :7 Export Date: 18 August 2020 CODEN: BRTOE Correspondence Address: Hebbink, J.; Department of Applied Mathematics, MIRA Institute for Biomedical Engineering and Technical Medicine, University of Twente, Drienerlolaan 5, Netherlands; email: g.j.hebbink@utwente.nl AB - The growing interest in brain networks to study the brain's function in cognition and diseases has produced an increase in methods to extract these networks. Typically, each method yields a different network. Therefore, one may ask what the resulting networks represent. To address this issue we consider electrocorticography (ECoG) data where we compare three methods. We derive networks from on-going ECoG data using two traditional methods: cross-correlation (CC) and Granger causality (GC). Next, connectivity is probed actively using single pulse electrical stimulation (SPES). We compare the overlap in connectivity between these three methods as well as their ability to reveal well-known anatomical connections in the language circuit. We find that strong connections in the CC network form more or less a subset of the SPES network. GC and SPES are related more weakly, although GC connections coincide more frequently with SPES connections compared to non-existing SPES connections. Connectivity between the two major hubs in the language circuit, Broca's and Wernicke's area, is only found in SPES networks. Our results are of interest for the use of patient-specific networks obtained from ECoG. In epilepsy research, such networks form the basis for methods that predict the effect of epilepsy surgery. For this application SPES networks are interesting as they disclose more physiological connections compared to CC and GC networks. LA - English DB - MTMT ER - TY - JOUR AU - Huang, Yuhao AU - Hajnal, Boglárka Zsófia AU - Entz, László AU - Fabó, Dániel AU - Herrero, Jose L. AU - Mehta, Ashesh D. AU - Keller, Corey J. TI - Intracortical Dynamics Underlying Repetitive Stimulation Predicts Changes in Network Connectivity JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 39 PY - 2019 IS - 31 SP - 6122 EP - 6135 PG - 14 SN - 0270-6474 DO - 10.1523/JNEUROSCI.0535-19.2019 UR - https://m2.mtmt.hu/api/publication/31020318 ID - 31020318 N1 - Funding Agency and Grant Number: National Institute of Neurological Disorders and Stroke [F31NS080357-01, T32-GM007288]; Stanford Society of Physician Scholars Collaborative Research Fellowship; Alpha Omega Alpha Postgraduate Research Award; Hungarian National Research, Development, and Innovation Office [2017-1.2.1-NKP-2017-00002]; NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM007288] Funding Source: NIH RePORTER Funding text: This work was supported by the National Institute of Neurological Disorders and Stroke (F31NS080357-01 and T32-GM007288), Stanford Society of Physician Scholars Collaborative Research Fellowship, and Alpha Omega Alpha Postgraduate Research Award to C.J.K., and by the Hungarian National Research, Development, and Innovation Office (2017-1.2.1-NKP-2017-00002) to D.F. We thank Maria Fini and Victor Du for help with data collection, Pierre Megevand and Erin Yeagle for help with technical considerations of the experimental design, and Wei Wu for comments on the paper. All authors discussed the data, analysis, and methods and contributed to the paper. The authors are enormously indebted to the patients who participated in this study, as well as the nursing and physician staff at North Shore University Hospital (Manhassat, NY) and the National Institute of Clinical Neurosciences (Budapest, Hungary). AB - Targeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable poststimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to poststimulation effects is limited but critical for treatment optimization. Here, we applied 10 Hz direct electrical stimulation across several cortical regions in 14 human subjects (6 males) implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70 -170 Hz) power. Immediately post-train, low-frequency (1-8 Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, corticocortical evoked potentials (indexing effective connectivity), and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just 2 min (similar to 10%) of repetitive stimulation, we were able to predict poststimulation connectivity changes with high disc rim inability. Together, this work reveals a relationship between stimulation dynamics and poststimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols. LA - English DB - MTMT ER - TY - JOUR AU - Oderiz, Carolina Cuello AU - von Ellenrieder, Nicolas AU - Dubeau, Francois AU - Eisenberg, Ariella AU - Gotman, Jean AU - Hall, Jeffery AU - Hincapie, Ana-Sofia AU - Hoffmann, Dominique AU - Job, Anne-Sophie AU - Khoo, Hui Ming AU - Minotti, Lorella AU - Olivier, Andre AU - Kahane, Phillippe AU - Frauscher, Birgit TI - Association of Cortical Stimulation-Induced Seizure With Surgical Outcome in Patients With Focal Drug-Resistant Epilepsy JF - JAMA NEUROLOGY J2 - JAMA NEUROL VL - 76 PY - 2019 IS - 9 SP - 1070 EP - 1078 PG - 9 SN - 2168-6149 DO - 10.1001/jamaneurol.2019.1464 UR - https://m2.mtmt.hu/api/publication/31023489 ID - 31023489 N1 - Funding Agency and Grant Number: Canadian Institute of Health Research [FDN-143208]; Savoy Epilepsy Foundation; CIBC Post-Doctoral Fellowship in Brain Imaging from the Montreal Neurological Institute; Fonds de Recherche du Quebec-Sante Funding text: This research is supported in part by grant FDN-143208 from the Canadian Institute of Health Research (Dr Gotman) and by a project grant from the Savoy Epilepsy Foundation (Dr Dubeau). Dr Hincapie's salary is supported by a CIBC Post-Doctoral Fellowship in Brain Imaging from the Montreal Neurological Institute. Dr Frauscher's salary is supported by Chercheur-boursier clinicien Junior 2, 2018-2021 award from the Fonds de Recherche du Quebec-Sante. AB - Key PointsQuestionIs seizure induction by cortical stimulation during intracranial electroencephalography associated with good surgical outcome in patients with focal drug-resistant epilepsy? FindingsIn this cohort study of 103 patients with focal drug-resistant epilepsy, cortical stimulation induced typical electroclinical seizures in 59 patients (57.3%). Induction of seizures was associated with better surgical outcome; a higher percentage of resected contacts from the seizure-onset zone informed by cortical stimulation, similar to that of spontaneous seizures, was associated with better surgical outcome. MeaningCortical stimulation appears to be reliable in identifying the cortical area responsible for seizure generation and to be associated with surgical outcome.ImportanceCortical stimulation is used during presurgical epilepsy evaluation for functional mapping and for defining the cortical area responsible for seizure generation. Despite wide use of cortical stimulation, the association between cortical stimulation-induced seizures and surgical outcome remains unknown. ObjectiveTo assess whether removal of the seizure-onset zone resulting from cortical stimulation is associated with a good surgical outcome. Design, Setting, and ParticipantsThis cohort study used data from 2 tertiary epilepsy centers: Montreal Neurological Institute in Montreal, Quebec, Canada, and Grenoble-Alpes University Hospital in Grenoble, France. Participants included consecutive patients (n=103) with focal drug-resistant epilepsy who underwent stereoelectroencephalography between January 1, 2007, and January 1, 2017. Participant selection criteria were cortical stimulation during implantation, subsequent open surgical procedure with a follow-up of 1 or more years, and complete neuroimaging data sets for superimposition between intracranial electrodes and the resection. Main Outcomes and MeasuresCortical stimulation-induced typical electroclinical seizures, the volume of the surgical resection, and the percentage of resected electrode contacts inducing a seizure or encompassing the cortical stimulation-informed and spontaneous seizure-onset zones were identified. These measures were correlated with good (Engel class I) and poor (Engel classes II-IV) surgical outcomes. Electroclinical characteristics associated with cortical stimulation-induced seizures were analyzed. ResultsIn total, 103 patients were included, of whom 54 (52.4%) were female, and the mean (SD) age was 31(11) years. Fifty-nine patients (57.3%) had cortical stimulation-induced seizures. The percentage of patients with cortical stimulation-induced electroclinical seizures was higher in the good outcome group than in the poor outcome group (31 of 44 [70.5%] vs 28 of 59 [47.5%]; P=.02). The percentage of the resected contacts encompassing the cortical stimulation-informed seizure-onset zone correlated with surgical outcome (median [range] percentage in good vs poor outcome: 63.2% [0%-100%] vs 33.3% [0%-84.6%]; Spearman rho =0.38; P=.003). A similar result was observed for spontaneous seizures (median [range] percentage in good vs poor outcome: 57.1% [0%-100%] vs 32.7% [0%-100%]; Spearman rho =0.32; P=.002). Longer elapsed time since the most recent seizure was associated with a higher likelihood of inducing seizures (>24 hours: 64.7% vs <24 hours: 27.3%; P=.04). Conclusions and RelevanceSeizure induction by cortical stimulation appears to identify the epileptic generator as reliably as spontaneous seizures do; this finding might lead to a more time-efficient intracranial presurgical investigation of focal epilepsy as the need to record spontaneous seizures is reduced.This cohort study examines the cortical stimulation of the epileptogenic zone and its association with good or poor outcomes in patients with focal epilepsy. LA - English DB - MTMT ER - TY - JOUR AU - Sakellariou, Dimitris F. AU - Koutroumanidis, Michalis AU - Richardson, Mark P. AU - Kostopoulos, George K. TI - Cross-subject network investigation of the EEG microstructure: A sleep spindles study JF - JOURNAL OF NEUROSCIENCE METHODS J2 - J NEUROSCI METH VL - 312 PY - 2019 SP - 16 EP - 26 PG - 11 SN - 0165-0270 DO - 10.1016/j.jneumeth.2018.11.001 UR - https://m2.mtmt.hu/api/publication/30513083 ID - 30513083 N1 - Funding Agency and Grant Number: Medical Research Council Confidence in Concept grant [MC_PC_16048]; ARMOR EU (FP7/2007-2013) [287720]; Medical Research Council [MR/K013998/1]; Engineering and Physical Sciences Research Council (Centre for Predictive Modelling in Healthcare) [EP/N014391/1]; NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust; EPSRC [EP/N014391/1] Funding Source: UKRI; MRC [MR/K013998/1, MC_PC_16048] Funding Source: UKRI Funding text: DFS is funded by the Medical Research Council Confidence in Concept grant (#MC_PC_16048). GKK was funded by ARMOR EU (FP7/2007-2013) agreement number 287720. MR is funded by Medical Research Council (Programme grant MR/K013998/1), Engineering and Physical Sciences Research Council (Centre for Predictive Modelling in Healthcare EP/N014391/1) and by the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust. AB - Background: The microstructural EEG elements and their functional networks relate to many neurophysiological functions of the brain and can reveal abnormalities. Despite the blooming variety of methods for estimating connectivity in the EEG of a single subject, a common pitfall is seen in relevant studies; grand averaging is used for estimating the characteristic connectivity patterns of a group of subjects. This averaging may distort results and fail to account for the internal variability of connectivity results across the subjects of a group. LA - English DB - MTMT ER - TY - JOUR AU - Snyder, Abraham Z. AU - Bauer, Adam Q. TI - Mapping Structure-Function Relationships in the Brain JF - BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING J2 - BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGINING VL - 4 PY - 2019 IS - 6 SP - 510 EP - 521 PG - 12 SN - 2451-9022 DO - 10.1016/j.bpsc.2018.10.005 UR - https://m2.mtmt.hu/api/publication/31023488 ID - 31023488 N1 - Funding Agency and Grant Number: National Institutes of Health [R01NS102870, K25NS083754, P01NS080675, P30NS098577]; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [P01NS080675, R01NS102870, P30NS098577, K25NS083754] Funding Source: NIH RePORTER Funding text: This work was supported by National Institutes of Health Grant Nos. R01NS102870 (to AQB), K25NS083754 (to AQB), P01NS080675 (to AZS), and P30NS098577 (to AZS). AB - Mapping the structural and functional connectivity of the brain is a major focus of systems neuroscience research and will help to identify causally important changes in neural circuitry responsible for behavioral dysfunction. Several methods for examining brain activity in humans have been extended to rodent and monkey models in which molecular and genetic manipulations exist for linking to human disease. In this review, which is part of a special issue focused on bridging brain connectivity information across species and spatiotemporal scales, we address mapping brain activity and neural connectivity in rodents using optogenetics in conjunction with either functional magnetic resonance imaging or optical intrinsic signal imaging. We chose to focus on these techniques because they are capable of reporting spontaneous or evoked hemodynamic activity most closely linked to human neuroimaging studies. We discuss the capabilities and limitations of blood-based imaging methods, usage of optogenetic techniques to map neural systems in rodent models, and other powerful mapping techniques for examining neural connectivity over different spatial and temporal scales. We also discuss implementing strategies for mapping brain connectivity in humans with both basic and clinical applications, and conclude with how cross-species mapping studies can be utilized to influence preclinical imaging studies and clinical practices alike. LA - English DB - MTMT ER - TY - JOUR AU - Tavildar, Siddhi AU - Mogen, Brian AU - Zanos, Stavros AU - Seeman, Stephanie C. AU - Perlmutter, Steve I AU - Fetz, Eberhard AU - Ashrafi, Ashkan TI - Inferring Cortical Connectivity From ECoG Signals Using Graph Signal Processing JF - IEEE ACCESS J2 - IEEE ACCESS VL - 7 PY - 2019 SP - 109349 EP - 109362 PG - 14 SN - 2169-3536 DO - 10.1109/ACCESS.2019.2934490 UR - https://m2.mtmt.hu/api/publication/33255133 ID - 33255133 N1 - Funding Agency and Grant Number: NSF Center for Neurotechnology [EEC-1028725] Funding text: This work was supported by the NSF Center for Neurotechnology under Grant EEC-1028725. AB - A novel method to characterize connectivity between sites in the cerebral cortex of primates is proposed in this paper. Connectivity graphs for two macaque monkeys are inferred from Electrocorticographic (ECoG) activity recorded while the animals were alert. The locations of ECoG electrodes are considered as nodes of the graph, the coefficients of the auto-regressive (AR) representation of the signals measured at each node are considered as the signal on the graph and the connectivity strengths between the nodes are considered as the edges of the graph. Maximization of the graph smoothness defined from the Laplacian quadratic form is used to infer the connectivity map (adjacency matrix of the graph). The cortical evoked potential (CEP) map was obtained by stimulating different electrodes and recording the evoked potentials at the other electrodes. The maps obtained by the graph inference and the traditional method of spectral coherence are compared with the CEP map. The results show that the proposed method provides a description of cortical connectivity that is more similar to the stimulation-based measures than spectral coherence. The results are also tested by the surrogate map analysis in which the CEP map is randomly permuted and the distribution of the errors is obtained. It is shown that error between the two maps is comfortably outside the surrogate map error distribution. This indicates that the similarity between the map calculated by the graph inference and the CEP map is statistically significant. LA - English DB - MTMT ER - TY - JOUR AU - Tavildar, Siddhi AU - Mogen, Brian AU - Zanos, Stavros AU - Seeman, Stephanie C. AU - Perlmutter, Steve I. AU - Fetz, Eberhard AU - Ashrafi, Ashkan TI - Inferring Cortical Connectivity From ECoG Signals Using Graph Signal Processing JF - IEEE ACCESS J2 - IEEE ACCESS VL - 7 PY - 2019 SP - 109349 EP - 109362 PG - 14 SN - 2169-3536 DO - 10.1109/ACCESS.2019.2934490 UR - https://m2.mtmt.hu/api/publication/31581020 ID - 31581020 AB - A novel method to characterize connectivity between sites in the cerebral cortex of primates is proposed in this paper. Connectivity graphs for two macaque monkeys are inferred from Electrocorticographic (ECoG) activity recorded while the animals were alert. The locations of ECoG electrodes are considered as nodes of the graph, the coefficients of the auto-regressive (AR) representation of the signals measured at each node are considered as the signal on the graph and the connectivity strengths between the nodes are considered as the edges of the graph. Maximization of the graph smoothness defined from the Laplacian quadratic form is used to infer the connectivity map (adjacency matrix of the graph). The cortical evoked potential (CEP) map was obtained by stimulating different electrodes and recording the evoked potentials at the other electrodes. The maps obtained by the graph inference and the traditional method of spectral coherence are compared with the CEP map. The results show that the proposed method provides a description of cortical connectivity that is more similar to the stimulation-based measures than spectral coherence. The results are also tested by the surrogate map analysis in which the CEP map is randomly permuted and the distribution of the errors is obtained. It is shown that error between the two maps is comfortably outside the surrogate map error distribution. This indicates that the similarity between the map calculated by the graph inference and the CEP map is statistically significant. LA - English DB - MTMT ER - TY - JOUR AU - Usami, Kiyohide AU - Korzeniewska, Anna AU - Matsumoto, Riki AU - Kobayashi, Katsuya AU - Hitomi, Takefumi AU - Matsuhashi, Masao AU - Kunieda, Takeharu AU - Mikuni, Nobuhiro AU - Kikuchi, Takayuki AU - Yoshida, Kazumichi AU - Miyamoto, Susumu AU - Takahashi, Ryosuke AU - Ikeda, Akio AU - Crone, Nathan E. TI - The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation JF - SLEEP J2 - SLEEP VL - 42 PY - 2019 IS - 6 PG - 9 SN - 0161-8105 DO - 10.1093/sleep/zsz050 UR - https://m2.mtmt.hu/api/publication/31021975 ID - 31021975 N1 - Department of Neurology, Johns Hopkins University, School of Medicine, Baltimore, MD, United States Department of Neurology, Kyoto University, Graduate School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan Department of Clinical Laboratory Medicine, Kyoto University, Graduate School of Medicine, Sakyo-ku, Kyoto, Japan Department of Respiratory Care and Sleep Control Medicine, Kyoto University, Graduate School of Medicine, Sakyoku, Kyoto, Japan Research and Educational Unit of Leaders for Integrated Medical System, Kyoto University, Graduate School of Medicine, Sakyo-ku, Kyoto, Japan Human Brain Research Center, Kyoto University, Graduate School of Medicine, Sakyo-ku, Kyoto, Japan Department of Neurosurgery, Kyoto University, Graduate School of Medicine, Sakyo-ku, Kyoto, Japan Department of Neurosurgery, Ehime University, Graduate School of Medicine, Shizukawa Toon city, Ehime, Japan Department of Neurosurgery, Sapporo Medical University, Chuo-ku, Sapporo, Japan Department of Epilepsy, Movement Disorders and Physiology, Kyoto University, Graduate School of Medicine, Sakyo-ku, Kyoto, Japan Cited By :5 Export Date: 18 August 2020 CODEN: SLEED Correspondence Address: Usami, K.; Department of Neurology, Kyoto University, Graduate School of Medicine, 54 Shogoin-Kawahara-cho, Japan; email: ukiyo@kuhp.kyoto-u.ac.jp AB - Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks. LA - English DB - MTMT ER - TY - JOUR AU - Yoshimoto, Tetsuyuki AU - Maruichi, Katsuhiko AU - Itoh, Yasuhiro AU - Takamiya, Soichiro AU - Kaneko, Tetsuya TI - Monitoring Corticocortical Evoked Potentials During Intracranial Vascular Surgery JF - WORLD NEUROSURGERY J2 - WORLD NEUROSURG VL - 122 PY - 2019 SP - E947 EP - E954 PG - 8 SN - 1878-8750 DO - 10.1016/j.wneu.2018.10.179 UR - https://m2.mtmt.hu/api/publication/30512872 ID - 30512872 N1 - Department of Neurosurgery, Kashiwaba Neurosurgical Hospital, Sapporo, Japan Department of Neurophysiology, Kashiwaba Neurosurgical Hospital, Sapporo, Japan Department of Neurosurgery, Hokkaido University School of Medicine, Sapporo, Japan Export Date: 18 August 2020 Correspondence Address: Yoshimoto, T.; Department of Neurosurgery, Kashiwaba Neurosurgical HospitalJapan; email: yossikamer@me.com AB - BACKGROUND: Monitoring of corticocortical evoked potentials (CCEPs) during brain tumor surgery of patients under anesthesia was recently reported to be effective in assisting in preservation of speech function. The aim of this study was to investigate whether CCEPs can be reproducibly measured between the frontal and temporal lobes during standard intracranial vascular surgery under general anesthesia; whether dynamic changes in CCEPs caused by reduced focal cerebral blood flow can be measured; and whether CCEPs can be used to monitor speech function, particularly associated with the left side of the brain. LA - English DB - MTMT ER - TY - JOUR AU - Yu, Xiaoman AU - Ding, Ping AU - Yuan, Liu AU - Zhang, Juncheng AU - Liang, Shuangshuang AU - Zhang, Shaohui AU - Liu, Na AU - Liang, Shuli TI - Cortico-Cortical Evoked Potentials in Children With Tuberous Sclerosis Complex Using Stereo-Electroencephalography JF - FRONTIERS IN NEUROLOGY J2 - FRONT NEUR VL - 10 PY - 2019 PG - 8 SN - 1664-2295 DO - 10.3389/fneur.2019.01093 UR - https://m2.mtmt.hu/api/publication/31023487 ID - 31023487 N1 - Funding Agency and Grant Number: Brain Research Fund of Beijing Municipal Science and Technology Commission [Z171100000117014]; Chinese National Nature & Science Foundation [81771388, 81271437] Funding text: This research was supported by Brain Research Fund of Beijing Municipal Science and Technology Commission (Z171100000117014) and Chinese National Nature & Science Foundation (81771388, 81271437). The funding source was not involved in the study design, data collection and analysis, interpretation of data, and the writing of the report. AB - Objectives: Patients with tuberous sclerosis complex (TSC) present multiple cortical tubers in the brain, which are responsible for epilepsy. It is still difficult to localize the epileptogenic tuber. The value of cortico-cortical evoked potentials (CCEPs) was assessed in epileptogenic tuber localization in patients with TSC using stereo-electroencephalography (SEEG). Methods: Patients with TSC who underwent SEEG and CCEP examination in preoperative evaluation during 2014-2017 and reached postoperative seizure freedom at 1-year follow-up were enrolled in this study (n = 11). CCEPs were conducted by stimulating every two adjacent contacts of SEEG electrodes and recording on other contacts of SEEG electrodes in one epileptogenic tuber and its early-stage propagating tuber, and their perituberal cortexes in each patient. The CCEP was defined as positive when N1 and/or N2 wave presented, and then the occurrence rates of positive CCEPs were then compared among different tubers and perituberal regions. Results: Occurrence rates of positive CCEP from epileptogenic tubers to early propagating tubers and epileptogenic tubers to perituberal cortexes were 100%, which were significantly higher than the occurrence rates of CCEP between other locations. The occurrence rates of CCEP from peripheral portions of epileptogenic tubers to peripheral portions of early propagating tubers or perituberal cortexes were 100%, which were significant higher than the occurrence rates of CCEP from peripheral regions of early propagating tubers to peripheral portions of epileptogenic tubers, from the central part of early propagating tuber to central portions of epileptogenic tubers, or from perituberal cortexes to the center part of epileptogenic tubers. Conclusion: Epileptogenic tubers presented much more diffusive connectivity with other tubers and perituberal cortexes than any other connectivity relationships across propagating tubers, and the peripheral region of epileptogenic tubers presented the greatest connectivity with propagating tubers and perituberal cortexes. CCEP can be an effective tool in epileptogenic tuber localization in patients with TSC. LA - English DB - MTMT ER - TY - JOUR AU - Alarcon, Gonzalo AU - Jimenez-Jimenez, Diego AU - Valentin, Antonio AU - Martin-Lopez, David TI - Characterizing EEG Cortical Dynamics and Connectivity with Responses to Single Pulse Electrical Stimulation (SPES) JF - INTERNATIONAL JOURNAL OF NEURAL SYSTEMS J2 - INT J NEURAL SYST VL - 28 PY - 2018 IS - 6 PG - 24 SN - 0129-0657 DO - 10.1142/S0129065717500575 UR - https://m2.mtmt.hu/api/publication/27555162 ID - 27555162 LA - English DB - MTMT ER - TY - JOUR AU - Basu, Ishita AU - Crocker, Britni AU - Farnes, Kara AU - Robertson, Madeline M. AU - Paulk, Angelique C. AU - Vallejo, Deborah I. AU - Dougherty, Darin D. AU - Cash, Sydney S. AU - Eskandar, Emad N. AU - Kramer, Mark M. AU - Widge, Alik S. TI - A neural mass model to predict electrical stimulation evoked responses in human and non-human primate brain JF - JOURNAL OF NEURAL ENGINEERING J2 - J NEURAL ENG VL - 15 PY - 2018 IS - 6 PG - 16 SN - 1741-2560 DO - 10.1088/1741-2552/aae136 UR - https://m2.mtmt.hu/api/publication/30387619 ID - 30387619 N1 - Funding Agency and Grant Number: Defense Advanced Research Projects Agency (DARPA) [W911NF-14-2-0045]; Brain and Behavior Research Foundation; OneMind Institute; MGH-MIT Strategic Initiative; Harvard Brain Institute Bipolar Initiative; National Institute of Mental Health [R03 MH111320, R21 MH109722]; MGH (ECOR Scholars Fund); [K24-NS088568]; NATIONAL INSTITUTE OF MENTAL HEALTH [R21MH109722, R03MH111320] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [K24NS088568] Funding Source: NIH RePORTER Funding text: This research was partially funded by the Defense Advanced Research Projects Agency (DARPA) under Cooperative Agreement Number W911NF-14-2-0045 issued by ARO contracting office in support of DARPA's SUBNETS Program. The views, opinions, and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the US Government.; ASW further acknowledges support from the Brain and Behavior Research Foundation, OneMind Institute, MGH-MIT Strategic Initiative, Harvard Brain Institute Bipolar Initiative (supported by a gift from Kent and Liz Dauten), and the National Institute of Mental Health (R03 MH111320, R21 MH109722).; SSS and BC were partially funded by K24-NS088568 and an internal MGH funding (ECOR Scholars Fund). AB - Objective. Deep brain stimulation (DBS) is a valuable tool for ameliorating drug resistant pathologies such as movement disorders and epilepsy. DBS is also being considered for complex neuro-psychiatric disorders, which are characterized by high variability in symptoms and slow responses that hinder DBS setting optimization. The objective of this work was to develop an in silico platform to examine the effects of electrical stimulation in regions neighboring a stimulated brain region. Approach. We used the Jansen-Rit neural mass model of single and coupled nodes to simulate the response to a train of electrical current pulses at different frequencies (10-160 Hz) of the local field potential recorded in the amygdala and cortical structures in human subjects and a non-human primate. Results. We found that using a single node model, the evoked responses could be accurately modeled following a narrow range of stimulation frequencies. Including a second coupled node increased the range of stimulation frequencies whose evoked responses could be efficiently modeled. Furthermore, in a chronic recording from a non-human primate, features of the in vivo evoked response remained consistent for several weeks, suggesting that model re-parameterization for chronic stimulation protocols would be infrequent. Significance. Using a model of neural population activity, we reproduced the evoked response to cortical and subcortical stimulation in human and non-human primate. This modeling framework provides an environment to explore, safely and rapidly, a wide range of stimulation settings not possible in human brain stimulation studies. The model can be trained on a limited dataset of stimulation responses to develop an optimal stimulation strategy for an individual patient. LA - English DB - MTMT ER - TY - JOUR AU - Fox, Kieran C R AU - Foster, Brett L AU - Kucyi, Aaron AU - Daitch, Amy L AU - Parvizi, Josef TI - Intracranial Electrophysiology of the Human Default Network JF - TRENDS IN COGNITIVE SCIENCES J2 - TRENDS COGN SCI VL - 22 PY - 2018 IS - 4 SP - 307 EP - 324 PG - 18 SN - 1364-6613 DO - 10.1016/j.tics.2018.02.002 UR - https://m2.mtmt.hu/api/publication/27302990 ID - 27302990 N1 - Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States Stanford Human Intracranial Cognitive Electrophysiology Program (SHICEP), Stanford, CA, United States Departments of Neurosurgery and Neuroscience, Baylor College of Medicine, Houston, TX, United States Stanford University School of Medicine, Stanford University, Stanford, CA, United States Cited By :21 Export Date: 18 August 2020 CODEN: TCSCF Correspondence Address: Fox, K.C.R.; Stanford Human Intracranial Cognitive Electrophysiology Program (SHICEP)United States; email: kcrfox@stanford.edu LA - English DB - MTMT ER - TY - JOUR AU - Keller, Corey J AU - Huang, Yuhao AU - Herrero, Jose L AU - Fini, Maria E AU - Du, Victor AU - Lado, Fred A AU - Honey, Christopher J AU - Mehta, Ashesh D TI - Induction and Quantification of Excitability Changes in Human Cortical Networks JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 38 PY - 2018 IS - 23 SP - S384 EP - S398 PG - 15 SN - 0270-6474 DO - 10.1523/JNEUROSCI.1088-17.2018 UR - https://m2.mtmt.hu/api/publication/27555163 ID - 27555163 N1 - Department of Neurosurgery, Feinstein Institute for Medical Research, Manhasset, NY 11030, United States Department of Neurology, Hofstra Northwell School of Medicine, Feinstein Institute for Medical Research, Manhasset, NY 11030, United States Department of Psychiatry and Behavioral Sciences, Stanford, CA 94305, United States Stanford Neuroscience Institute, Stanford University, Stanford, CA 94305, United States Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94394, United States Departments of Neuroscience and Neurology, Albert Einstein College of Medicine, Bronx, NY 10461, United States Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, United States Cited By :14 Export Date: 18 August 2020 CODEN: JNRSD Correspondence Address: Keller, C.J.; Stanford University, 401 Quarry Road, United States; email: ckeller1@stanford.edu LA - English DB - MTMT ER - TY - JOUR AU - Pearce, Alan J AU - Rist, Billymo AU - Fraser, Clare L AU - Cohen, Adrian AU - Maller, Jerome J TI - Neurophysiological and cognitive impairment following repeated sports concussion injuries in retired professional rugby league players JF - BRAIN INJURY J2 - BRAIN INJURY VL - 32 PY - 2018 IS - 4 SP - 498 EP - 505 PG - 8 SN - 0269-9052 DO - 10.1080/02699052.2018.1430376 UR - https://m2.mtmt.hu/api/publication/27302993 ID - 27302993 N1 - Funding Agency and Grant Number: Smart Head Play Charity; Impact Technologies; Australian Football League and Samsung Corporation; NHMRC Funding text: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. AJP is funded, in part, by a grant from Smart Head Play Charity, and Impact Technologies; and has been previously supported by funding from the Australian Football League and Samsung Corporation. AJP has also received equipment support for research from MagVenture and AD Instruments. AC is a director of Necksafe Ltd Charity. JJM has previously been funded by a NHMRC fellowship. Other authors declare no sources of research funding. LA - English DB - MTMT ER - TY - JOUR AU - Prime, David AU - Rowlands, David AU - O'Keefe, Steven AU - Dionisio, Sasha TI - Considerations in performing and analyzing the responses of cortico-cortical evoked potentials in stereo-EEG JF - EPILEPSIA J2 - EPILEPSIA VL - 59 PY - 2018 IS - 1 SP - 16 EP - 26 PG - 11 SN - 0013-9580 DO - 10.1111/epi.13939 UR - https://m2.mtmt.hu/api/publication/27302994 ID - 27302994 LA - English DB - MTMT ER - TY - JOUR AU - Raccah, Omri AU - Daitch, Amy L. AU - Kucyi, Aaron AU - Parvizi, Josef TI - Direct Cortical Recordings Suggest Temporal Order of Task-Evoked Responses in Human Dorsal Attention and Default Networks JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 38 PY - 2018 IS - 48 SP - 10305 EP - 10313 PG - 9 SN - 0270-6474 DO - 10.1523/JNEUROSCI.0079-18.2018 UR - https://m2.mtmt.hu/api/publication/30387617 ID - 30387617 N1 - Funding Agency and Grant Number: US National Institute of Mental Health [1R01-MH-109954-01]; Banting Fellowship from the Canadian Institutes of Health Research; National Institute of Child Health and Human Development [1F32HD087028-01]; EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [F32HD087028] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH109954] Funding Source: NIH RePORTER Funding text: 1F32HD087028-01 This project was funded by US National Institute of Mental Health (Grant 1R01-MH-109954-01; to J.P.), the Banting Fellowship from the Canadian Institutes of Health Research (A.K.), and a Postdoctoral Fellowship (1F32HD087028-01) from the National Institute of Child Health and Human Development (A.L.D.). We thank J. Schrouff for assisting with the development of the signal-processing techniques, A. Areti for contributing to the creation of the figures, and other Laboratory of Behavioral and Cognitive Neuroscience members for assistance and input throughout this study. The iEEG preprocessing codes for this project are publicly available at https://github.com/LBCN-Stanford/Preprocessing_pipeline. AB - The past decade has seen a large number of neuroimaging studies focused on the anticorrelated functional relationship between the default mode network (DMN) and the dorsal attention network (DAN). Due principally to the low temporal resolution of functional neuroimaging modalities, the fast-neuronal dynamics across these networks remain poorly understood. Here we report novel human intracranial electrophysiology data from six neurosurgical patients ( four males) with simultaneous coverage of well characterized nodes of the DMN and DAN. Subjects performed an arithmetic processing task, shown previously to evoke reliable deactivations (below baseline) in the DMN, and activations in the DAN. In this cohort, we show that DMN deactivations lag DAN activations by approximately 200 ms. Our findings suggest a clear temporal order of processing across the two networks during the current task and place the DMN further than the DAN in a plausible information-processing hierarchy. LA - English DB - MTMT ER - TY - JOUR AU - Rolston, John D. AU - Chang, Edward F. TI - Critical Language Areas Show Increased Functional Connectivity in Human Cortex JF - CEREBRAL CORTEX J2 - CEREB CORTEX VL - 28 PY - 2018 IS - 12 SP - 4161 EP - 4168 PG - 8 SN - 1047-3211 DO - 10.1093/cercor/bhx271 UR - https://m2.mtmt.hu/api/publication/30387609 ID - 30387609 N1 - Funding Agency and Grant Number: National Institute on Deafness and Other Communication Disorders [1F32DC013953-01] Funding text: J.D.R. was supported by a fellowship from the National Institute on Deafness and Other Communication Disorders (1F32DC013953-01). AB - Electrocortical stimulation (ECS) mapping is routinely used to identify critical language sites before resective neurosurgery. The precise locations of these sites are highly variable across patients, occurring in the frontal, temporal, and parietal lobes-it is this variability that necessitates individual patient mapping. But why these particular anatomical sites are so privileged in each patient is unknown. We hypothesized that critical language sites have greater functional connectivity with nearby cortex than sites without critical functions, since they serve as central nodes within the language network. Functional connectivity across language, motor, and cleared sites was measured in 15 patients undergoing electrocortiographic (ECoG) mapping for epilepsy surgery. Critical language sites had significantly higher connectivity than sites without critical functions (P = 0.001), and this also held for motor sites (P = 0.022). These data support the hypothesis that critical language sites are highly connected within the local cortical network, perhaps explaining why their disruption with ECS leads to transient disturbances in language function. It is our hope that improved understanding of the mechanisms of ECS will permit improved surgical planning and perhaps contribute to the understanding of normal language physiology. LA - English DB - MTMT ER - TY - JOUR AU - Shafi, Reema TI - Understanding the Hierarchical Organization of Large-Scale Networks Based on Temporal Modulations in Patterns of Neural Connectivity JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 38 PY - 2018 IS - 13 SP - 3154 EP - 3156 PG - 3 SN - 0270-6474 DO - 10.1523/JNEUROSCI.3503-17.2018 UR - https://m2.mtmt.hu/api/publication/27302991 ID - 27302991 LA - English DB - MTMT ER - TY - JOUR AU - Trebaul, Lena AU - Deman, Pierre AU - Tuyisenge, Viateur AU - Jedynak, Maciej AU - Hugues, Etienne AU - Rudrauf, David AU - Bhattacharjee, Manik AU - Tadel, Francois AU - Chanteloup-Foret, Blandine AU - Saubat, Carole AU - Mejia, Gina Catalina Reyes AU - Adam, Claude AU - Nica, Anca AU - Pail, Martin AU - Dubeau, Francois AU - Rheims, Sylvain AU - Trebuchon, Agnes AU - Wang, Haixiang AU - Liu, Sinclair AU - Blauwblomme, Thomas AU - Garces, Mercedes AU - De Palma, Luca AU - Valentin, Antonio AU - Metsahonkala, Eeva-Liisa AU - Petrescu, Ana Maria AU - Landre, Elizabeth AU - Szurhaj, William AU - Hirsch, Edouard AU - Valton, Luc AU - Rocamora, Rodrigo AU - Schulze-Bonhage, Andreas AU - Mindruta, Ioana AU - Francione, Stefano AU - Maillard, Louis AU - Taussig, Delphine AU - Kahane, Philippe AU - David, Olivier TI - Probabilistic functional tractography of the human cortex revisited JF - NEUROIMAGE J2 - NEUROIMAGE VL - 181 PY - 2018 SP - 414 EP - 429 PG - 16 SN - 1053-8119 DO - 10.1016/j.neuroimage.2018.07.039 UR - https://m2.mtmt.hu/api/publication/30387610 ID - 30387610 N1 - Inserm, U1216, Grenoble, F-38000, France Univ. Grenoble Alpes, Grenoble Institut des Neurosciences, GIN, Grenoble, F-38000, France Epilepsy Unit, Dept of Neurology, Pitié-Salpêtrière Hospital, APHP, Paris, France Neurology Department, CHU, Rennes, France Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic Montreal Neurological Institute and Hospital, Montreal, Canada Department of Functional Neurology and Epileptology, Hospices Civils de Lyon and University of Lyon, Lyon, France Service de Neurophysiologie Clinique, APHM, Hôpitaux de la Timone, Marseille, France Yuquan Hospital Epilepsy Center, Tsinghua University, Beijing, China Canton Sanjiu Brain Hospital Epilepsy Center, Jinan University, Guangzhou, China Department of Pediatric Neurosurgery, Hôpital Necker-Enfants Malades, Université Paris V Descartes, Sorbonne Paris Cité, Paris, France Multidisciplinary Epilepsy Unit, Hospital Universitario y Politécnico La Fe, Valencia, Spain Department of Neuroscience, Bambino Gesù Children's Hospital, IRRCS, Rome, Italy Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, United Kingdom Epilepsy Unit, Hospital for Children and Adolescents, Helsinki, Finland Neurophysiology and Epilepsy Unit, Bicêtre Hospital, France Department of Neurosurgery, Sainte-Anne Hospital, Paris, France Epilepsy Unit, Department of Clinical Neurophysiology, Lille University Medical Center, Lille, France University Hospital, Department of Neurology, Strasbourg, France University Hospital, Department of Neurology, Toulouse, France Epilepsy Monitoring Unit, Department of Neurology, Hospital del Mar-IMIM, Barcelona, Spain Epilepsy Center, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Germany Neurology Department, University Emergency Hospital, Bucharest, Romania Epilepsy Surgery Center Niguarda Hospital, Milan, Italy Centre Hospitalier Universitaire de Nancy, Nancy, France Service de neurochirurgie pédiatrique, Fondation Rothschild, Paris, France CHU Grenoble Alpes, Neurology Department, Grenoble, France Cited By :16 Export Date: 18 August 2020 CODEN: NEIME Correspondence Address: David, O.; Grenoble Institut des Neurosciences, Chemin Fortuné Ferrini, Bât EJ Safra, France; email: Olivier.David@inserm.fr AB - In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human. LA - English DB - MTMT ER - TY - JOUR AU - Tuyisenge, Viateur AU - Trebaul, Lena AU - Bhattacharjee, Manik AU - Chanteloup-Foret, Blandine AU - Saubat-Guigui, Carole AU - Mindruta, Ioana AU - Rheims, Sylvain AU - Maillard, Louis AU - Kahane, Philippe AU - Taussig, Delphine AU - David, Olivier TI - Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning JF - CLINICAL NEUROPHYSIOLOGY J2 - CLIN NEUROPHYSIOL VL - 129 PY - 2018 IS - 3 SP - 548 EP - 554 PG - 7 SN - 1388-2457 DO - 10.1016/j.clinph.2017.12.013 UR - https://m2.mtmt.hu/api/publication/27302992 ID - 27302992 N1 - Funding Agency and Grant Number: European Research Council under the European Union's Seventh Framework Programme/ERC [616268 F-TRACT]; Romanian UEFISCDI [PN-II-ID-PCE-2011-3-0240]; Grenoble-Alpes University Hospital (EPISTIM study) [DRCI 1325] Funding text: The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. 616268 F-TRACT. This work was also funded by Romanian UEFISCDI Grant PN-II-ID-PCE-2011-3-0240, and by a Grenoble-Alpes University Hospital grant (DRCI 1325, EPISTIM study). LA - English DB - MTMT ER - TY - JOUR AU - van Blooijs, Dorien AU - Leijten, Frans S. S. AU - van Rijen, Peter C. AU - Meijer, Hil G. E. AU - Huiskamp, Geertjan J. M. TI - Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation JF - HUMAN BRAIN MAPPING J2 - HUM BRAIN MAPP VL - 39 PY - 2018 IS - 11 SP - 4611 EP - 4622 PG - 12 SN - 1065-9471 DO - 10.1002/hbm.24309 UR - https://m2.mtmt.hu/api/publication/30387618 ID - 30387618 N1 - Funding Agency and Grant Number: Epilepsy Foundation [17-07]; Dutch Epilepsy Foundation [95104015]; National Dutch Science Foundation ZonMW Funding text: Epilepsy Foundation, Grant/Award Number: #17-07; Dutch Epilepsy Foundation, Grant/Award Number: 95104015; National Dutch Science Foundation ZonMW AB - We investigated effective networks constructed from single pulse electrical stimulation (SPES) in epilepsy patients who underwent intracranial electrocorticography. Using graph analysis, we compared network characteristics of tissue within and outside the epileptogenic area. In 21 patients with subdural electrode grids (1 cm interelectrode distance), we constructed a binary, directional network derived from SPES early responses (<100 ms). We calculated in-degree, out-degree, betweenness centrality, the percentage of bidirectional, receiving and activating connections, and the percentage of connections toward the (non-)epileptogenic tissue for each node in the network. We analyzed whether these network measures were significantly different in seizure onset zone (SOZ)-electrodes compared to non-SOZ electrodes, in resected area (RA)-electrodes compared to non-RA electrodes, and in seizure free compared to not seizure-free patients. Electrodes in the SOZ/RA showed significantly higher values for in-degree and out-degree, both at group level, and at patient level, and more so in seizure-free patients. These differences were not observed for betweenness centrality. There were also more bidirectional and fewer receiving connections in the SOZ/RA in seizure-free patients. It appears that the SOZ/RA is densely connected with itself, with only little input arriving from non-SOZ/non-RA electrodes. These results suggest that meso-scale effective network measures are different in epileptogenic compared to normal brain tissue. Local connections within the SOZ/RA are increased and the SOZ/RA is relatively isolated from the surrounding cortex. This offers the prospect of enhanced prediction of epilepsy-prone brain areas using SPES. LA - English DB - MTMT ER - TY - JOUR AU - Waters, Allison C. AU - Veerakumar, Ashan AU - Choi, Ki Sueng AU - Howell, Bryan AU - Tiruvadi, Vineet AU - Bijanki, Kelly R. AU - Crowell, Andrea AU - Riva-Posse, Patricio AU - Mayberg, Helen S. TI - Test-retest reliability of a stimulation-locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression JF - HUMAN BRAIN MAPPING J2 - HUM BRAIN MAPP VL - 39 PY - 2018 IS - 12 SP - 4844 EP - 4856 PG - 13 SN - 1065-9471 DO - 10.1002/hbm.24327 UR - https://m2.mtmt.hu/api/publication/30387613 ID - 30387613 N1 - Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States Cited By :5 Export Date: 18 August 2020 CODEN: HBMAE Correspondence Address: Waters, A.C.; Department of Psychiatry and Behavioral Sciences, Emory University School of MedicineUnited States; email: alliwaters@emory.edu AB - Deep brain stimulation (DBS) to the subcallosal cingulate cortex (SCC) is an emerging therapy for treatment resistant depression. Precision targeting of specific white matter fibers is now central to the model of SCC DBS treatment efficacy. A method to confirm SCC DBS target engagement is needed to reduce procedural variance across treatment providers and to optimize DBS parameters for individual patients. We examined the reliability of a novel cortical evoked response that is time-locked to a 2 Hz DBS pulse and shows the propagation of signal from the DBS target. The evoked response was detected in four individuals as a stereotyped series of components within 150 ms of a 6 V DBS pulse, each showing coherent topography on the head surface. Test-retest reliability across four repeated measures over 14 months met or exceeded standards for valid test construction in three of four patients. Several observations in this pilot sample demonstrate the prospective utility of this method to confirm surgical target engagement and instruct parameter selection. The topography of an orbital frontal component on the head surface showed specificity for patterns of forceps minor activation, which may provide a means to confirm DBS location with respect to key white matter structures. A divergent cortical response to unilateral stimulation of left (vs. right) hemisphere underscores the need for feedback acuity on the level of a single electrode, despite bilateral presentation of therapeutic stimulation. Results demonstrate viability of this method to explore patient-specific cortical responsivity to DBS for brain-circuit pathologies. LA - English DB - MTMT ER - TY - JOUR AU - Zanos, Stavros AU - Rembado, Irene AU - Chen, Daofen AU - Fetz, Eberhard E. TI - Phase-Locked Stimulation during Cortical Beta Oscillations Produces Bidirectional Synaptic Plasticity in Awake Monkeys JF - CURRENT BIOLOGY J2 - CURR BIOL VL - 28 PY - 2018 IS - 16 SP - 2515 EP - + PG - 16 SN - 0960-9822 DO - 10.1016/j.cub.2018.07.009 UR - https://m2.mtmt.hu/api/publication/30387621 ID - 30387621 N1 - Funding Agency and Grant Number: National Institutes of Health [NS12542, RR 00166]; NATIONAL CENTER FOR RESEARCH RESOURCES [P51RR000166] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R37NS012542, R01NS012542] Funding Source: NIH RePORTER Funding text: The authors would like thank Larry Shupe for programming assistance and Rebekah Schaefer and Olivia Robinson for assistance with animals. This work was supported by the National Institutes of Health (NS12542 and RR 00166). AB - The functional role of cortical beta oscillations, if any, remains unresolved. During oscillations, the periodic fluctuation in excitability of entrained cells modulates transmission of neural impulses and periodically enhances synaptic interactions. The extent to which oscillatory episodes affect activity-dependent synaptic plasticity remains to be determined. In nonhuman primates, we delivered single-pulse electrical cortical stimulation to a "stimulated'' site in sensorimotor cortex triggered on a specific phase of ongoing beta (12-25 Hz) field potential oscillations recorded at a separate "triggering'' site. Corticocortical connectivity from the stimulated to the triggering site as well as to other (non-triggering) sites was assessed by cortically evoked potentials elicited by test stimuli to the stimulated site, delivered outside of oscillatory episodes. In separate experiments, connectivity was assessed by intracellular recordings of evoked excitatory postsynaptic potentials. The conditioning paradigm produced transient (1-2 s long) changes in connectivity between the stimulated and the triggering site that outlasted the duration of the oscillatory episodes. The direction of the plasticity effect depended on the phase from which stimulation was triggered: potentiation in depolarizing phases, depression in hyperpolarizing phases. Plasticity effects were also seen at non-triggering sites that exhibited oscillations synchronized with those at the triggering site. These findings indicate that cortical beta oscillations provide a spatial and temporal substrate for short-term, activity-dependent synaptic plasticity in primate neocortex and may help explain the role of oscillations in attention, learning, and cortical reorganization. LA - English DB - MTMT ER - TY - JOUR AU - Zhang, Nan AU - Zhang, Bingqing AU - Rajah, Gary B. AU - Geng, Xiaokun AU - Singh, Rasanjeet AU - Yang, Yanfeng AU - Yan, Xiupeng AU - Li, Zhe AU - Zhou, Wenjing AU - Ding, Yuchuan AU - Sun, Wei TI - The effectiveness of cortico-cortical evoked potential in detecting seizure onset zones JF - NEUROLOGICAL RESEARCH J2 - NEUROL RES VL - 40 PY - 2018 IS - 6 SP - 480 EP - 490 PG - 11 SN - 0161-6412 DO - 10.1080/01616412.2018.1454092 UR - https://m2.mtmt.hu/api/publication/30387620 ID - 30387620 N1 - Funding Agency and Grant Number: National Natural Science Foundation of China [81571267]; capital health research and development of special [2016-2-2013] Funding text: This work was supported by National Natural Science Foundation of China [grant number 81571267] and the capital health research and development of special (2016-2-2013). AB - Objective:The aim of the study was to evaluate the parameters for localizing the seizure onset zone in refractory epilepsy patients using cortico-cortical evoked potentials (CCEP). LA - English DB - MTMT ER - TY - JOUR AU - Boly, Melanie AU - Massimini, Marcello AU - Tsuchiya, Naotsugu AU - Postle, Bradley R AU - Koch, Christof AU - Tononi, Giulio TI - Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 37 PY - 2017 IS - 40 SP - 9603 EP - 9613 PG - 11 SN - 0270-6474 DO - 10.1523/JNEUROSCI.3218-16.2017 UR - https://m2.mtmt.hu/api/publication/26910907 ID - 26910907 N1 - Funding Agency and Grant Number: National Institutes of Health Grant [1R03NS096379, MH095984]; James S. McDonnell Scholar Award; H-FETOPEN-RIA [686764]; Templeton World Charity Foundation; Tiny Blue Dot Foundation; Distinguished Chair in Consciousness Science (University of Wisconsin); NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH095984, R01MH064498] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R03NS096379] Funding Source: NIH RePORTER Funding text: This work was supported by National Institutes of Health Grant 1R03NS096379 to M.B., the James S. McDonnell Scholar Award 2013 and the H2020-FETOPEN-2014-2015-RIA under agreement No. 686764 (Luminous Project) to M.M., the Templeton World Charity Foundation to N.T., National Institutes of Health Grant MH095984 to B.R.P., and the Tiny Blue Dot Foundation and the Distinguished Chair in Consciousness Science (University of Wisconsin) to G.T. LA - English DB - MTMT ER - TY - JOUR AU - Chapeton, Julio I AU - Inati, Sara K AU - Zaghloul, Kareem A TI - Stable functional networks exhibit consistent timing in the human brain JF - BRAIN J2 - BRAIN VL - 140 PY - 2017 SP - 628 EP - 640 PG - 13 SN - 0006-8950 DO - 10.1093/brain/aww337 UR - https://m2.mtmt.hu/api/publication/26556208 ID - 26556208 N1 - Funding Agency and Grant Number: National Institutes of Health; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [ZIANS003144] Funding Source: NIH RePORTER Funding text: This work was supported by the Intramural Research Program at the National Institutes of Health. The authors declare no competing financial interests. Part number: 3 LA - English DB - MTMT ER - TY - CHAP AU - Donos, Cristian AU - Barborica, Andrei AU - Mindruta, Ioana AU - Maliia, Mihai AU - Popa, Irina AU - Ciurea, Jean ED - Opris, I ED - Casanova, M TI - Connectomics in Patients with Temporal Lobe Epilepsy T2 - THE PHYSICS OF THE MIND AND BRAIN DISORDERS PB - Springer Netherlands CY - Cham SN - 9783319296722 T3 - Springer Series in Cognitive and Neural Systems ; Vol. 11. PY - 2017 SP - 447 EP - 468 PG - 22 DO - 10.1007/978-3-319-29674-6_20 UR - https://m2.mtmt.hu/api/publication/31406154 ID - 31406154 LA - English DB - MTMT ER -