TY - JOUR AU - Csukly, Gábor AU - Szabó, Ádám György AU - Polgár, Patrícia AU - Farkas, Kinga AU - Gyebnár, Gyula AU - Kozák, Lajos Rudolf AU - Stefanics, Gábor TI - Fronto-thalamic structural and effective connectivity and delusions in schizophrenia: a combined DTI/DCM study JF - PSYCHOLOGICAL MEDICINE J2 - PSYCHOL MED VL - 51 PY - 2021 IS - 12 SP - 2083 EP - 2093 PG - 11 SN - 0033-2917 DO - 10.1017/S0033291720000859 UR - https://m2.mtmt.hu/api/publication/31292551 ID - 31292551 AB - Schizophrenia (SZ) is a complex disorder characterized by a range of behavioral and cognitive symptoms as well as structural and functional alterations in multiple cortical and subcortical structures. SZ is associated with reduced functional network connectivity involving core regions such as the anterior cingulate cortex (ACC) and the thalamus. However, little is known whether effective coupling, the directed influence of one structure over the other, is altered during rest in the ACC-thalamus network.We collected resting-state fMRI and diffusion-weighted MRI data from 18 patients and 20 healthy controls. We analyzed fronto-thalamic effective connectivity using dynamic causal modeling for cross-spectral densities in a network consisting of the ACC and the left and right medio-dorsal thalamic regions. We studied structural connectivity using fractional anisotropy (FA).We found decreased coupling strength from the right thalamus to the ACC and from the right thalamus to the left thalamus, as well as increased inhibitory intrinsic connectivity in the right thalamus in patients relative to controls. ACC-to-left thalamus coupling strength correlated with the Positive and Negative Syndrome Scale (PANSS) total positive syndrome score and with delusion score. Whole-brain structural analysis revealed several tracts with reduced FA in patients, with a maximum decrease in white matter tracts containing fronto-thalamic and cingulo-thalamic fibers.We found altered effective and structural connectivity within the ACC-thalamus network in SZ. Our results indicate that ACC-thalamus network activity at rest is characterized by reduced thalamus-to-ACC coupling. We suggest that positive symptoms may arise as a consequence of compensatory measures to imbalanced fronto-thalamic coupling. LA - English DB - MTMT ER - TY - JOUR AU - Stefanics, Gábor AU - Heinzle, J. AU - Czigler, István AU - Valentini, E. AU - Stephan, K.E. TI - Timing of repetition suppression of event-related potentials to unattended objects JF - EUROPEAN JOURNAL OF NEUROSCIENCE J2 - EUR J NEUROSCI VL - 52 PY - 2020 IS - 11 SP - 4432 EP - 4441 PG - 10 SN - 0953-816X DO - 10.1111/ejn.13972 UR - https://m2.mtmt.hu/api/publication/30385584 ID - 30385584 N1 - First published:26 May 2018 LA - English DB - MTMT ER - TY - JOUR AU - Stephan, K E AU - Petzschner, F H AU - Kasper, L AU - Bayer, J AU - Wellstein, K V AU - Stefanics, Gábor AU - Pruessmann, K P AU - Heinzle, J TI - Laminar fMRI and computational theories of brain function. JF - NEUROIMAGE J2 - NEUROIMAGE VL - 197 PY - 2019 SP - 699 EP - 706 PG - 8 SN - 1053-8119 DO - 10.1016/j.neuroimage.2017.11.001 UR - https://m2.mtmt.hu/api/publication/31309071 ID - 31309071 N1 - Journal Article; Research Support, Non-U.S. Gov't; Review AB - Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. LA - English DB - MTMT ER - TY - JOUR AU - Manjaly, Zina-Mary AU - Harrison, Neil A. AU - Critchley, Hugo D. AU - Do, Cao Tri AU - Stefanics, Gábor AU - Wenderoth, Nicole AU - Lutterotti, Andreas AU - Mueller, Alfred AU - Stephan, Klaas Enno TI - Pathophysiological and cognitive mechanisms of fatigue in multiple sclerosis JF - JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY J2 - J NEUROL NEUROSUR PS VL - 90 PY - 2019 IS - 6 SP - 642 EP - 651 PG - 10 SN - 0022-3050 DO - 10.1136/jnnp-2018-320050 UR - https://m2.mtmt.hu/api/publication/30795555 ID - 30795555 N1 - Cited By :8 Export Date: 20 April 2020 CODEN: JNNPA Correspondence Address: Manjaly, Z.-M.; Department of Neurology, Schulthess ClinicSwitzerland; email: zina-mary.manjaly@kws.ch Chemicals/CAS: amantadine, 665-66-7, 768-94-5; glatiramer, 147245-92-9, 28704-27-0; modafinil, 68693-11-8; natalizumab, 189261-10-7 Funding details: Universität Zürich, UZH Funding text 1: The immune system plays a key role in aetiology and progression of MS.2 3 69 In general, immunological processes in the CNS and the body can interact through multiple pathways.70 71 In MS, the relative contributions of central and peripheral immunological events during the induction and early inflammatory phase of MS are not fully understood. In particular, it remains to be clarified whether a primary immunological process takes place in the brain and spreads to the periphery or whether immune activation begins peripherally before being transferred to the initially unaffected CNS (for review, see69). The latter possibility is supported by the fact that highly effective immunomodulatory treatments for MS (eg, fingolimod, rituximab) have peripheral targets. Regardless of where the initial immune response occurred, myelin damage in the CNS is thought to lead to the release of antigens to the periphery.2 This, in turn, primes immune responses in lymphoid tissue and triggers the invasion of lymphocytes into the CNS.2 While peripheral immune responses may be the driving force at the early stage of MS, evidence suggests that later in the disease, the immune response is shifted and compartmentalised to the CNS in lymphoid-like follicles in the meninges that maintain chronic inflammation.72 Funding text 2: Acknowledgements we gratefully acknowledge support by the wilhelm-Schulthess Foundation, René and Susanne Braginsky Foundation, the University of Zurich and the Clinical Research Priority Program Multiple Sclerosis from the University of Zurich and the University Hospital of Zurich. Journal Article; Research Support, Non-U.S. Gov't; Review AB - Fatigue is one of the most common symptoms in multiple sclerosis (MS), with a major impact on patients' quality of life. Currently, treatment proceeds by trial and error with limited success, probably due to the presence of multiple different underlying mechanisms. Recent neuroscientific advances offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. However, development of these tools for differential diagnosis will require guidance by pathophysiological and cognitive theories that propose mechanisms which can be assessed in individual patients. This article provides an overview of contemporary pathophysiological theories of fatigue in MS and discusses how the mechanisms they propose may become measurable with emerging technologies and thus lay a foundation for future personalised treatments. LA - English DB - MTMT ER - TY - JOUR AU - Stefanics, Gábor AU - Stephan, Klaas Enno AU - Heinzle, Jakob TI - Feature-specific prediction errors for visual mismatch JF - NEUROIMAGE J2 - NEUROIMAGE VL - 196 PY - 2019 SP - 142 EP - 151 PG - 10 SN - 1053-8119 DO - 10.1016/j.neuroimage.2019.04.020 UR - https://m2.mtmt.hu/api/publication/30725979 ID - 30725979 AB - Predictive coding (PC) theory posits that our brain employs a predictive model of the environment to infer the causes of its sensory inputs. A fundamental but untested prediction of this theory is that the same stimulus should elicit distinct precision weighted prediction errors (pwPEs) when different (feature-specific) predictions are violated, even in the absence of attention. Here, we tested this hypothesis using functional magnetic resonance imaging (fMRI) and a multi-feature roving visual mismatch paradigm where rare changes in either color (red, green), or emotional expression (happy, fearful) of faces elicited pwPE responses in human participants. Using a computational model of learning and inference, we simulated pwPE and prediction trajectories of a Bayes-optimal observer and used these to analyze changes in blood oxygen level dependent (BOLD) responses to changes in color and emotional expression of faces while participants engaged in a distractor task. Controlling for visual attention by eye-tracking, we found pwPE responses to unexpected color changes in the fusiform gyrus. Conversely, unexpected changes of facial emotions elicited pwPE responses in cortico-thalamo-cerebellar structures associated with emotion and theory of mind processing. Predictions pertaining to emotions activated fusiform, occipital and temporal areas. Our results are consistent with a general role of PC across perception, from low-level to complex and socially relevant object features, and suggest that monitoring of the social environment occurs continuously and automatically, even in the absence of attention. LA - English DB - MTMT ER - TY - BOOK AU - Weber, Lilian AU - Diaconescu, Andreea AU - Tomiello, Sara AU - Schöbi, Dario AU - Iglesias, Sandra AU - Mathys, Christoph AU - Haker, Helene AU - Stefanics, Gábor AU - Schmidt, André AU - Kometer, Michael AU - Vollenweider, Franz X AU - Stephan, Klaas Enno TI - F157. HIERARCHICAL PREDICTION ERRORS DURING AUDITORY MISMATCH UNDER PHARMACOLOGICAL MANIPULATIONS: A COMPUTATIONAL SINGLE-TRIAL EEG ANALYSIS PY - 2018 DO - 10.1093/schbul/sby017.688 UR - https://m2.mtmt.hu/api/publication/31310801 ID - 31310801 LA - English DB - MTMT ER - TY - JOUR AU - Xu, Qianru AU - Ruohonen, Elisa M AU - Ye, Chaoxiong AU - Li, Xueqiao AU - Kreegipuu, Kairi AU - Stefanics, Gábor AU - Luo, Wenbo AU - Astikainen, Piia TI - Automatic Processing of Changes in Facial Emotions in Dysphoria. A Magnetoencephalography Study. TS - A Magnetoencephalography Study. JF - FRONTIERS IN HUMAN NEUROSCIENCE J2 - FRONT HUM NEUROSCI VL - 12 PY - 2018 SP - 186 SN - 1662-5161 DO - 10.3389/fnhum.2018.00186 UR - https://m2.mtmt.hu/api/publication/31309070 ID - 31309070 AB - It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck's Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria. LA - English DB - MTMT ER - TY - JOUR AU - Stefanics, Gábor AU - Heinzle, Jakob AU - Horváth, András Attila AU - Stephan, Klaas TI - Visual Mismatch and Predictive Coding: A Computational Single-Trial ERP Study JF - JOURNAL OF NEUROSCIENCE J2 - J NEUROSCI VL - 38 PY - 2018 IS - 16 SP - 4020 EP - 4030 PG - 11 SN - 0270-6474 DO - 10.1523/JNEUROSCI.3365-17.2018 UR - https://m2.mtmt.hu/api/publication/3394936 ID - 3394936 N1 - Funding Agency and Grant Number: University of Zurich; Rene and Susanne Braginsky Foundation; Clinical Research Priority Program "Multiple Sclerosis" Funding text: We acknowledge support by the University of Zurich (K.E.S.), the Rene and Susanne Braginsky Foundation (K.E.S.), and the Clinical Research Priority Program "Multiple Sclerosis" (G.S., K.E.S.). AB - Predictive coding (PC) posits that the brain uses a generative model to infer the environmental causes of its sensory data and uses precision-weighted prediction errors (pwPEs) to continuously update this model. While supported by much circumstantial evidence, experimental tests grounded in formal trial-by-trial predictions are rare. One partial exception is event-related potential (ERP) studies of the auditory mismatch negativity (MMN), where computational models have found signatures of pwPEs and related model-updating processes. Here, we tested this hypothesis in the visual domain, examining possible links between visual mismatch responses and pwPEs. We used a novel visual "roving standard" paradigm to elicit mismatch responses in humans (of both sexes) by unexpected changes in either color or emotional expression of faces. Using a hierarchical Bayesian model, we simulated pwPE trajectories of a Bayes-optimal observer and used these to conduct a comprehensive trial-by-trial analysis across the time x sensor space. We found significant modulation of brain activity by both color and emotion pwPEs. The scalp distribution and timing of these single-trial pwPE responses were in agreement with visual mismatch responses obtained by traditional averaging and subtraction (deviant-minus-standard) approaches. Finally, we compared the Bayesian model to a more classical change model of MMN. Model comparison revealed that trial-wise pwPEs explained the observed mismatch responses better than categorical change detection. Our results suggest that visual mismatch responses reflect trial-wise pwPEs, as postulated by PC. These findings go beyond classical ERP analyses of visual mismatch and illustrate the utility of computational analyses for studying automatic perceptual processes.SIGNIFICANCE STATEMENT Human perception is thought to rely on a predictive model of the environment that is updated via precision-weighted prediction errors (pwPEs) when events violate expectations. This "predictive coding" view is supported by studies of the auditory mismatch negativity brain potential. However, it is less well known whether visual perception of mismatch relies on similar processes. Here we combined computational modeling and electroencephalography to test whether visual mismatch responses reflected trial-by-trial pwPEs. Applying a Bayesian model to series of face stimuli that violated expectations about color or emotional expression, we found significant modulation of brain activity by both color and emotion pwPEs. A categorical change detection model performed less convincingly. Our findings support the predictive coding interpretation of visual mismatch responses. LA - English DB - MTMT ER - TY - JOUR AU - Horváth, András Attila AU - Szűcs, Anna AU - Csukly, Gábor AU - Sákovics, Anna AU - Stefanics, Gábor AU - Kamondi, Anita TI - EEG and ERP biomarkers of Alzheimer's disease: a critical review JF - FRONTIERS IN BIOSCIENCE-LANDMARK J2 - FRONT BIOSCI-LANDMARK VL - 23 PY - 2018 IS - 2 SP - 183 EP - 220 PG - 38 SN - 2768-6701 DO - 10.2741/4587 UR - https://m2.mtmt.hu/api/publication/3282565 ID - 3282565 AB - Here we critically review studies that used electroencephalography (EEG) or event-related potential (ERP) indices as a biomarker of Alzheimer's disease. In the first part we overview studies that relied on visual inspection of EEG traces and spectral characteristics of EEG. Second, we survey analysis methods motivated by dynamical systems theory (DST) as well as more recent network connectivity approaches. In the third part we review studies of sleep. Next, we compare the utility of early and late ERP components in dementia research. In the section on mismatch negativity (MMN) studies we summarize their results and limitations and outline the emerging field of computational neurology. In the following we overview the use of EEG in the differential diagnosis of the most common neurocognitive disorders. Finally, we provide a summary of the state of the field and conclude that several promising EEG/ERP indices of synaptic neurotransmission are worth considering as potential biomarkers. Furthermore, we highlight some practical issues and discuss future challenges as well. LA - English DB - MTMT ER - TY - JOUR AU - Stefanics, Gábor TI - Computational Modeling of Mismatch Negativity (MMN) JF - PSYCHOPHYSIOLOGY J2 - PSYCHOPHYSIOLOGY VL - 54 PY - 2017 SP - S9 EP - S10 SN - 0048-5772 DO - 10.1111/psyp.12925 UR - https://m2.mtmt.hu/api/publication/31311240 ID - 31311240 LA - English DB - MTMT ER -