@article{MTMT:31292551, title = {Fronto-thalamic structural and effective connectivity and delusions in schizophrenia: a combined DTI/DCM study}, url = {https://m2.mtmt.hu/api/publication/31292551}, author = {Csukly, Gábor and Szabó, Ádám György and Polgár, Patrícia and Farkas, Kinga and Gyebnár, Gyula and Kozák, Lajos Rudolf and Stefanics, Gábor}, doi = {10.1017/S0033291720000859}, journal-iso = {PSYCHOL MED}, journal = {PSYCHOLOGICAL MEDICINE}, volume = {51}, unique-id = {31292551}, issn = {0033-2917}, abstract = {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.}, keywords = {SCHIZOPHRENIA; Connectivity; DCM; Thalamus; delusion; PANSS; DTI; PEB; Anterior cingulum}, year = {2021}, eissn = {1469-8978}, pages = {2083-2093}, orcid-numbers = {Csukly, Gábor/0000-0002-5006-9407; Szabó, Ádám György/0000-0003-4014-3762; Farkas, Kinga/0000-0002-1125-3957; Gyebnár, Gyula/0000-0003-0368-3663; Kozák, Lajos Rudolf/0000-0003-0368-3663} } @article{MTMT:30385584, title = {Timing of repetition suppression of event-related potentials to unattended objects}, url = {https://m2.mtmt.hu/api/publication/30385584}, author = {Stefanics, Gábor and Heinzle, J. and Czigler, István and Valentini, E. and Stephan, K.E.}, doi = {10.1111/ejn.13972}, journal-iso = {EUR J NEUROSCI}, journal = {EUROPEAN JOURNAL OF NEUROSCIENCE}, volume = {52}, unique-id = {30385584}, issn = {0953-816X}, year = {2020}, eissn = {1460-9568}, pages = {4432-4441} } @article{MTMT:31309071, title = {Laminar fMRI and computational theories of brain function.}, url = {https://m2.mtmt.hu/api/publication/31309071}, author = {Stephan, K E and Petzschner, F H and Kasper, L and Bayer, J and Wellstein, K V and Stefanics, Gábor and Pruessmann, K P and Heinzle, J}, doi = {10.1016/j.neuroimage.2017.11.001}, journal-iso = {NEUROIMAGE}, journal = {NEUROIMAGE}, volume = {197}, unique-id = {31309071}, issn = {1053-8119}, abstract = {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.}, keywords = {Predictive coding; Effective connectivity; cortical layers; Computational psychiatry; Computational psychosomatics; Neuromodeling}, year = {2019}, eissn = {1095-9572}, pages = {699-706} } @article{MTMT:30795555, title = {Pathophysiological and cognitive mechanisms of fatigue in multiple sclerosis}, url = {https://m2.mtmt.hu/api/publication/30795555}, author = {Manjaly, Zina-Mary and Harrison, Neil A. and Critchley, Hugo D. and Do, Cao Tri and Stefanics, Gábor and Wenderoth, Nicole and Lutterotti, Andreas and Mueller, Alfred and Stephan, Klaas Enno}, doi = {10.1136/jnnp-2018-320050}, journal-iso = {J NEUROL NEUROSUR PS}, journal = {JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY}, volume = {90}, unique-id = {30795555}, issn = {0022-3050}, abstract = {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.}, year = {2019}, eissn = {1468-330X}, pages = {642-651} } @article{MTMT:30725979, title = {Feature-specific prediction errors for visual mismatch}, url = {https://m2.mtmt.hu/api/publication/30725979}, author = {Stefanics, Gábor and Stephan, Klaas Enno and Heinzle, Jakob}, doi = {10.1016/j.neuroimage.2019.04.020}, journal-iso = {NEUROIMAGE}, journal = {NEUROIMAGE}, volume = {196}, unique-id = {30725979}, issn = {1053-8119}, abstract = {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.}, keywords = {PERCEPTION; Color perception; Emotion recognition; Predictive coding; perceptual inference; Precision weighted prediction error}, year = {2019}, eissn = {1095-9572}, pages = {142-151}, orcid-numbers = {Stefanics, Gábor/0000-0002-0324-0996} } @misc{MTMT:31310801, title = {F157. HIERARCHICAL PREDICTION ERRORS DURING AUDITORY MISMATCH UNDER PHARMACOLOGICAL MANIPULATIONS: A COMPUTATIONAL SINGLE-TRIAL EEG ANALYSIS}, url = {https://m2.mtmt.hu/api/publication/31310801}, author = {Weber, Lilian and Diaconescu, Andreea and Tomiello, Sara and Schöbi, Dario and Iglesias, Sandra and Mathys, Christoph and Haker, Helene and Stefanics, Gábor and Schmidt, André and Kometer, Michael and Vollenweider, Franz X and Stephan, Klaas Enno}, doi = {10.1093/schbul/sby017.688}, unique-id = {31310801}, year = {2018} } @article{MTMT:31309070, title = {Automatic Processing of Changes in Facial Emotions in Dysphoria. A Magnetoencephalography Study.}, url = {https://m2.mtmt.hu/api/publication/31309070}, author = {Xu, Qianru and Ruohonen, Elisa M and Ye, Chaoxiong and Li, Xueqiao and Kreegipuu, Kairi and Stefanics, Gábor and Luo, Wenbo and Astikainen, Piia}, doi = {10.3389/fnhum.2018.00186}, journal-iso = {FRONT HUM NEUROSCI}, journal = {FRONTIERS IN HUMAN NEUROSCIENCE}, volume = {12}, unique-id = {31309070}, issn = {1662-5161}, abstract = {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.}, keywords = {dysphoria; Change detection; magnetoencephalography; EMOTIONAL FACES; automatic}, year = {2018}, eissn = {1662-5161}, pages = {186} } @article{MTMT:3394936, title = {Visual Mismatch and Predictive Coding: A Computational Single-Trial ERP Study}, url = {https://m2.mtmt.hu/api/publication/3394936}, author = {Stefanics, Gábor and Heinzle, Jakob and Horváth, András Attila and Stephan, Klaas}, doi = {10.1523/JNEUROSCI.3365-17.2018}, journal-iso = {J NEUROSCI}, journal = {JOURNAL OF NEUROSCIENCE}, volume = {38}, unique-id = {3394936}, issn = {0270-6474}, abstract = {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.}, year = {2018}, eissn = {1529-2401}, pages = {4020-4030} } @article{MTMT:3282565, title = {EEG and ERP biomarkers of Alzheimer's disease: a critical review}, url = {https://m2.mtmt.hu/api/publication/3282565}, author = {Horváth, András Attila and Szűcs, Anna and Csukly, Gábor and Sákovics, Anna and Stefanics, Gábor and Kamondi, Anita}, doi = {10.2741/4587}, journal-iso = {FRONT BIOSCI-LANDMARK}, journal = {FRONTIERS IN BIOSCIENCE-LANDMARK}, volume = {23}, unique-id = {3282565}, issn = {2768-6701}, abstract = {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.}, year = {2018}, eissn = {2768-6698}, pages = {183-220}, orcid-numbers = {Szűcs, Anna/0000-0002-9990-5787; Csukly, Gábor/0000-0002-5006-9407; Kamondi, Anita/0000-0001-9860-730X} } @article{MTMT:31311240, title = {Computational Modeling of Mismatch Negativity (MMN)}, url = {https://m2.mtmt.hu/api/publication/31311240}, author = {Stefanics, Gábor}, doi = {10.1111/psyp.12925}, journal-iso = {PSYCHOPHYSIOLOGY}, journal = {PSYCHOPHYSIOLOGY}, volume = {54}, unique-id = {31311240}, issn = {0048-5772}, year = {2017}, eissn = {1469-8986}, pages = {S9-S10} }