Berchio Cristina, Piguet Camille, Gentsch Kornelia, Küng Anne-Lise, Rihs Tonia A., Hasler Roland, Aubry Jean-Michel, Dayer Alexandre, Michel Christoph M., Perroud Nader (2017), Face and gaze perception in borderline personality disorder: An electrical neuroimaging study, in Psychiatry Research: Neuroimaging
, 269, 62-72.
Berchio Cristina, Piguet Camille, Michel Christoph M., Cordera Paolo, Rihs Tonia A., Dayer Alexandre G., Aubry Jean-Michel (2017), Dysfunctional gaze processing in bipolar disorder, in NeuroImage: Clinical
, 16, 545-556.
Berchio Cristina, Rihs Tonia, Piguet Camille, Dayer Alexandre, Aubry Jean-Michel, Michel Christoph M. (2016), Early averted gaze processing in the right Fusiform Gyrus: An EEG source imaging study., in Biological Psychology
, 119, 156-170.
Gschwind Markus, Hardmeier Martin, Van De Ville Dimitri, Tomescu Miralena I., Penner Iris-Katharina, Naegelin Yvonne, Fuhr Peter, Michel Christoph M., Seeck Margitta (2016), Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis, in NeuroImage: Clinical
, 12, 466-477.
Michel Christoph M., Koenig Thomas, EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review, in Neuroimage
James Clara, Oechslin Matthias, Michel Christoph M, De Pretto M., Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise., in Frontiers Neuroscience
Custo Anna, Van de Ville Dimitri, Wells WM, Brunet Denis, Michel Christoph M, Electroencephalographic Resting-State Networks: Source Localization of Microstates, in Brain Connectivity
Recent research on brain functions using whole-brain imaging methods have led to important paradigm shifts in the understanding of higher cognitive functions and their disturbances in different brain pathologies. The first paradigm shift was from the idea that brain functions are localized in hierarchically distinct areas and the information is processed in a feed-forward stream, to the concept of distributed networks and massive parallel processing in different brain areas collectively serving the same function. The second paradigm shift was a radical change in the interpretation of the brain state during rest: rather than considering the brain inactive and simply reacting to incoming stimuli, the prevailing hypothesis now is that the brain is inherently active in an organized way at rest to be optimally prepared for stimulus processing.This new view of how the brain processes information led to a vast amount of studies that looked at large-scale brain networks at rest: their spatial organization, temporal dynamics, influence on information processing, and changes in different mental diseases. Different methods are used to reveal these networks, leading to different interpretations about their spatial and temporal organization. On the one hand, brain networks are studied with functional magnetic resonance imaging (fMRI) that shows correlated BOLD fluctuations in different brain areas. On the other hand they are studied with Magneto- or Electroencephalography (M/EEG) that show correlated amplitude fluctuations of oscillations in different brain areas or time-varying changes of the topographies of the global electromagnetic field. It has been proposed that the resting state networks (RSN) measured with fMRI (rsfMRI) reflect a sort of “constant inner state of exploration” to make the system optimally prepared for a given impending input and thus influencing perception and cognitive processing. While this idea intuitively makes sense, the fluctuations seen with the rsfMRI are too slow to prepare for a given unpredictable input and to allow a fast and adequate reaction. In order to mediate complex mental activities and optimally respond to the rapidly changing information input, the networks have to reorganize in different spatial patterns on a sub-second time scale. M/EEG can record fluctuations on this time scale and are thus better suited to study the fast dynamics of resting states and their influence on stimulus processing. In this project we propose to characterize the spatial and temporal properties of resting-state networks recorded with high-density EEG, combined EEG-fMRI, and combined intracranial and scalp EEG. We propose several new analysis methods and will apply them on a large number of experimental and clinical data that have been collected in our laboratory during previous years, including data from patients with epilepsy, multiple sclerosis (MS), schizophrenia, autism, bipolar disorder, as well as patients in coma and under anaesthesia. Moreover, collaboration with groups specialized in recordings from deep brain regions will allow us to investigate the role of subcortical structures in resting-state networks and to look at alteration of network dynamics in different disease states (Parkinson’s, Tourette, OCD, drug addiction, epilepsy).We belief that this project will provide a better understanding of the mechanisms that lead to the behavioral and cognitive disturbances in different pathologies at the system level, helping to develop better strategies for rehabilitation and treatment.