title: Dysconnection topography in schizophrenia revealed with state-space analysis of EEG.
abstract: BACKGROUND
  The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals.
  
  
  RESULTS
  To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels) EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series-the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity.
  
  
  CONCLUSIONS
  The new method of multivariate synchronization significantly boosts the potential of EEG as an imaging technique compatible with other imaging modalities. Its application to schizophrenia research shows that schizophrenia can be explained within the concept of neural dysconnection across and within large-scale brain networks.
authors.affiliation: Ecole Polytechnique Fédérale de Lausanne, IC-School of Computer and Communication Sciences, Laboratory of Nonlinear Systems, Lausanne, Switzerland.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Jalili
authors.forename: Suzie
authors.initials: S
authors.lastname: Lavoie
authors.forename: Patricia
authors.initials: P
authors.lastname: Deppen
authors.forename: Reto
authors.initials: R
authors.lastname: Meuli
authors.forename: Kim Q
authors.initials: KQ
authors.lastname: Do
authors.forename: Michel
authors.initials: M
authors.lastname: Cuénod
authors.forename: Martin
authors.initials: M
authors.lastname: Hasler
authors.forename: Oscar
authors.initials: O
authors.lastname: De Feo
authors.forename: Maria G
authors.initials: MG
authors.lastname: Knyazeva
mesh_terms: D000328:Adult; D001931:Brain Mapping; D016022:Case-Control Studies; D002540:Cerebral Cortex; D003344:Cortical Synchronization; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000473:pathology; D012559:Schizophrenia / Q000175:diagnosis* / Q000473:pathology*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors