EEG coherence of prefrontal areas in normal and schizophrenic males during perceptual activation

Re, Hoffman; Ms, Buchsbaum; Escobar, Michael; Makuch, RW; Kh, Nuechterlein; Sm, Guich

doi:10.1176/jnp.3.2.169

Cited by 49 publications

(2 citation statements)

References 31 publications

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“…These studies, largely applying bivariate methods, e.g., (phase) coherence analysis of time series in pairs of EEG signals, exemplified abnormalities in EEG synchronization at rest and during the performance of cognitive tasks [25], [26], [27], [28], [29], [30], [31]. However, the limitations of bivariate synchronization analysis inevitably led to the region-of-interest approach that is an analysis of several pre-selected pairs of signals.…”

Section: Introductionmentioning

confidence: 99%

Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG

et al. 2007

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BackgroundThe 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.Methods/ResultsTo 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.Conclusion/SignificanceThe 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.

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Section: Introductionmentioning

confidence: 99%

Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG

et al. 2007

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“…As to the evoked alpha activity, in SCZ a relationship between evoked alpha power and speed of processing [ 89 ] and working memory [ 99 ] has been detected. Furthermore, deficits in EEG signal coherence between cortical, temporal and occipital areas in the alpha band were related to worse vigilance skills in SCZ [ 112 ]. However, a lack of correlation between event-related alpha activity and different cognitive domains such as speed of processing, memory and learning [ 90 , 110 ], or between evoked alpha desynchronization and social cognition skills [ 87 ] have also been reported.…”

Section: Resultsmentioning

confidence: 99%

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

et al. 2022

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Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.

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An In Vivo Study of the Prefrontal Cortex of Schizophrenic Patients at Different Stages of Illness via Phosphorus Magnetic Resonance Spectroscopy

Stanley

Williamson

Drost

et al. 1995

Arch Gen Psychiatry

197

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EEG coherence of prefrontal areas in normal and schizophrenic males during perceptual activation

Cited by 49 publications

References 31 publications

Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG

Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

An In Vivo Study of the Prefrontal Cortex of Schizophrenic Patients at Different Stages of Illness via Phosphorus Magnetic Resonance Spectroscopy

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