Electrophysiological insights into connectivity anomalies in schizophrenia: a systematic review

Abstract

The pathophysiology of schizophrenia may fundamentally involve a disturbance in the interaction between neuronal groups that leads to impaired communication within and between brain areas. Such a "dysconnectivity syndrome" could underlie the pronounced cognitive deficits as well as the emergence of psychosis. Evidence for this hypothesis has mainly come from functional magnetic resonance imaging (fMRI) studies which have investigated connectivity anomalies during spontaneous as well as task-related activity. In the current review, we will summarize evidence from electro-and magnetoencephalography (EEG/MEG) which have employed measures, such as coherence, phase-locking and mutual information, that have tested changes in functional connectivity during task-related as well as resting-state time-frequency data. We will highlight the methodological issues associated with these measures as well as provide recommendations for future research.

A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns

“…The accuracy of CNN using PDC features ranged from 72.65% to 86.91% (with modified accuracy ranged from 70.95% to 86.90%), in which the alpha frequency band is more discriminative compared to other frequency bands. This could be explained by the previous findings that the more pronounced differences in EEG connectivity between the SZ and HC were observed in the low-frequency and alpha bands [13]. Altered neural oscillation and synchronization in SZ can be associated with several key features of the disorder such as the generalized cognitive deficits, neurodevelopmental profile and cellular dysfunction [12].…”

“…Analysis of functional connectivity (FC), the statistical dependencies between signals (fMRI or EEG) from spatially distant brain regions, has revealed dysconnectivity in schizophrenic brain networks especially between the frontal regions [8]. EEG studies reported SZ-related aberrant synchronization of neural oscillatory at both the low and high frequencies [12,13]. However, the observed differences in FC patterns between SZ and controls have been inconsistent among fMRI studies, with reports of hyperconnectivity and hypoconnectivity (the increased and decreased strength of connections) between the same brain regions [9].…”

Dissociated cortical phase- and amplitude-coupling patterns in the human brain

“…Both coupling modes may provide versatile biomarkers for various neuropsychiatric diseases (Fornito et al, 2015;Stam, 2014) including autism (Kitzbichler et al, 2015), schizophrenia (Cetin et al, 2016;Maran et al, 2016), epilepsy (Burns et al, 2014;van Dellen et al, 2014;Zerouali et al, 2016), dementia (Koelewijn et al, 2017;Maestú et al, 2015), Parkinson's disease (Oswal et al, 2016), multiple sclerosis (Cover et al, 2006;Schoonheim et al, 2013;Tewarie et al, 2014) and blindness (Hawellek et al, 2013).…”

Global field synchronization of 40 Hz auditory steady-state response: Does it change with attentional demands?

“…Forty Hz ASSRs are increasingly used in neuropsychiatric populations: some authors argue that these responses reflect the integrity of auditory circuits [8,20,42,43], while others interpret ASSRs in terms of global synchronization of neural activity with the external environment [2,25,38]. For the evaluation of the net synchrony/connectivity of electroencephalographic responses, various methods can be employed [44]. However only the coherence between brain areas following 40 Hz periodic auditory stimulation was used before: Mulert et al (2011) applied the coherence as a connectivity measure in patients with schizophrenia and Yamasaki et al (2005) employed the coherence measure in healthy controls to assess the rapid temporal processing in the auditory cortex [45,46].…”