Page 298 - MEGIN Book Of Abstracts - 2023

associated with the Positive and Negative Syndrome state condition. MEG coherence source imaging (CSI) in
Scale total and thought disorder factors for the first source space and spectral analysis in sensor space were
three networks. In addition, the left posterior temporal performed. Significant differences were found between
network was associated with positive and negative fac- the 2 patient groups: (1) MEG and EEG spectral analysis
tors, and the right inferior frontal network was associ- showed significantly higher power at low frequencies
ated with the positive factor. (delta band) at sensor space in DS compared with NDS
patients; (2) source analysis revealed larger power in
CONCLUSIONS Machine learning network analysis of the DS compared with NDS group at low frequencies
resting alpha-band neural activity identified several in the frontal region; (3) NDS patients showed signifi-
aberrant networks in individuals with first-episode cantly higher MEG signal relative power in beta bands
schizophrenia spectrum psychosis, including the left in sensor space compared with DS patients; (4) both DS
temporal, right inferior frontal, right posterior parietal, and NDS patients showed higher EEG absolute power
and bilateral cingulate cortices. Abnormal long-range at higher beta band compared to controls; and (5) pa-
alpha communication is evident at the first presenta- tients with DS were found to have a significantly higher
tion for psychosis and may provide clues about mecha- MEG CSI than controls in the beta frequency band.
nisms of dysconnectivity in psychosis and novel targets These data support the observation of increased power
for noninvasive brain stimulation. in the low-frequency EEG/MEG rhythms associated with
the DS. Increased power in the beta rhythms was more
Keywords: Alpha, Machine learning, Magnetoencepha- associated with the NDS.
lography, Network, Non-negative matrix factorization,
Schizophrenia Keywords: EEG, MEG, coherence source imaging, deficit
syndrome, electroencephalography, magnetoencepha-
Biological psychiatry. Cognitive neuroscience and lography, resting state, schizophrenia
neuroimaging (2020), Vol. 5, No. 10 (31451387) (10
citations) Clinical EEG and neuroscience (2020), Vol. 51, No. 1
(31379210) (5 citations)

Deficit Versus Nondeficit Schizophrenia: An MEG-
EEG Investigation of Resting State and Source Oscillatory, Computational, and Behavioral
Coherence-Preliminary Data (2020) Evidence for Impaired GABAergic Inhibition in
Schizophrenia (2020)
Gjini, Klevest; Bowyer, Susan M; Wang, Frank; Boutros,
Nash N Shaw, Alexander D; Knight, Laura; Freeman, Tom C A;
Williams, Gemma M; Moran, Rosalyn J; Friston, Karl J;
Department of Neurology, University of Wisconsin-Madison, Walters, James T R; Singh, Krish D
Madison, WI, USA; Wayne State University, Detroit, MI, USA;
University of California, Berkeley, Berkeley, CA, USA; Depart- CUBRIC, School of Psychology, College of Biomedical and Life
ment of Psychiatry, Wayne State University, Detroit, MI, USA Sciences, Cardiff University, Cardiff, UK; MRC Centre for Neuro-
psychiatric Genetics and Genomics, Division of Psychological
ABSTRACT This study investigated the magneto- and Medicine and Clinical Neurosciences, School of Medicine,
electroencephalography (MEG and EEG, respectively) Cardiff University, Cardiff, UK
resting state to identify the deviations closely associ-
ated with the deficit syndrome (DS) in schizophrenia ABSTRACT The dysconnection hypothesis of schizo-
patients. Ten subjects in each group (control, DS, and phrenia (SZ) proposes that psychosis is best under-
nondeficit schizophrenia [NDS]) were included. Sub- stood in terms of aberrant connectivity. Specifically,
jects underwent MEG-EEG recordings during a resting it suggests that dysconnectivity arises through aber-

 ontents  Index 277
C