Evidence map›Paper›PMID 40079512›Full record

ArticleBrain and behavior2025

Functional Connectivity in Chronic Schizophrenia: An EEG Resting-State Study with Corrected Imaginary Phase-Locking.

Christophe Domingos, Wiktor Więcławski, Sandra Frycz, Maja Wojcik, Martin Jáni, Olga Dudzińska, Przemysław Adamczyk, Tomas Ros

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Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Christophe DomingosInstitute of Psychology, Jagiellonian University, Krakow, Poland.ORCID https://orcid.org/0000-0001-5855-1372
Wiktor WięcławskiInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Sandra FryczInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Maja WojcikInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Martin JániInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Olga DudzińskaInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Przemysław AdamczykInstitute of Psychology, Jagiellonian University, Krakow, Poland.
Tomas RosDepartment of Clinical Neuroscience, University of Geneva, Geneva, Switzerland.

Funding

National Science Centre Poland 2016/23/B/HS6/00286National Science Centre Poland 2021/41/B/HS6/02967Swiss National Science Foundation (SNSF) 215712
6 · The paper itself

Abstract

Schizophrenia is a complex disorder characterized by altered brain functional connectivity, detectable during both task and resting state conditions using different neuroimaging methods. To this day, electroencephalography (EEG) studies have reported inconsistent results, showing both hyper- and hypo-connectivity with diverse topographical distributions. Interpretation of these findings is complicated by volume-conduction effects, where local brain activity fluctuations project simultaneously to distant scalp regions (zero-phase lag), inducing spurious inter-electrode correlations.

aimIn the present study, we explored the network dynamics of schizophrenia using a novel functional connectivity metric-corrected imaginary phase locking value (ciPLV)-which is insensitive to changes in amplitude as well as interactions at zero-phase lag. This method, which is less prone to volume conduction effects, provides a more reliable estimate of sensor-space functional network connectivity in schizophrenia.

methodsWe employed a cross-sectional design, utilizing resting state EEG recordings from two adult groups: individuals diagnosed with chronic schizophrenia (n = 30) and a control group of healthy participants (n = 30), all aged between 18 and 55 years old.

resultsOur observations revealed that schizophrenia is characterized by a prevalence of excess theta (4-8 Hz) power localized to centroparietal electrodes. This was accompanied by significant alterations in inter- and intra-hemispheric functional network connectivity patterns, mainly between frontotemporal regions within the theta band and frontoparietal regions within beta/gamma bands.

conclusionsOur findings suggest that patients with schizophrenia demonstrate long-range electrophysiological connectivity abnormalities that are independent of spectral power (i.e., volume conduction). Overall, distinct hemispheric differences were present in frontotemporo-parietal networks in theta and beta/gamma bands. While preliminary, these alterations could be promising new candidate biomarkers of chronic schizophrenia.

Indexed as

BrainElectroencephalographyNerve NetSchizophreniaAdolescentAdultBrain MappingChronic DiseaseCross-Sectional StudiesFemaleHumansMaleMiddle AgedNeural PathwaysRestYoung AdultEEGfunctional connectivityphase locking valuepower spectrumresting‐stateschizophrenia

Identifiers

PMID40079512
PMCPMC11905041

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.