Aberrant information flow within resting-state triple network model in schizophrenia : an EEG effective connectivity study

2025
journal article
article
dc.abstract.enSchizophrenia is a psychiatric disorder with heterogeneous clinical manifestations and complex aetiology. Notably, the triple-network model proposes an interesting framework for investigating abnormal neurocircuit activity at rest in schizophrenia. The present study on 30 chronic schizophrenia individuals and 30 controls aimed to explore the differences in EEG resting state effective connectivity within a triple-network model using source-localization-based Directed Transfer Function. Our findings revealed multiband effective connectivity disturbances within default mode (DMN), central executive (CEN), and salience (SN) networks in schizophrenia. The most significant difference was manifested in a global DMN hyperconnectivity, accompanied by low-band hyperconnectivity and high-band hypoconnectivity in CEN, along with the aberrant information flows in SN. In conclusion, our study presents novel insights into schizophrenia neuropathology, with a particular emphasis on the reversed directionality in information flows between hubs of SN, DMN, and CEN. This may be suggested as a promising biomarker of schizophrenia.
dc.affiliationWydział Filozoficzny : Instytut Psychologii
dc.affiliationSzkoła Doktorska Nauk Społecznych
dc.contributor.authorAdamczyk, Przemysław - 105187
dc.contributor.authorWięcławski, Wiktor
dc.contributor.authorWójcik, Maja
dc.contributor.authorFrycz, Sandra - 456304
dc.contributor.authorPanek, Bartłomiej - 216204
dc.contributor.authorJani, Martin
dc.contributor.authorWyczesany, Mirosław - 126071
dc.date.accessioned2025-04-15T07:43:23Z
dc.date.available2025-04-15T07:43:23Z
dc.date.createdat2025-03-25T18:03:20Zen
dc.date.issued2025
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.sponsorshipidubidub_yes
dc.description.versionostateczna wersja wydawcy
dc.description.volume349
dc.identifier.articleid111985
dc.identifier.doi10.1016/j.pscychresns.2025.111985
dc.identifier.doidataset10.57903/UJ/VWZUOD
dc.identifier.issn0925-4927
dc.identifier.projectNarodowe Centrum Nauki 2016/23/B/HS6/00286
dc.identifier.projectNarodowe Centrum Nauki 2021/41/B/HS6/02967
dc.identifier.urihttps://ruj.uj.edu.pl/handle/item/551522
dc.languageeng
dc.language.containereng
dc.rightsUdzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa
dc.rights.licenceCC-BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/legalcode.pl
dc.share.typeotwarte czasopismo
dc.subject.encentral executive network
dc.subject.endefault mode network
dc.subject.eneffective connectivity
dc.subject.enEEG
dc.subject.enresting-state
dc.subject.enschizophrenia
dc.subtypeArticle
dc.titleAberrant information flow within resting-state triple network model in schizophrenia : an EEG effective connectivity study
dc.title.journalPsychiatry Research - Neuroimaging
dc.typeJournalArticle
dspace.entity.typePublicationen
dc.abstract.en
Schizophrenia is a psychiatric disorder with heterogeneous clinical manifestations and complex aetiology. Notably, the triple-network model proposes an interesting framework for investigating abnormal neurocircuit activity at rest in schizophrenia. The present study on 30 chronic schizophrenia individuals and 30 controls aimed to explore the differences in EEG resting state effective connectivity within a triple-network model using source-localization-based Directed Transfer Function. Our findings revealed multiband effective connectivity disturbances within default mode (DMN), central executive (CEN), and salience (SN) networks in schizophrenia. The most significant difference was manifested in a global DMN hyperconnectivity, accompanied by low-band hyperconnectivity and high-band hypoconnectivity in CEN, along with the aberrant information flows in SN. In conclusion, our study presents novel insights into schizophrenia neuropathology, with a particular emphasis on the reversed directionality in information flows between hubs of SN, DMN, and CEN. This may be suggested as a promising biomarker of schizophrenia.
dc.affiliation
Wydział Filozoficzny : Instytut Psychologii
dc.affiliation
Szkoła Doktorska Nauk Społecznych
dc.contributor.author
Adamczyk, Przemysław - 105187
dc.contributor.author
Więcławski, Wiktor
dc.contributor.author
Wójcik, Maja
dc.contributor.author
Frycz, Sandra - 456304
dc.contributor.author
Panek, Bartłomiej - 216204
dc.contributor.author
Jani, Martin
dc.contributor.author
Wyczesany, Mirosław - 126071
dc.date.accessioned
2025-04-15T07:43:23Z
dc.date.available
2025-04-15T07:43:23Z
dc.date.createdaten
2025-03-25T18:03:20Z
dc.date.issued
2025
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.sponsorshipidub
idub_yes
dc.description.version
ostateczna wersja wydawcy
dc.description.volume
349
dc.identifier.articleid
111985
dc.identifier.doi
10.1016/j.pscychresns.2025.111985
dc.identifier.doidataset
10.57903/UJ/VWZUOD
dc.identifier.issn
0925-4927
dc.identifier.project
Narodowe Centrum Nauki 2016/23/B/HS6/00286
dc.identifier.project
Narodowe Centrum Nauki 2021/41/B/HS6/02967
dc.identifier.uri
https://ruj.uj.edu.pl/handle/item/551522
dc.language
eng
dc.language.container
eng
dc.rights
Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa
dc.rights.licence
CC-BY
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/legalcode.pl
dc.share.type
otwarte czasopismo
dc.subject.en
central executive network
dc.subject.en
default mode network
dc.subject.en
effective connectivity
dc.subject.en
EEG
dc.subject.en
resting-state
dc.subject.en
schizophrenia
dc.subtype
Article
dc.title
Aberrant information flow within resting-state triple network model in schizophrenia : an EEG effective connectivity study
dc.title.journal
Psychiatry Research - Neuroimaging
dc.type
JournalArticle
dspace.entity.typeen
Publication
Affiliations

* The migration of download and view statistics prior to the date of April 8, 2024 is in progress.

Views
13
Views per month
Views per city
Warsaw
3
Singapore
1
Downloads
adamczyk_et-al_aberrant_information_flow_within_resting-state_triple_2025.pdf
2
adamczyk_psyn_2025.pdf
2