Show simple item record

dc.contributor.authorIraji, Armin
dc.contributor.authorFaghiri, Ashkan
dc.contributor.authorFu, Zening
dc.contributor.authorRachakonda, Srinivas
dc.contributor.authorKochunov, Peter
dc.contributor.authorBelger, Aysenil
dc.contributor.authorFord, Judy M.
dc.contributor.authorMcEwen, Sarah
dc.contributor.authorMathalon, Daniel H.
dc.contributor.authorMueller, Bryon A.
dc.contributor.authorPearlson, Godfrey D.
dc.contributor.authorPotkin, Steven G.
dc.contributor.authorPreda, Adrian
dc.contributor.authorTurner, Jessica A.
dc.contributor.authorvan Erp, Theodorus G.M.
dc.contributor.authorCalhoun, Vince D.
dc.date.accessioned2022-06-13T13:18:06Z
dc.date.available2022-06-13T13:18:06Z
dc.date.issued2022-06-01
dc.identifier.urihttp://hdl.handle.net/10713/19120
dc.description.abstractWe introduce an extension of independent component analysis (ICA), called multiscale ICA, and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. Multiscale ICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and sex-common connectivity patterns in schizophrenia. Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex-specific differences occur (a) within the subcortical domain, (b) between the somatomotor and cerebellum domains, and (c) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial-scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial-scale functional interactions and symptom scores, highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.en_US
dc.description.sponsorshipNational Institutes of Healthen_US
dc.description.urihttps://doi.org/10.1162/netn_a_00196en_US
dc.language.isoenen_US
dc.publisherMIT Pressen_US
dc.relation.ispartofNetwork Neuroscienceen_US
dc.subjectMulti-model-order independent component analysis (ICA)en_US
dc.subjectMulti-spatial-scale dynamic functional connectivityen_US
dc.subjectMulti-spatial-scale intrinsic connectivity networksen_US
dc.subjectMultiscale ICA (msICA)en_US
dc.subjectResting-state fMRIen_US
dc.titleMulti-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophreniaen_US
dc.typeArticleen_US
dc.identifier.doi10.1162/netn_a_00196
dc.source.journaltitleNetwork Neuroscience
dc.source.volume6
dc.source.issue2
dc.source.beginpage357
dc.source.endpage381


This item appears in the following Collection(s)

Show simple item record