Journal Article

DZNE-2026-01113

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Multivariate connectivity deviations reveal task-evoked and clinical network reorganization

Kröll, J.-P. ; Abdelmotaleb, M. ; Kocataş, H. ; Müller, V. ; Paas, L. ; Meinzer, M. ; Flöel, A.DZNE* ; Eickhoff, S. ; Patil, K. R.

2026
Elsevier St. Louis

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Please use a persistent id in citations: doi:10.1016/j.isci.2026.117959

Abstract: Understanding how cognitive demands and pathology reshape functional connectivity (FC) requires multivariate, region-specific methods. Here, we introduce one-class SVM-based connectome anomaly recognition (OSCAR), which detects condition-related deviations in regional connectivity profiles. OSCAR learns region-to-whole-brain connectivity patterns from a reference state using one-class support vector machines and quantifies target-condition deviations based on outlier proportions. We validated OSCAR across three diverse cognitive tasks, in which it identified regions within networks associated with conflict processing, object-location memory, and lexical learning. In a clinical cohort that included individuals with early psychosis, OSCAR identified relevant regions, including thalamic and basal ganglia areas. Compared with permutation-based multivariate analysis of variance, OSCAR detected additional established task- and disease-relevant parcels, while its task-related findings were at least as close, and often closer, to independent activation findings. OSCAR thus provides an interpretable, region-centered approach for mapping multivariate FC reconfigurations across experimental and clinical conditions.

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Contributing Institute(s):

1. Dementia Prevention – Mechanisms and Clinical Implementation (AG Flöel)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

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Database coverage:
; ; Article Processing Charges ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DOAJ Seal ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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