Published in

Massachusetts Institute of Technology Press, Network Neuroscience, 2(6), p. 357-381, 2022

DOI: 10.1162/netn_a_00196



Export citation

Search in Google Scholar

Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Orange circle
Preprint: archiving restricted
Orange circle
Postprint: archiving restricted
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO


Abstract We 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.