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Dryad

Stroke data from: Robust dynamic brain coactivation states estimated in individuals

Cite this dataset

Peng, Xiaolong et al. (2022). Stroke data from: Robust dynamic brain coactivation states estimated in individuals [Dataset]. Dryad. https://doi.org/10.5061/dryad.kwh70rz76

Abstract

A confluence of evidence indicates that brain functional connectivity (FC) is not static but rather dynamic. Capturing transient network interactions in the individual brain requires a technology that offers sufficient within-subject reliability. Here, we introduce an individualized network-based dynamics analysis technique and demonstrate that it is reliable in detecting subject-specific brain states during both resting state and a cognitively challenging language task. Moreover, we evaluated the extent to which brain states showed hemispheric asymmetries and how various phenotypic factors such as handedness and gender might influence network dynamics. We discovered a right-lateralized brain state that occurred more frequently in men than in women, and more frequently in right-handed versus left-handed individuals. Lastly, we demonstrated longitudinal brain state changes in 42 patients with subcortical stroke over 6 months. Taken together, this approach could quantify subject-specific dynamic brain states and has potential for use in both basic and clinical neuroscience research.

Methods

This is supplemental material for "X. Peng, Robust dynamic brain coactivation states estimated in individuals, Science Advances, 2022".

Funding

National Natural Science Foundation of China, Award: 81790652

National Natural Science Foundation of China, Award: 81790650

National Institute of Neurological Disorders and Stroke, Award: R01NS091604

National Institute of Mental Health, Award: P50MH106435

National Institute of Neurological Disorders and Stroke, Award: R21NS120186

National Institute of Mental Health, Award: R61MH121640

National Institute of Mental Health, Award: 5K01MH111802