Distinct functional and structural connections predict crystallised and fluid cognition in healthy adults. Issue 10 (8th April 2021)

• Record Type: Journal Article
• Authors: Dhamala, Elvisha; Jamison, Keith W.; Jaywant, Abhishek; Dennis, Sarah; Kuceyeski, Amy
• Is Part Of: Human brain mapping. Volume 42:Issue 10(2021)
• Page Start: 3102
• Page End: 3118
• Publication Date: 2021-04-08
• Subjects: cognition -- connectomics -- functional connectivity -- machine learning -- neuroimaging -- prediction -- structural connectivity; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25420
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: White matter pathways between neurons facilitate neuronal coactivation patterns in the brain. Insight into how these structural and functional connections underlie complex cognitive functions provides an important foundation with which to delineate disease‐related changes in cognitive functioning. Here, we integrate neuroimaging, connectomics, and machine learning approaches to explore how functional and structural brain connectivity relate to cognition. Specifically, we evaluate the extent to which functional and structural connectivity predict individual crystallised and fluid cognitive abilities in 415 unrelated healthy young adults (202 females) from the Human Connectome Project. We report three main findings. First, we demonstrate functional connectivity is more predictive of cognitive scores than structural connectivity, and, furthermore, integrating the two modalities does not increase explained variance. Second, we show the quality of cognitive prediction from connectome measures is influenced by the choice of grey matter parcellation, and, possibly, how that parcellation is derived. Third, we find that distinct functional and structural connections predict crystallised and fluid abilities. Taken together, our results suggest that functional and structural connectivity have unique relationships with crystallised and fluid cognition and, furthermore, studying both modalities provides a more comprehensive insight into the neural correlates of cognition. Abstract : In this study, we investigate the relationship between multimodal connectivity and cognition. First, we demonstrate functional connectivity is more predictive of cognitive scores than structural connectivity, and, furthermore, integrating the two modalities does not increase explained variance. Second, we show the quality of cognitive prediction from connectome measures is influenced by the choice of grey matter parcellation, and, possibly, how that parcellation is derived. Third, we find that distinct functional and structural connections predict crystallised and fluid abilities.