Abstract #1294

Hybrid structure-function connectome predicts individual cognitive abilities

Elvisha Dhamala^1,2, Keith W Jamison¹, Sarah M Dennis³, Raihaan Patel^4,5, M Mallar Chakravarty^4,5,6, and Amy Kuceyeski^1,2

¹Radiology, Weill Cornell Medicine, New York, NY, United States, ²Neuroscience, Weill Cornell Medicine, New York, NY, United States, ³Sarah Lawrence College, Bronxville, NY, United States, ⁴Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada, ⁵Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada, ⁶Psychiatry, McGill University, Montreal, QC, Canada

Structural connectivity (SC) and functional connectivity (FC) can be independently used to predict cognition and show distinct patterns of variance in relation to cognition. No work identified has yet investigated whether SC and FC can be combined to better predict cognitive abilities. In this work, we aimed to predict cognitive measures in 785 healthy adults using a hybrid structure-function connectome and quantify the most important connections. We show that: 1) hybrid connectomes explain 15% of the variance in individual cognitive measures, and 2) long-range cortico-cortical functional connections and short-range cortico-subcortical and subcortico-subcortical structural connections are most important for the prediction.

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