• Manu Krishnamurthy, Xiaozhen You, Leigh N Sepeta, Emily Matuska, Chima Oluigbo, Madison M Berl, William D Gaillard, and Taha Gholipour.
• Center for Neuroscience, Children's National Hospital, George Washington University, Washington, D.C., USA.
• J Neuroimaging. 2022 Nov 1; 32 (6): 120112101201-1210.

Background And PurposeTask-based functional MRI (fMRI) mapping of the motor function prior to epilepsy surgery has limitations in children with epilepsy. We present a data-driven method to automatically delineate the motor cortex using task-free, resting-state fMRI (rsfMRI) data.MethodsWe used whole-brain rsfMRI for independent component analysis (ICA). A template matching process with Discriminability Index-based Component Identification score was used for each participant to select and combine motor ICA components in their native brain space, resulting in a whole-brain ICA Motor Map (wIMM). We validated wIMM by comparing individual results with bilateral finger-tapping motor task fMRI activation, and evaluated its reproducibility in controls.ResultsData from 64 patients and 12 controls were used to generate group wIMM maps. The hit rate between wIMM and motor task activation ranged from 60% to 79% across all participants. Sensitivity of wIMM for capturing the task activation peak was 87.5% among 32 patients and 100% in 12 controls with available motor task results. We also showed high similarity in repeated runs in controls.ConclusionsOur results show the sensitivity and reproducibility of an automated motor mapping method based on ICA analysis of rsfMRI in children with epilepsy. The ICA maps may provide different, but useful, information than task fMRI. Future studies will expand our method to mapping other brain functions, and may lead to a surgical planning tool for patients who cannot perform task fMRI and help predict their postsurgical function.© 2022 American Society of Neuroimaging.

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