Fig. 2.

Prediction of behavioral deficits on the basis of structural and functional imaging. (A) Experimental procedures for manual lesion segmentation (Upper), and for region of interest (ROI)-based functional connectivity estimation. (B) Ridge regression was applied using either lesion or functional connectivity to predict deficit for a left-out patient. A ridge regression function using lesion/FC to explain deficit is trained for n − 1 subjects. For each patient, this function generates a prediction of deficit in each domain based on data, and a beta weight matrix that can be projected back on to the brain. (C) Predicted deficit scores were compared with measured scores for each patient to determine model accuracy. (D) Beta weights used to predict left motor deficit with either the lesion (Upper) or the FC matrix (Lower) are projected back on to the brain.