First, we used patient‐specific anatomic MRI, stimulation settings, and volume of tissue activated (VTA) modeling techniques to estimate the extent of tissue directly modulated by DBS during each observation. Following non‐uniformity correction of all MR images, VTA modeling was conducted using a well‐described pipeline (lead‐DBS v2.0; https://www.lead-dbs.org/). This involved localization of electrode contacts on postoperative MRI acquisitions by two experienced users (AH and GJBE), non‐linear normalization to MNI152 standard space (using “low variance” ANTS (http://stnava.github.io/ANTs/) with an additional subcortical affine transformation when necessary) via coregistered preoperative images, and estimation of the shape/extent of the electrical field using finite element method modeling with 0.2 V/mm gradient thresholding (FieldTrip‐SimBio pipeline; http://fieldtriptoolbox.org). 25 , 26 A VTA was estimated for each of the sampled “memory‐yes” and “memory‐no” observations using the corresponding stimulation setting (contact and voltage) and peri‐electrode conductivity estimates (gray matter: 0.33 S/m; white matter: 0.14 S/m; cerebrospinal fluid: 1.79 S/m; electrode contact: 108 S/m; insulated electrode components: 10−16 S/m) derived from standard space tissue priors. Left‐sided VTAs were flipped in the sagittal plane to facilitate group‐level analysis. Figure  1 provides a visual summary of the major neuroimaging processing steps used in this paper.

Visual summary of neuroimaging methods. The major methodological steps (colored arrows) and their corresponding descriptions are shown alongside exemplar brain images. First, patient‐acquired pre‐ and postoperative anatomic MRI scans were coregistered together, and each patient's leads were precisely localized in patient space based on the post‐operative acquisition (red arrows). Next, the coregistered patient scans were normalized to a standard MNI152 template, and the resultant transforms were used to warp the lead models to MNI space (green arrows). VTAs were then modeled for each “memory‐yes/memory‐no” observation in MNI space using the corresponding stimulation settings and conductivity estimates from standard space tissue priors (turquoise arrow). Finally, the created VTAs (n = 386) were employed as (1) inputs for local voxel‐wise mapping analysis (yellow arrow) and (2) seeds for rsfMRI functional connectivity mapping (magenta arrow). MNI = Montreal Neurological Institute; rsfMRI = resting state functional magnetic resonance imaging; VTA = volume of tissue activated

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