Intracranial recordings captured from subdural electrodes in patients with drug resistant epilepsy offer clinicians and researchers a powerful tool for examining neural activity in the human brain with high spatial and temporal precision. There are two major challenges, however, to interpreting these signals both within and across individuals. Anatomical distortions following implantation make accurately identifying the electrode locations difficult. In addition, because each implant involves a unique configuration, comparing neural activity across individuals in a standardized manner has been limited to broad anatomical regions such as cortical lobes or gyri. We address these challenges here by introducing a semi-automated method for localizing subdural electrode contacts to the unique surface anatomy of each individual, and by using a surface-based grid of regions of interest (ROIs) to aggregate electrode data from similar anatomical locations across individuals. Our localization algorithm, which uses only a postoperative CT and preoperative MRI, builds upon previous spring-based optimization approaches by introducing manually identified anchor points directly on the brain surface to constrain the final electrode locations. This algorithm yields an accuracy of 2 mm. Our surface-based ROI approach involves choosing a flexible number of ROIs with different spatial resolutions. ROIs are registered across individuals to represent identical anatomical locations while accounting for the unique curvature of each brain surface. This ROI based approach therefore enables group level statistical testing from spatially precise anatomical regions.

Objective Presurgical language assessment can help minimize damage to eloquent cortex during resective epilepsy surgery. Two methods for presurgical language mapping are functional MRI (fMRI) and direct cortical stimulation (DCS) of implanted subdural electrodes. We compared fMRI results to DCS to help optimize non-invasive language localization and assess its validity. Methods We studied 19 patients referred for presurgical evaluation of drug-resistant epilepsy. Patients completed 4 language tasks during preoperative fMRI. After subdural electrode implantation, we used DCS to localize language areas. For each stimulation site, we determined whether language positive electrode pairs intersected with significant fMRI activity clusters for language tasks. Results Sensitivity and specificity depended on electrode ROI radii and statistical thresholding. For patients with at least one language positive stimulation site, an auditory description decision task provided the best tradeoff between sensitivity and specificity. For patients with no language positive stimulation sites, fMRI was a dependable method of excluding eloquent language processing. Interpretation Language fMRI is an effective tool for determining language lateralization prior to electrode implantation, and is especially useful for excluding unexpected critical language areas. It can help guide subdural electrode implantation and narrow the search for eloquent cortical areas via DCS.

We identify a memory-specific attention mechanism in the human anterior temporal lobe, an area implicated in semantic processing and episodic memory formation. Spiking neuron activity is suppressed and becomes more reliable in preparation for verbal memory formation. Intracranial EEG signals implicate this region as a source of executive control for attentional selection. Consistent with this interpretation, its surgical removal causes a significant memory impairment for attended words relative to unattended words.

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