Language mapped to a high‐resolution brain atlas for surgical evaluation of epilepsy patients

OBJECTIVE: parcels, based on the MNI152 template and anatomical landmarks. This allowed comparison to similarly transformed direct cortical stimulation (DCS) maps created from medically intractable epilepsy patients studied intracranially at Yale University and selected fMRI activation data. Our goal was to create anatomically precise boundaries of language function and support individualized planning for intracranial EEG (icEEG) studies and/or surgical resection. METHODS: A systematic search of DCS studies of language-related functions identified 12 stimulation studies (10 subdural, two stereo-EEG) that provided sufficiently clear surface visualizations for parcel-level mapping. Language-positive sites from six commonly tested functions (visual naming, auditory naming, naming (auditory/visual), reading, repetition and speech arrest) were manually co-registered to YBA parcels using conserved anatomical landmarks, facilitating topological comparison among similar language functions from the literature, Yale's electrical stimulation mapping cohort, and Neurosynth and Parcelsynth fMRI activation. RESULTS: Across 1182 patients, 176 YBA parcels (approximately 25% of cortical parcels) were implicated in at least one language task. Composite stimulation maps demonstrated robust consistency with the Yale DCS cohort and substantial overlap with distributed fMRI language networks. The resulting interactive maps provide parcel-level specificity while highlighting under-sampled but functionally critical regions. SIGNIFICANCE: The maps provide a review of language function determined through DCS and meta-analytic repositories of fMRI activation data. By consolidating stimulation-derived language data into a high-resolution parcellated atlas, this work offers a spatially detailed surface-based representation of language boundaries for surgical planning. The YBA facilitates standardized multimodal communication and allows patient-specific stimulation results to be interpreted within population-derived functional boundaries.

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Publication Details

Journal
Epilepsia
Published
2026-04-03
DOI
https://doi.org/10.1002/epi.70229
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

Language mapped to a high‐resolution brain atlas for surgical evaluation of epilepsy patients

Hari McGrath, Evan Collins, Omar Chishti, Hitten P. Zaveri et al.
Epilepsia
EEG and Brain-Computer Interfaces
article

Language mapped to a high‐resolution brain atlas for surgical evaluation of epilepsy patients

Hari McGrath, Evan Collins, Omar Chishti, Hitten P. Zaveri, D. D. Spencer, Ryan Bose‐Roy, Adithya Sivaraju, Natalie Akierman Segal, Rachel Lehman
article en

Abstract

OBJECTIVE: parcels, based on the MNI152 template and anatomical landmarks. This allowed comparison to similarly transformed direct cortical stimulation (DCS) maps created from medically intractable epilepsy patients studied intracranially at Yale University and selected fMRI activation data. Our goal was to create anatomically precise boundaries of language function and support individualized planning for intracranial EEG (icEEG) studies and/or surgical resection. METHODS: A systematic search of DCS studies of language-related functions identified 12 stimulation studies (10 subdural, two stereo-EEG) that provided sufficiently clear surface visualizations for parcel-level mapping. Language-positive sites from six commonly tested functions (visual naming, auditory naming, naming (auditory/visual), reading, repetition and speech arrest) were manually co-registered to YBA parcels using conserved anatomical landmarks, facilitating topological comparison among similar language functions from the literature, Yale's electrical stimulation mapping cohort, and Neurosynth and Parcelsynth fMRI activation. RESULTS: Across 1182 patients, 176 YBA parcels (approximately 25% of cortical parcels) were implicated in at least one language task. Composite stimulation maps demonstrated robust consistency with the Yale DCS cohort and substantial overlap with distributed fMRI language networks. The resulting interactive maps provide parcel-level specificity while highlighting under-sampled but functionally critical regions. SIGNIFICANCE: The maps provide a review of language function determined through DCS and meta-analytic repositories of fMRI activation data. By consolidating stimulation-derived language data into a high-resolution parcellated atlas, this work offers a spatially detailed surface-based representation of language boundaries for surgical planning. The YBA facilitates standardized multimodal communication and allows patient-specific stimulation results to be interpreted within population-derived functional boundaries.

Epilepsia
Northwick Park Hospital (GB), Yale University (US), Danieli (Italy) (IT), Massachusetts Institute of Technology (US)
Swebilius Foundation, National Institutes of Health
Quality Education
Openalex Percentile: Top 29%
EEG and Brain-Computer Interfaces
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