Electrocorticographic Detection of Speech Networks in Glioma-infiltrated Cortex

Direct cortical stimulation (DCS) is the clinical gold standard for identifying functional cortex in the human brain, which is essential for the safe removal of brain lesions. Defining the electro-physiological properties of DCS-positive cortical regions may facilitate the identification of critical language regions, thereby permitting safe glioma resections in communities without access. Leveraging a multicenter electrophysiologic dataset of DCS-positive language regions spatially matched with subdural arrays, we analyzed regions identified as functionally critical (DCS+) versus functionally non-critical (DCS-) during intraoperative language mapping. In IDH-mutant gliomas, DCS+ regions exhibited significantly greater speech-related neural activity and enhanced encoding and decoding of linguistic and semantic features. We demonstrate that resting-state classifiers distinguish DCS+ from DCS- regions in IDH-mutant tumors. Task-based and resting-state electrophysiologic distinctions were pathology-specific and not present in IDH-wildtype glioblastomas. These findings may accelerate DCS mapping by guiding surgeons to priority regions, improving efficiency, and patient outcomes.