This study explored methods to distinguish glioma tumor tissue from the surrounding peritumoral cortex, which may appear normal on conventional imaging yet have some characteristics of tumor progression. The researchers employed intraoperative electrocorticography (ECoG) to record electrical activity from 718 cortical electrodes in 29 patients undergoing glioma resection, whole tumor, peritumoral, and healthy brain regions. Analysis of ECoG data revealed pronounced differences in neural activity across tissue types. Tumor regions exhibited elevated slow-wave (delta) activity alongside reduced higher-frequency (beta and gamma) signals, whereas peritumoral cortex, particularly areas immediately adjacent to the tumor, displayed intermediate electrophysiological patterns indicative of early infiltration. Importantly, many glioma patients experience seizures, and ECoG detected seizure-related activity not only within tumor tissue but also in the peritumoral cortex. This demonstrates how the peritumoral cortex can appear normal on imaging yet be involved with tumor-induced symptoms such as seizures. Computational models trained on these ECoG-derived features were able to distinguish tumors from healthy tissue with approximately 70% accuracy, underscoring the potential of intraoperative electrophysiology as a diagnostic and surgical guidance tool.