Scalp EEG predicts intracranial brain activity in humans.

ABSTRACT: Inferring deep brain activity from noninvasive scalp recordings remains a fundamental challenge in neuroscience. Here, we analyzed concurrent scalp and intracranial recordings from 1918 electrode contacts across 20 patients affected by drug-resistant epilepsy undergoing intracranial depth electrode monitoring for pre-surgical evaluation to establish predictive relationships between surface and deep brain signals. Using regularized and cross-validated linear regression within subjects, we demonstrate that scalp recordings can predict spontaneous intracranial activity, with accuracy varying by region, depth, and frequency. Low-frequency signals (<12 Hz) were most predictable, with our models explaining approximately 10% of intracranial signal variance across contacts. Prediction accuracy dec

SUBMITTER: Subramanian AK 

PROVIDER: S-EPMC12026988 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature