A framework for quality assurance in human intracranial electrophysiology

Abstract

Intracranial electroencephalography (iEEG) provides an unprecedented opportunity to directly record neural activity and causally perturb the human brain through electrical stimulation. Yet, the increasingly collaborative nature and complexity of modern iEEG studies pose substantial challenges for experimental control, data quality, and standardization. Unlike most experimental modalities, human iEEG data are acquired within dynamic clinical environments, where patient condition, recording quality, hardware configuration, and experimental protocols may vary across recording sessions and collaborating sites. The resulting heterogeneity creates opportunities for technical and procedural failures that often remain undetected until downstream analyses, when corrective action is no longer possible. Here, we present a framework for standardized session-level quality assurance in human iEEG research and provide an open-source implementation compatible with Brain Imaging Data Structure (BIDS)-organized datasets. The framework defines four complementary domains of quality assessment crucial for human iEEG studies: protocol fidelity, behavioral integrity, stimulation validation, and signal quality. These domains integrate electrophysiological recordings, behavioral event logs, and stimulation metadata to verify data completeness, confirm participant engagement, validate stimulation delivery, and identify potentially compromised recording channels. Automated quality metrics and standardized diagnostic visualizations are generated following each testing session, enabling rapid identification of technical and procedural failures while corrective action is still possible. By providing a standardized approach to session-level quality assurance, the framework improves data integrity, enhances reproducibility, facilitates analyst training, and supports harmonized data collection across laboratories and clinical sites.