Mapping epileptogenic brain using a unified spatial–temporal–spectral source imaging framework

X Xiyuan Jiang (Department of Biomedical Engineering, Carnegie Mellon University) Z Zhengxiang Cai (Department of Biomedical Engineering, Carnegie Mellon University) C Colton Gonsisko (Department of Biomedical Engineering, Carnegie Mellon University) G Gregory A. Worrell (Department of Neurology, Mayo Clinic) B Bin He (Max Planck Institute for Chemical Physics of Solids)

Abstract

Noninvasive electrophysiological source imaging (ESI) is a valuable tool for localizing and imaging brain activity, with significant potential to aid presurgical planning in focal drug-resistant epilepsy (fDRE) patients. Scalp electroencephalography (EEG) biomarkers, including interictal spikes, high-frequency oscillations (HFOs), and seizures, each offer unique capabilities in estimating the epileptogenic zone (EZ). However, there is a limited quantitative understanding of how these biomarkers differ in source-imaging precision, requiring distinct processing pipelines. Here, we developed a spatial–temporal–spectral imaging (STSI) framework for precision source imaging, and quantitatively evaluated various epilepsy biomarkers for source imaging in 2,081 individual events (spikes, HFOs, and seizures) from a cohort of 42 fDRE patients, comparing results to clinical ground truth such as surgical resection outcomes and intracranial EEG-defined seizure onset zones. The STSI enabled quantitative comparisons across key EEG epilepsy-related biomarkers, with averaged localization errors of 6.67 mm for seizures, 8.73 mm for HFOs overlapping with spikes (pHFO), 10.28 mm for HFO-riding spikes (pSpike), 19.59 mm for general spikes (aSpike), and 36.53 mm for general HFOs (aHFO), respectively, for seizure-free patients. These findings indicate that HFOs overlapping with spikes is the most spatially accurate interictal biomarker for mapping the EZ. The proposed STSI framework not only establishes a unified analysis approach for epileptic biomarkers to enhance presurgical planning in focal drug-resistant epilepsy, but could also generalize as a versatile tool for mapping event-related potentials, neural oscillations, and dynamic brain states, within a single framework to advance cognitive neuroscience research and clinical management of neurological and psychiatric disorders.

Article Details

Volume / Issue Vol. 122, Issue 50
Published December 16, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (5)

X

Xiyuan Jiang

Department of Biomedical Engineering, Carnegie Mellon University

Z

Zhengxiang Cai

Department of Biomedical Engineering, Carnegie Mellon University

C

Colton Gonsisko

Department of Biomedical Engineering, Carnegie Mellon University

G

Gregory A. Worrell

Department of Neurology, Mayo Clinic

B

Bin He

Max Planck Institute for Chemical Physics of Solids