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Related Concept Videos

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Related Experiment Video

Updated: May 8, 2026

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
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Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

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

Xiyuan Jiang1, Zhengxiang Cai1, Colton Gonsisko1

  • 1Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.

Proceedings of the National Academy of Sciences of the United States of America
|December 8, 2025
PubMed
Summary
This summary is machine-generated.

High-frequency oscillations overlapping with spikes offer the most precise noninvasive localization of the epileptogenic zone in drug-resistant epilepsy. This finding enhances presurgical planning by improving brain imaging accuracy for epilepsy patients.

Keywords:
EEGepilepsyinterictal biomarkersource imagingsource localization

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Epileptology

Background:

  • Noninvasive electrophysiological source imaging (ESI) is crucial for localizing brain activity in focal drug-resistant epilepsy (fDRE).
  • Various scalp electroencephalography (EEG) biomarkers like spikes and high-frequency oscillations (HFOs) are used to estimate the epileptogenic zone (EZ), but their comparative precision is not well understood.
  • Distinct processing pipelines are often required for different biomarkers, limiting quantitative comparisons.

Purpose of the Study:

  • To develop a unified spatial-temporal-spectral imaging (STSI) framework for precise source imaging of epilepsy biomarkers.
  • To quantitatively evaluate and compare the source-imaging precision of different EEG biomarkers (spikes, HFOs, seizures) in fDRE patients.
  • To establish a more accurate method for presurgical planning in fDRE.

Main Methods:

  • Developed and applied a novel spatial-temporal-spectral imaging (STSI) framework.
  • Analyzed 2,081 individual epilepsy events (spikes, HFOs, seizures) from 42 fDRE patients.
  • Compared source imaging results against clinical ground truth, including surgical resection outcomes and intracranial EEG-defined seizure onset zones.

Main Results:

  • The STSI framework enabled quantitative comparisons of localization errors for various biomarkers.
  • Seizures showed the lowest localization error (6.67 mm), followed by HFOs overlapping with spikes (pHFO, 8.73 mm) and HFO-riding spikes (pSpike, 10.28 mm).
  • General spikes (aSpike, 19.59 mm) and general HFOs (aHFO, 36.53 mm) exhibited larger localization errors in seizure-free patients.

Conclusions:

  • HFOs overlapping with spikes represent the most spatially accurate interictal biomarker for mapping the epileptogenic zone.
  • The STSI framework provides a unified approach for analyzing epileptic biomarkers, enhancing presurgical planning for fDRE.
  • The STSI framework has broader potential applications in cognitive neuroscience and clinical management of neurological disorders.