# Network analysis for epilepsy surgery

> **NIH NIH R01** · YALE UNIVERSITY · 2022 · $366,406

## Abstract

PROJECT SUMMARY
Accurate localization of the seizure onset area in patients with medically refractory focal epilepsies is crucial for
successful neurosurgical treatment using interventions such as tissue resection, laser ablation and brain
stimulation. However, current localization approaches have serious shortcomings because they are time-
consuming, expensive, qualitative and do not necessarily lead to seizure control. To overcome this hurdle, we
propose to validate a novel and powerful approach, termed brain interictal network mapping – BINMAP – by
which a brief segment of the brain’s interictal (background) activity will be used to first establish a frequency
band-specific functional connectivity map and then this map will be used to accurately delineate the seizure
onset area in focal epilepsies. The objective here is to validate the BINMAP approach in patients with different
types of focal epilepsies and rodent models of focal neocortical epilepsy. The central hypothesis is that
BINMAP will delineate the seizure onset area more effectively and accurately than current approaches and
reduce the cost and patient discomfort and improve the outcome of epilepsy surgery. The first aim of the
project is to optimize and validate BINMAP in 120 patients with neocortical and mesial temporal lobe
epilepsies. The method will be conducted on the interictal intracranial electroencephalogram (icEEG) and
scalp EEG, sampled at multiple time points during continuous, up to 2-week long, inpatient monitoring
procedures. The second aim will be to use two established rodent models of focal neocortical epilepsy, to
understand the mechanisms underlying the development of both a biomarker for post-lesion epilepsy and the
functional connectivity detected by BINMAP. To this end, discrete epileptogenic lesions will be created in the
neocortex of rats, followed by BINMAP monitoring of the epileptogenic process. The research is innovative for
two reasons. First, it uses a brief segment of interictal icEEG, versus seizure recordings obtained over several
days of continuous long-term monitoring, to delineate the seizure onset area in patients with epilepsy. Second,
it aims to understand the mechanism underlying the development of functional connectivity in focal neocortical
epilepsies during epileptogenesis. The expected outcome of this study will both help elucidate the network
changes which accompany epileptogenesis and transform the way clinicians locate the seizure onset area by
replacing expensive and time-consuming icEEG recordings with analysis of interictal icEEG. If successful, this
project will have a high translational impact because it will dramatically reduce the cost and increase the
accuracy of seizure onset area localization, thereby lowering health expenses and increasing the success of
epilepsy surgery.

## Key facts

- **NIH application ID:** 10375413
- **Project number:** 5R01NS109062-04
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** TORE EID
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $366,406
- **Award type:** 5
- **Project period:** 2019-07-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10375413

## Citation

> US National Institutes of Health, RePORTER application 10375413, Network analysis for epilepsy surgery (5R01NS109062-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10375413. Licensed CC0.

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