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Investigation of Stereotyped High-Frequency Oscillations with Computational Intelligence for the Prediction of Seizure Onset Zone in Epilepsy

Award Number: R01NS112497
ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Investigation of Stereotyped High-Frequency Oscillations with Computational Intelligence for the Prediction of Seizure Onset Zone in Epilepsy - PROJECT SUMMARY Neurosurgical therapy of refractory epilepsy requires accurate localization of seizure onset zone (SOZ). In clinical practice, intracranial EEG (iEEG) is recorded in the epilepsy monitoring unit (EMU) over many days where multiple seizures are recorded to provide information to localize the SOZ. The prolonged monitoring in the EMU adds to the risk of complications and can include intracranial bleeding and potentially death. Recently, high frequency oscillations (HFO) of iEEG between 80 to 500 Hz are highly valued as a promising clinical biomarker for epilepsy. HFOs are believed to be clinically significant, and thus could be used for SOZ localization. However, HFOs can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, pathological HFOs are indistinguishable from physiological ones, which limit their application in epilepsy pre-surgical planning. In this proposal, to the best of our knowledge, we show of a recurrent waveform pattern that distinguishes pathological HFOs from physiological ones. In particular, we observed that the SOZ generates repeatedly a set of stereotyped HFO waveforms whereas the HFOs from nonepileptic regions were irregular in their waveform morphology. Based on these observations, using computational tools built on recent advances in sparse coding and unsupervised machine learning techniques, we propose to detect these stereotyped recurrent HFO waveform patterns directly from the continuous iEEG data of adult and pediatric patients and test their prognostic value by correlating the spatial distribution of detected events to clinical findings such as SOZ, resection zone and seizure freedom. We hypothesize that accurate detection of pathologic HFOs in brief iEEG recordings can identify the SOZ and eliminate the necessity of prolonged EMU monitoring and reduce the associated risks. With these motivations, in this project an interdisciplinary team composed of biomedical engineers, epileptologists and neurosurgeons will work together to develop and test novel computational tools to detect stereotyped HFOs and its subtypes in large iEEG datasets recorded with clinical electrodes. Developed algorithms and iEEG data will be shared with the research community to contribute to the reproducible research and help other research groups to develop novel methods. The results of this study will be essential for achieving our group's long term goal of developing an online neural signal processing system for the rapid and accurate identification of SOZ with brief invasive recording.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2023	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	6	5/2/2025	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2023	UNIVERSITY OF HOUSTON SYSTEM	4300 MARTIN LUTHER KING BLVD	HOUSTON	TX	77204	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	5	1/4/2024	NON-COMPETING CONTINUATION	-$459,230
2024	2023	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	001	6	1/4/2024	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$459,230
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $459,231 )
2023	2023	UNIVERSITY OF HOUSTON SYSTEM	4300 MARTIN LUTHER KING BLVD	HOUSTON	TX	77204	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	5	4/27/2023	NON-COMPETING CONTINUATION	$459,231
														Subtotal = $459,231

Issue Date FY: 2022 ( Subtotal = $459,231 )
2022	2022	UNIVERSITY OF HOUSTON SYSTEM	4800 W CALHOUN ST STE 316	HOUSTON	TX	77004	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	4/14/2022	NON-COMPETING CONTINUATION	$459,231
														Subtotal = $459,231

Issue Date FY: 2021 ( Subtotal = $459,231 )
2021	2021	UNIVERSITY OF HOUSTON SYSTEM	4800 W CALHOUN ST STE 316	HOUSTON	TX	77004	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	3	4/8/2021	NON-COMPETING CONTINUATION	$459,231
														Subtotal = $459,231

Issue Date FY: 2020 ( Subtotal = $459,252 )
2020	2020	UNIVERSITY OF HOUSTON SYSTEM	4800 W CALHOUN ST STE 316	HOUSTON	TX	77004	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	3/23/2020	NON-COMPETING CONTINUATION	$459,252
														Subtotal = $459,252

Issue Date FY: 2019 ( Subtotal = $488,027 )
2019	2019	UNIVERSITY OF HOUSTON SYSTEM	4800 W CALHOUN ST STE 316	HOUSTON	TX	77004	HARRIS	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	7/6/2019	NEW	$488,027
														Subtotal = $488,027

Grand Total All Awards = $2,324,972

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Investigation of Stereotyped High-Frequency Oscillations with Computational Intelligence for the Prediction of Seizure Onset Zone in Epilepsy

Award Number: R01NS112497

ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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