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Imaging Epilepsy Sources with Biophysically Constrained Deep Neural Networks

Award Number: R01NS127849
ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 06/15/2023
PERIOD OF PERFORMANCE END DATE: 05/31/2027

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Imaging Epilepsy Sources with Biophysically Constrained Deep Neural Networks - Project Summary The goal of this project is to develop and validate a novel electrophysiological source imaging (ESI) approach based on biophysically constrained deep neural networks (BioDNN), to significantly improve surgical planning in drug resistant focal epilepsy patients. Epilepsy affects about 70 million people worldwide. For approximately 33% of the 3.4 million Americans with epilepsy, seizures are not controlled by medications alone. Epilepsy surgery is the most viable option for curing drug resistant focal epilepsy, only if seizure sources can be accurately localized and safely removed. There is a clinical need to innovate technological tools for better surgical planning of focal epilepsy. We propose in this project a novel ESI technology based on biophysically constrained deep neural network (BioDNN) to provide accurate, robust, and objective spatio-temporal estimates of the underlying epileptogenic zone (EZ). Of innovation is that the trained neural network, is capable of imaging brain sources without the need to tune the model’s hyper-parameters by an operator for every new instance of data, thus making the technique objective and easy-to-use in clinical settings. Our specific aims are: Aim 1. Establishing and Validating the BioDNN for Imaging Epileptogenic Tissue from EEG Inter-ictal Epileptiform Discharges (IEDs) of Focal Epilepsy Patients. We will establish, optimize and validate the proposed BioDNN for imaging EZ from IEDs in EEG in 200 focal drug resistant epilepsy (DRE) patients, in comparison to clinical “ground truth . Aim 2. Developing and Validating the BioDNN Model for Imaging Epileptogenic Tissue from MEG Inter-ictal Epileptiform Discharges of Focal Epilepsy Patients. We will develop and optimize the BioDNN model for imaging EZ from MEG IEDs and validate the MEG-BioDNN model and compare with the EEG-BioDNN model in 80 focal DRE patients in comparison to clinical “ground truth. Aim 3. Developing and Validating the BioDNN Model for Imaging Epileptogenic Tissue from Ictal EEG of Focal Epilepsy Patients. We will develop the BioDNN for imaging the SOZ from scalp ictal EEG and validate it from high density ictal EEG recordings in 120 focal DRE patients, in comparison to clinical “ground truth”. The successful completion of the proposed research will establish a novel machine learning technology to non-invasively localize and image underlying epileptogenic tissue from interictal and ictal electrophysiological biomarkers. The establishment of such a novel technology promises to significantly improve the precision of intracranial EEG electrodes implantation and aid surgical planning, leading to significant improvement in surgical outcomes, and benefiting numerous drug resistant epilepsy patients. 1


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 = $601,854 )
2025	2025	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	3	5/1/2025	NON-COMPETING CONTINUATION	$601,854
														Subtotal = $601,854

Issue Date FY: 2024 ( Subtotal = $585,640 )
2024	2024	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	7/18/2024	NON-COMPETING CONTINUATION	$585,640
														Subtotal = $585,640

Issue Date FY: 2023 ( Subtotal = $644,041 )
2023	2023	CARNEGIE MELLON UNIVERSITY	5000 FORBES AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	6/9/2023	NEW	$644,041
														Subtotal = $644,041

Grand Total All Awards = $1,831,535

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Imaging Epilepsy Sources with Biophysically Constrained Deep Neural Networks

Award Number: R01NS127849

ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 06/15/2023

PERIOD OF PERFORMANCE END DATE: 05/31/2027

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