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New approach for identification pHFO networks to predict epileptogenesis

Award Number: R16NS131108
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: 07/15/2022
PERIOD OF PERFORMANCE END DATE: 06/30/2026

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New approach for identification pHFO networks to predict epileptogenesis - PROJECT SUMMARY Epilepsy is among the most common serious neurological disorders, and about 40% of epilepsy patients do not respond to existing treatment. Clinically, the prolonged, refractory epilepsy with negative surgical outcomes is often associated with distributed epilepsy onset rather than a local epileptogenic zone. Understanding the epilepsy as a large-scale brain network abnormality enables the development of new treatment options and research directions. At present, the majority of research related to analysis of the epileptic network has been focused on the ictal period, while few have been devoted to the analysis of the earlier stages of epileptogenesis (latent period). Investigating the brain network properties of epileptogenesis is as important and can help develop antiepileptogenic interventions for epilepsy prevention and cure. Early in our experiments, we discovered pathological high-frequency oscillations (pHFOs), which are reliable biomarkers of epileptogenesis. They are generated by clusters of pathologically interconnected neurons (PIN-clusters) and reflect bursts of population spikes. Recent updates in the animal models of chronic epilepsy evidenced the spatially distributed pHFO events, which implies the development of large-scale PIN-cluster networks during epileptogenesis. It is critical to study the network topology and characteristics of PIN-cluster-formed epileptogenic networks in order to further understand the underlying mechanisms of epileptogenesis. To fulfill this gap, the present study plan is to explore pHFO-based networks using the Kainic Acid (KA)- induced status epilepticus (SE) model of epileptogenesis. We hypothesize that epileptogenesis after SE is dependent upon the formation of large-scale PIN-cluster networks that is expressed by the spatial occurrence and temporal coupling of pHFOs. Combining the biocompatible, organic–material based neural interface array (NeuroGrid) with multichannel silicon probes, we aim to identify the spatial and temporal profiles of pHFOs (Aim1). Using the advanced computational algorithms such as graph theory analysis and Shannon Entropy (SE), we propose to investigate the causal relationship and characteristics of the pHFO-based epileptogenic networks (Aim2). The outcome of this study will assess the robustness of novel network-based recording design and algorithm development. It will also determine whether the pHFO-derived network parameters are a reliable biomarker of epileptogenesis. The future plans are to translate the pHFO-network concept and computational tools into the clinical study of epilepsy. This approach may open a new direction to the prevention of epilepsy development and cure epilepsy.


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: 2024 ( Subtotal = $180,025 )
2024	2024	UNIVERSITY OF NORTH TEXAS	1112 DALLAS DR STE 4000	DENTON	TX	76205	DENTON	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	3	6/12/2024	NON-COMPETING CONTINUATION	$180,025
														Subtotal = $180,025

Issue Date FY: 2023 ( Subtotal = $180,025 )
2023	2023	UNIVERSITY OF NORTH TEXAS	1155 UNION CIR #305250	DENTON	TX	76203	DENTON	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	6/20/2023	NON-COMPETING CONTINUATION	$180,025
														Subtotal = $180,025

Issue Date FY: 2022 ( Subtotal = $180,025 )
2022	2022	UNIVERSITY OF NORTH TEXAS	1155 UNION CIR #305250	DENTON	TX	76203	DENTON	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	7/14/2022	NEW	$180,025
														Subtotal = $180,025

Grand Total All Awards = $540,075

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New approach for identification pHFO networks to predict epileptogenesis

Award Number: R16NS131108

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: 07/15/2022

PERIOD OF PERFORMANCE END DATE: 06/30/2026

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