Biomarkers for Nocturnal Epileptiform Discharges in Children with Autism
Abstract
Background and Focus Areas: In the absence of seizures, interictal epileptiform discharges (IED) have been found in up to 60% of children diagnosed with ASD. There is evidence that IEDs can cause lasting language, cognitive, motor, and behavioral impairments, as well as an increased risk to develop epilepsy. But the risks of IEDs are understudied because we lack easy techniques to screen children with ASD for IEDs. Our preliminary research suggests that that IEDs may result from abnormal brain dynamics that can be measured and characterized by analysis of short segments of electroencephalograms (EEG) taken while a child is awake using advanced computer algorithms. Three areas of particular interest to the FY22 ARP Idea Development Award program are addressed in this project: 1. Mechanisms of heterogeneous clinical expression of ASD. We believe that a subgroup of ASD will have IEDs as predicted by low complexity wake EEG signals. This may present a profile of an ASD subgroup helpful for future development of personalized treatment. 2. Mechanisms underlying conditions co-occurring with ASD: seizures. The centrality of seizure or abnormal electrical activity in ASD remains unknown. What is known is that a large number of people with ASD suffer from comorbid epilepsy. This project will contribute to that understanding by computing dynamical parameters and comparing ASD patients with and without IEDs. 3. Create tools to increase the speed with which evidence-based practices are deployed in community-based settings. If successful, our screening method could be deployed in primary care settings, convenient to the families, and analyzed automatically with our algorithms, providing a universal screening tool that will enable timely, personalized care. Impact: The result of this project could immediately provide methods to test personalized treatment approaches that improve cognitive or behavioral symptoms and reduce epilepsy risk in children with ASD. It is likely that treatment of IEDs, which can also be monitored with our methods, will lead to new research opportunities and therapies. EEG screening could ascertain a subgroup of ASD which could lead to personalized treatment and prevention analogous to a lab test to guide treatment decisions. Innovation: This project is based on a conception of the brain as a complex dynamical system. Our approach to analyzing this system uses a novel integration of multiscale, nonlinear signal analysis, together with novel machine learning based on supervised tensor factorization. The result is a computational framework for personalized therapeutic monitoring of children with ASD. Together, these advanced computational tools promise to detect IEDs, provide insight into the neurophysiology of these abnormal brain electrical activities, and provide biomarkers to monitor therapy or developmental trajectories.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310333
Entities
People
- William Bosl
Organizations
- United States Army
- University of San Francisco