Sandeep Robert Datta, MD, PhD - US grants

There are 65 million people worldwide with epilepsy and 150,000 new cases of epilepsy are diagnosed in the US annually. However, treatment options for epilepsy remain inadequate, with many patients suffering from treatment-resistant seizures, cognitive comorbidities and the negative side effects of treatment. A major obstacle to progress towards the development of new therapies is the fact that preclinical epilepsy research typically requires labor-intensive and expensive 24/7 video-EEG monitoring of seizures that rests on the subjective scoring of seizure phenotypes by human observers (as exemplified by the widely used Racine scale of behavioral seizures). Recently, the Datta lab showed that complex animal behaviors are structured in stereotyped modules (?syllables?) at sub-second timescales and arranged according to specific rules (?grammar?). These syllables can be detected without observer bias using a method called motion sequencing (MoSeq) that employs video imaging with a 3D camera combined with artificial intelligence (AI)-assisted video analysis to characterize behavior. Through collaboration between the Soltesz and Datta labs, exciting data were obtained that demonstrated that MoSeq can be adapted for epilepsy research to perform objective, inexpensive and automated phenotyping of mice in a mouse model of chronic temporal lobe epilepsy. Here we propose to test and improve MoSeq further to address long-standing, fundamental challenges in epilepsy research. This includes the development of an objective alternative to the Racine scale, testing of MoSeq as an automated anti-epileptic drug (AED) screening method, and the development of human observer- independent behavioral biomarkers for seizures, epileptogenesis, and cognitive comorbidities. In addition, we plan to dramatically extend the epilepsy-related capabilities of MoSeq to include the automated tracking of finer-scale body parts (e.g., forelimb and facial clonus) that are not possible with the current approach. Finally, we propose to develop the analysis pipeline for MoSeq into a form that is intuitive, inexpensive, user-friendly and thus easily sharable with the research community. We anticipate that these results will have a potentially transformative effect on the field by demonstrating the feasibility and power of automated, objective, user- independent, inexpensive analysis of both acquired and genetic epilepsy phenotypes.

Acute intoxication with organophosphorus (OP) pesticides is a significant public health concern and long-term neurological effects are not well understood. A major obstacle to progress towards reproducible, rigorous preclinical research in the long-term effects of OP- induced status epilepticus is that current experimental approaches often require prohibitively time and labor-intensive 24/7 video-EEG monitoring and inherently subjective scoring of seizures by human observers (like the widely used Racine scale). While algorithms for automated seizure detection in EEG are improving, the critically important behavioral manifestations of acquired epilepsy and assessment of its cognitive comorbidities remain poorly quantified. Our parent grant focuses on developing an objective, high-throughput technique to characterize epileptic phenotypes using a new method called motion sequencing (MoSeq) and apply it to automated anti-epileptic drugs (AED) screening. The central idea of MoSeq rests on the discovery that complex animal behaviors are structured in stereotyped modules (?syllables?) at sub-second timescales that are arranged according to specific rules (?grammar?) that can be detected without observer bias by artificial intelligence (AI)-assisted 3D video analysis. In this administrative supplement project, we propose to employ and refine MoSeq to address key challenges in research into the development of new medical countermeasures (MCM) against nerve agents and OP pesticides. This includes testing if it is possible to objectively study the long-term effects of OP intoxication and evaluate MCMs at scale by determine epilepsy-specific behavioral modules and associated transition probabilities in mice after acute OP exposure. In addition, given that neuroinflammation is likely to play a key role in OP-induced persistent neuronal circuit disturbance, we will test if microglial depletion can rescue the OP-induced chronic changes in behavioral syllables and transition probabilities. Together, the aims in this administrative supplement will both benefit from and contribute to our parent grant?s goal to develop a reliable, sharable tool for the research community to study seizures and cognitive comorbidities of epilepsy.