# CounterAct Administrative Supplement to NS114020 Automated Phenotyping in Epilepsy

> **NIH NIH R01** · STANFORD UNIVERSITY · 2021 · $123,798

## Abstract

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.

## Key facts

- **NIH application ID:** 10227611
- **Project number:** 3R01NS114020-02S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Sandeep R Datta
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $123,798
- **Award type:** 3
- **Project period:** 2020-10-01 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10227611

## Citation

> US National Institutes of Health, RePORTER application 10227611, CounterAct Administrative Supplement to NS114020 Automated Phenotyping in Epilepsy (3R01NS114020-02S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10227611. Licensed CC0.

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