# Closed-loop control of neural dynamics and action selection in C elegans

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $42,534

## Abstract

Project Summary/Abstract
 In response to new sensory stimuli, an animal must decide what to do next. Escape behaviors
are excellent models with which to study the neurobiological basis of behavior because they are
essential and interpretable. Here we propose to study neural factors which influence a probabilistic
behavior where C. elegans escapes stimulation of an aversive sensory neuron ASH. Specifically we
will determine how much variance in behavior is accounted for by ongoing global neural dynamics i.e.
time-varying patterns of activity which encode major behaviors such as forward, backward, dorsal, and
ventral crawling. During dynamics, a given neuron receives different levels of excitation and inhibition
from its synaptic partners, which may contribute to behaviors seeming probabilistic.
 During whole-brain imaging with cellular resolution to access the activity of the entire brain of
the animal simultaneously, we will optogenetically stimulate neurons during signatures of activity
correlated with crawling behaviors using a closed-loop calcium imaging quantification and optogenetic
stimulation platform to perturb dynamics. We will characterize how stimulus intensity and dynamics
interact to activate sensory and downstream neurons. We will also examine a variable forward or
reversal behavior which emerges when worms are disturbed from a state with no obvious dynamics,
sleep. We will characterize how neurons respond to different intensities of stimulation and fit physiology
data to a model relating activation function and action selection.
 Taken together these experiments use a simple animal model to shed light on how evoked
neuronal activity is modulated by ongoing patterns throughout the network. These experiments
emphasize a distributed view of sensory and motor representations and explore its implications on
dynamics in a highly interconnected nervous system. This research and training plan in this proposal
is decidedly hybrid experimental and computational, necessarily guided by two leaders in each
discipline at the famously collaborative University of California, San Francisco.

## Key facts

- **NIH application ID:** 10240513
- **Project number:** 5F31NS115572-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Raymond Lake Dunn
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $42,534
- **Award type:** 5
- **Project period:** 2019-09-18 → 2022-09-17

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10240513

## Citation

> US National Institutes of Health, RePORTER application 10240513, Closed-loop control of neural dynamics and action selection in C elegans (5F31NS115572-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10240513. Licensed CC0.

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