# Identifying, manipulating, and studying a complete sensory-to-motor model behavior circuit

> **NIH NIH R01** · SCRIPPS RESEARCH INSTITUTE, THE · 2021 · $100,000

## Abstract

PROJECT SUMMARY
We are requesting supplemental funds to obtain and apply transformative, recently validated
methods to identify and study the neural correlates of behavior. How does the brain transform
sensory information into complex behavior? The objective of the parent proposal is to identify
the relevant neurons across the brain that are necessary to produce a relatively simple
motivated behavior to study and identify fundamental principles underlying coding. Sensory-to-
behavior circuits contain a variety of neural computations such as those that determine the
identity and meaning of the sensed cues, gauge internal state, remember previous experience,
and command muscle action. In the parent proposal we aim to identify and study an entire
circuit from sensation across the brain to motor output. The original RFA called for the ability to
leverage and study neural dynamics. At the time of the funding of the parent grant, we proposed
to monitor brain-wide activity using cFos as a proxy, however this only provides a snapshot of
an instant of brain activity in post-mortem animals. We complemented this approach with in vivo
imaging of GCaMP activity by fiber photometry in awake behaving animals. This method reveals
neural dynamics over seconds but is limited to image a small subset of the brain. Though these
methods were state of the art at the time, they are both low through-put to implement and do not
provide neural dynamics across the whole brain. Recently, functional ultrasound imaging (fUSi)
has been validated to report dynamic images of the entire mouse brain (4 times/second) with a
resolution of at least 100um. Dynamic, whole brain, high resolution imagine is truly
transformative. fUSi is relatively easy and low-cost which will reduce resources including
personnel, animals, and time. It will not just be faster and easier; we will learn more. We expect
the additional information provided by fUSi to increase the confidence and scope of our
conclusions. This will enable unprecedented activity profiles to inform all of our original aims
including identifying key neural circuits and nodes, information flow within nodes and across the
brain, and the change in activity with development and experience in and across individuals.
Moreover, dynamic brain wide activity correlated with behavior will increase our ability to
generate reliable models of information coding. Better models are expected to provide new,
testable hypothesis that will benefit our understanding of information coding of sensory and
social behavior and of brain function in general. An administrative supplement to implement this
approach will result in more rapid achievement of our aims and better facilitate the goals of the
initial RFA.

## Key facts

- **NIH application ID:** 10449063
- **Project number:** 3R01NS108439-04S1
- **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE
- **Principal Investigator:** LISA STOWERS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $100,000
- **Award type:** 3
- **Project period:** 2018-09-30 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10449063

## Citation

> US National Institutes of Health, RePORTER application 10449063, Identifying, manipulating, and studying a complete sensory-to-motor model behavior circuit (3R01NS108439-04S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10449063. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*