# Neural dynamics of freely-moving, naturalistic behavior

> **NIH NIH F31** · STANFORD UNIVERSITY · 2024 · $48,974

## Abstract

Project Summary
 How does the brain support a repertoire of complex, natural movements? Motor systems neuroscience stud-
ies how neural dynamics in the motor system perform motor computations ranging from basic motor planning
and execution to more complex ones such as motor error correction or visuomotor adaptation that allow us to
reach our goals in a rich, changing world around us. To see how neural dynamics relate to these various mo-
tor computations, studies traditionally employ a constrained experimental environment where restrained subjects
perform virtual tasks through a computer screen and produce isolated arm reaches. This creates a generaliz-
ability question: how do neural dynamics studied in the lab relate to those of performing movements in the real
world? Underlying this question, there lies a more basic knowledge gap on how neural dynamics generalize for
performing the same computation but in different tasks or environments, such as in freely-moving environments.
This work aims to understand what is truly fundamental about motor cortical activity patterns for performing a
motor computation, regardless of task or environmental context. Aim 1 will obtain a grounded understanding
of how neural dynamics generalize for performing the same motor computation in different virtual tasks within
the traditionally constrained environment. Aim 2 then tackles the question of how neural dynamics generalize
for performing the same motor computation in a virtual task within the constrained environment to an analogous
naturalistic task within the freely-moving environment. This work leverages a freely-moving experimental platform
that acquires rich, synchronized behavioral data and neural data, combined with modeling of neural dynamics
to understand how neurons coordinate similarly when performing similar computations in different tasks and en-
vironments. Understanding how neural dynamics generalize from supporting artificially constrained behavior to
freely-moving, naturalistic behavior will be a key achievement in neuroscience with applications towards under-
standing how cortical control of natural motor functions go awry in people with stroke or brain injury and improving
assistive neurotechnologies, such as neural prosthetics, for those with motor disabilities. This work provides the
ideal opportunity to grow a diverse set of scientific, technical, and quantitative skills for career advancement
as an independent scientist, under the guidance of Dr. Nuyujukian who has multi-disciplinary expertise at the
intersection of neuroscience, medicine, and engineering. With the support from this fellowship, combined with
unparalleled access to cutting-edge techniques and well-furnished facilities with a thriving scientific community at
Stanford, this project is poised to succeed and make an impact in basic science and medicine.

## Key facts

- **NIH application ID:** 10998263
- **Project number:** 1F31NS139679-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Elizabeth Jun
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $48,974
- **Award type:** 1
- **Project period:** 2024-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10998263

## Citation

> US National Institutes of Health, RePORTER application 10998263, Neural dynamics of freely-moving, naturalistic behavior (1F31NS139679-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10998263. Licensed CC0.

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