# CRCNS: Dynamical Constraints on Neural Population Activity

> **NIH NIH R01** · CARNEGIE-MELLON UNIVERSITY · 2021 · $411,479

## Abstract

Cognition and behavior unfold over time. The temporal aspects of thought and action reflect, at least in part,
the temporal evolution of the activity of the populations of neurons that control them. It has long been
hypothesized that the time course of neural activity arises from dynamical constraints imposed by the
underlying neural circuitry. However, this has been difficult to show experimentally because it requires the
ability to finely perturb neural activity in varied ways. Here, we propose to employ a brain-computer interface
(BCI) paradigm to study neural dynamics. A BCI enables us to perturb neural activity by harnessing the
animal's volitional control to drive the activity of a population of neurons into configurations that we specify.
In this way, we can perform causal tests of dynamical constraints and their relation to behavior. We will
study dynamical constraints imposed by motor preparation using multi-neuronal activity recorded in the
motor cortex of macaque monkeys. We hypothesize that dynamical constraints exist in the motor cortex,
and that these constraints are shaped during motor preparation to drive arm movements. To test these
hypotheses, we will first challenge the animals to violate the putative dynamical constraints. Then, we will
test the hypothesis that motor preparation sets up dynamical constraints appropriate for the upcoming arm
movement. Finally, we will use the BCI paradigm to perturb neural activity during movement preparation to
alter and evoke arm movements. Taken together, our proposed work will likely lead to a richer
understanding of how networks of neurons give rise to population dynamics, and how those dynamics relate
to neural computation and behavior.

## Key facts

- **NIH application ID:** 10145807
- **Project number:** 5R01NS105318-05
- **Recipient organization:** CARNEGIE-MELLON UNIVERSITY
- **Principal Investigator:** Aaron Paul Batista
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $411,479
- **Award type:** 5
- **Project period:** 2017-07-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10145807

## Citation

> US National Institutes of Health, RePORTER application 10145807, CRCNS: Dynamical Constraints on Neural Population Activity (5R01NS105318-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10145807. Licensed CC0.

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