# Large-scale recording of population activity during social cognition in freely moving non-human primates

> **NIH NIH U01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2020 · $524,787

## Abstract

PROJECT SUMMARY/ABSTRACT
Social interactions, a ubiquitous aspect of our everyday life, are critical to the health and survival of the species,
but little is known about their underlying neural computations. The major limitation preventing our understanding
of the neural underpinnings of social cognition is the lack of a suitable framework to allow us to study how it
emerges in real time from interactions among brain networks. Indeed, examining the neural bases of complex
social interactions has been traditionally performed by studying the brain of nonhuman primates in a laboratory
environment in which the head and body are restrained while synthetic stimuli are presented on a computer
monitor. However, it has become increasingly understood that studying the brain in spatially confined, artificial
laboratory rigs poses severe limits on our capacity to understand the function of brain circuits. To overcome
these limitations, we propose a novel approach to understand the neural underpinnings of social cognition. We
will use a high-yield wireless system to study the cortical dynamics and plasticity of social interactions by
recording population activity in multiple visual, temporal, and prefrontal cortical areas while nonhuman primates
are interacting freely with their environment and with other animals. This new approach will enable us to uncover
the dynamics of neuronal network activity that drives social interactions in an ethologically relevant behavioral
task that involves sensory integration, memory, and complex decision-making. Our integrative project brings
together innovative brain recording technologies and microelectronics together with large data sets analysis
techniques. Our proposed research will constitute a paradigm shift by moving social neuroscience – from simply
observing animal behavior and recording the responses of single cells – to a quantitative understanding of the
distributed neuronal network encoding during social behavior in freely moving nonhuman primates performing
rich naturalistic tasks. We anticipate that the large quantity of neural data recorded using our approach will be of
great interest to clinicians and computational neuroscientists studying general properties of normal and
dysfunctional neural networks, possibly leading to medical insights into the mechanisms of autism and attention
deficit disorders that impair social interactions.

## Key facts

- **NIH application ID:** 9977287
- **Project number:** 5U01NS108680-03
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** Behnaam Aazhang
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $524,787
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9977287

## Citation

> US National Institutes of Health, RePORTER application 9977287, Large-scale recording of population activity during social cognition in freely moving non-human primates (5U01NS108680-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9977287. Licensed CC0.

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