# From Social Networks to Neural Networks: Investigating the Neural Basis of Real-Life Social Relationships

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2021 · $409,154

## Abstract

PROJECT SUMMARY
Social relationships develop between individuals with a social network. Difficulties in mediating social
relationships with other individuals is strongly associated with severe mental disorders ranging from
depression, chronic stress, autism and other. Thus, understanding the neural underpinning of social
relationships is paramount. To gain insight that would inform of real-life behavior, I propose to study the
nervous system under real-life conditions in which social interactions in humans and animals typically occur. In
particular, I focus on the fact that social interactions typically involve multiple participants, employ the usage of
a flexible repertoire of communication signals, and occur between individuals of varying social bonds and
personality traits. Furthermore, social relationships evolve over prolonged periods of time in a dynamic fashion.
In this proposal we focus on the anterior cingulate cortex (ACC). We do so because activity in this area has
previously been strongly associated with social behaviors across a wide range of mammalian species,
including humans. However, much less is known about the neural computations in the ACC with respect to
social relationships, especially during real-life and multi-dimensional social conditions. To do so, we use the
Egyptian fruit bat, a highly social, long-lived mammal that is accustom to group living and where individuals
engage in relationships that extend over many months/years. We further develop advanced behavioral
measurements that allow us to monitor the social interactions of individuals within our colonies continuously
and characterize their social relationships between group members. To study the neural circuits that underlie
social relationships we develop wireless neurophysiological tools that enable monitoring neural activity from
entire colonies of bats simultaneously at cellular and millisecond resolutions (electrophysiology) and over
prolonged periods of time (calcium imaging). This novel approach allows us to consider the true complexity of
real-life social interactions and consider the social bonds between the individuals, the dynamic structure of the
social relationships as well as the individual variability in personality traits. Specifically, we aim to achieve the
following aims: (1) We start by describing the basic neural dynamics in the ACC during semi-natural, dyadic,
social interactions and communication. (2) We next describe the ACC neural dynamics during interaction
occurring within real-life, stable, social networks while considering the relationships between individuals (3) We
describe the evolution of ACC neural dynamic in parallel to the dynamical changes that occur in real-life social
networks. (4) We use optogenetics tools to disrupt neural activity in the ACC during group social interactions in
order to assess its causal role in real-life social relationships with other individuals. Combined, these
experiments will provide a detailed descripti...

## Key facts

- **NIH application ID:** 10126466
- **Project number:** 1R01MH125387-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Michael Moshe Yartsev
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $409,154
- **Award type:** 1
- **Project period:** 2021-05-07 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10126466

## Citation

> US National Institutes of Health, RePORTER application 10126466, From Social Networks to Neural Networks: Investigating the Neural Basis of Real-Life Social Relationships (1R01MH125387-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10126466. Licensed CC0.

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