# Circuit basis of social behavior decision-making in a subcortical network

> **NIH NIH R01** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2022 · $580,587

## Abstract

Project Summary/Abstract
 This proposal responds to an FOA (RFA-NS-18-030) calling for 1) “novel approaches to understand neural
circuitry associated with well-defined social behaviors;” 2) Distributed circuits that contribute to the coordination
of motivational states and reward behavior;” 3) “Empirical and analytical approaches to understand how
behavioral states are emergent properties of the interaction of neurons, circuits and networks.” The study of
subcortical circuits that control conserved, naturalistic behaviors is crucial to understanding brain function. We
aim to understand how dynamic interactions between different circuit nodes in the Hypothalamic-Extended
Amygdala Decision (“HEAD”) network control innate social behavior decisions, e.g., between aggressive and
reproductive behaviors. We propose an integrated approach to this problem that combines microendoscopic
imaging (MEI) of genetically identified neuronal subpopulations with automated, machine learning-based
classification of social behavior in freely moving mice, together with functional perturbations of neuronal activity
in vivo. Our broad, long-term objective is to understand how distributed activity among interconnected
structures in the HEAD network controls moment-to-moment decisions between competing goal-directed
behaviors that are crucial for the survival of animals and humans. The central objective of this proposal is to
understand how information flows through this network during social interactions, and is decoded to control the
decision to engage in reproductive vs. aggressive social behaviors. To understand how activity in “upstream”
nodes controls neural representations in “downstream” nodes, we will implement a novel approach combining
reversible chemogenetic inhibition of the former with concurrent imaging of neuronal population activity in the
latter. The rationale for this approach is that an understanding of the system requires characterizing the effects
of functional manipulations on both behavioral and circuit-level phenotypes. To achieve our objective, we will
first characterize the neural coding of behavior and conspecific sex identity in multiple nodes of the extended
amygdala, using single-site microendoscopic imaging and computational analytic approaches (Aim 1);
determine how perturbations in the activity of such nodes influence representations in hypothalamic nodes
(Aim 2); investigate the roles of intra- and inter-nuclear interactions in determining the balance of activity
between aggression and reproduction-promoting hypothalamic nodes (Aim 3); determine how this balance is
decoded by downstream mid-brain structures to determine the type of social behavior to express (Aim 4). This
contribution is significant because it represents a systems-level approach to understanding how a subcortical
network controls behavioral decision-making. The contribution is innovative because it integrates analysis of
neuronal population activity, quantitative measurem...

## Key facts

- **NIH application ID:** 10461937
- **Project number:** 5R01NS123916-02
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** David J Anderson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $580,587
- **Award type:** 5
- **Project period:** 2021-08-15 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10461937

## Citation

> US National Institutes of Health, RePORTER application 10461937, Circuit basis of social behavior decision-making in a subcortical network (5R01NS123916-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10461937. Licensed CC0.

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