# Mapping Neural Dynamics in Hormone-sensitive Networks

> **NIH NIH K99** · PRINCETON UNIVERSITY · 2024 · $135,989

## Abstract

Project Summary/Abstract
Deciding to self-initiate social interaction (i.e., proactive social behavior) depends on many variables: the social
context, our social partner, and our hormonal state. Gonadal hormones impact social behavior primarily by
regulating neural gene expression across a network of interconnected, subcortical brain regions. Further,
behavior itself can lead to changes in hormone levels, indicating behavior and hormonal state exist in an ongoing
feedback loop. Many mood disorders, such as depression and anxiety, exhibit profound sex differences, which
relate to hormonal state and interact with social behavior dysfunction. Critically, proactive social behavior can
increase resiliency to these disorders. Unraveling the neuroendocrine mechanisms that promote proactive social
behavior is a critical step toward identifying the etiology of mood disorder-associated social dysfunction.
Recent work by the candidate demonstrates two neural populations of this subcortical network interact to
regulate the proactive seeking of social interaction. However, we do not know how hormone-sensitive
populations across this distributed network interact to encode proactive social behavior and related social
variables (context, partner), nor do we understand the impact of hormonal change on this encoding. The goal
of this proposal is to comprehensively map the influence of gonadal hormones on network-level coding of
proactive social behavior and related variables (context, partner), and identify sites of in vivo hormonal action.
Here, the candidate develops new methods for computational analysis of social behavior and new optical tools
for recording neural activity across multiple brain regions in socially interacting mice. The candidate leverages
these tools to map mouse social behavior (Aim 1) and network-wide neural coding across a change in hormonal
state (Aim 2). In the independent phase of the project, the candidate combines the tools developed in this
proposal with a novel fluorescent reporter to “close” the feedback loop by recording the dynamics of social
experience-dependent, hormone-mediated neural gene transcription across a hormone-sensitive brain network
(Aim 3). This project will provide a new mechanistic understanding of how hormonal changes, neural function,
and social behavior interact and provide key insights into how these behaviors go awry in mood disorders.
This proposal brings together an experienced team of mentors and collaborators with ideal expertise for the
work. This team will provide critical training for the candidates short- and long-term success, including in systems
and computational neuroscience, behavior quantification, and neuroendocrinology. This diverse expertise will
allow the candidate to develop a computational neuroendocrinology research program that applies systems
neuroscience techniques to pressing questions in neuroendocrinology. The proposed training program combines
technical research training with forma...

## Key facts

- **NIH application ID:** 10985545
- **Project number:** 1K99MH135212-01A1
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Eartha Mae Guthman
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $135,989
- **Award type:** 1
- **Project period:** 2024-07-16 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10985545

## Citation

> US National Institutes of Health, RePORTER application 10985545, Mapping Neural Dynamics in Hormone-sensitive Networks (1K99MH135212-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10985545. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*