# Characterizing the underlying population code to understand the functional organization of the hippocampus and the lateral hypothalamus

> **NIH NIH R00** · UNIVERSITY OF VIRGINIA · 2024 · $248,999

## Abstract

Project Summary/Abstract
Recent advancements in neural recording/imaging technologies and computational methods have generated a
renewed interest in studying coordinated population activity. Understanding the population code can help us
better understand the complex mechanisms behind substance use disorders (SUD). One leading idea is that
high-dimensional neural activity, such as simultaneous recordings from hundreds to thousands of cells, can lie
on low-dimensional manifolds, such that a handful of latent variables can accurately describe the activity of all
recorded neurons. The lateral hypothalamus (LH) is a brain area well-known for its functional diversity – individual
cells respond with great heterogeneity to a wide range of appetitive behaviors, and LH stimulation can evoke a
variety of actions ranging from feeding to social interaction. This project proposes to use the latest nonlinear
dimensionality reduction techniques to extract the low-dimensional manifolds representing population activity
patterns that geometrically organize the heterogeneous single neuron activity. These manifolds can then be used
to achieve this project’s main goal – differentiating LH neural population encoding of natural reward-seeking
behaviors and maladaptive drug-seeking behaviors. In addition, novel computational modeling methods will be
used to perform unsupervised detection of internal neural states that guide animals switching between these two
reward-seeking behaviors. Finally, state-of-the-art cellular-resolution simultaneous stimulation and imaging
microscopy will be used to casually perturb animal behavior and/or neural activity patterns by activating
sequences of neurons along trajectories on the low-dimensional manifolds. Importantly, Aims 1 and 2 support
these goals by offering training in the use of the necessary computational and instrumentation techniques.
Ultimately, results obtained from this project will advance our understanding of the neural mechanisms
separating harmful drug-seeking behaviors and useful natural reward-seeking behaviors, such that SUD
treatments with more precise targets can be developed that minimize unwanted side effects.

## Key facts

- **NIH application ID:** 10894828
- **Project number:** 5R00DA053388-04
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Horng-An Edward Nieh
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $248,999
- **Award type:** 5
- **Project period:** 2023-08-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10894828

## Citation

> US National Institutes of Health, RePORTER application 10894828, Characterizing the underlying population code to understand the functional organization of the hippocampus and the lateral hypothalamus (5R00DA053388-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10894828. Licensed CC0.

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