# Investigating the logic of homeostatic sleep control circuitry in Drosophila

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $341,250

## Abstract

Abstract
Continuous sleep loss degrades the physiology of systems throughout the brain and body, eventually causing
death. To prevent these consequences, homeostatic mechanisms activate after prolonged waking to promote
sleep. Understanding neural mechanisms that control sleep homeostasis will provide insight into the basic
functions of sleep and aid the development of interventions that provide resilience to sleep loss, but these
circuits have not been clearly characterized. Previous studies have identified a small population of fly neurons
that project into the dorsal Fan-shaped Body (dFB) and act as a homeostatic control center for sleep. We have
conducted an RNAi screen to identify sleep-promoting dFB input signals and have characterized an output
signal released by dFB neurons to induce sleep. In this proposal, we will: (1) use electrophysiology along with
receptor RNAis and mutants to confirm dFB input signal identity, (2) create genetic reporters for post-synaptic
targets of dFB neurons, and (3) use patch-clamp recordings to test whether dFB excitability is elevated to
promote sleep during memory consolidation and degraded in aged flies, resulting in sleep fragmentation.

## Key facts

- **NIH application ID:** 9927704
- **Project number:** 5R01NS105967-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Jeffrey Michael Donlea
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $341,250
- **Award type:** 5
- **Project period:** 2018-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9927704

## Citation

> US National Institutes of Health, RePORTER application 9927704, Investigating the logic of homeostatic sleep control circuitry in Drosophila (5R01NS105967-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9927704. Licensed CC0.

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