# Functional Connectivity in the Circadian Clock

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2024 · $542,354

## Abstract

Project Summary
The robust, yet sensitive, systems underlying daily behaviors provide an outstanding opportunity
to apply dynamical network science to understand how neural connectivity adapts to a changing
environment. Daily rhythms in behavior and physiology (e.g., sleep-wake and hormone
secretion) depend on circadian clock genes, pacemaking cells and cell-cell signaling to adjust to
daily cues such as seasonal changes in daylength. The suprachiasmatic nucleus, SCN,
coordinates these daily rhythms to anticipate challenges such as finding food and mates and
avoiding predators. This application focuses on major gaps in our understanding of how SCN
cells adapt and synchronize to produce daily rhythms in response to seasonal changes in
photoperiod.
The proposed experiments combine in vivo and in vitro cell-type specific perturbations and
recordings with computational biology and control engineering to test the central hypothesis that
specific and reversible changes in network topology underlie adaptation to long and short days.
The Aims will map, for the first time, cell-cell connectivity changes in the SCN during adjustment
to long and short days. We will record gene expression and intracellular calcium from distinct
classes of neurons within the SCN before, during, and after exposure to long (summer) or short
(winter) days and, using a novel data science method, infer their connectivity. We will evaluate
these inferred networks by using computational models to predict their behavior to control-
theory-inspired perturbations that are then implemented on identified cells in vitro and in vivo.
Taken together, the proposed aims will elevate the SCN into the small class of circuits that has
been mapped with sufficient cellular resolution to allow evaluation of connectivity rules that
support the robust, yet sensitive, network performance. The results from the experiments will lay
a foundation for understanding how the brain is organized as a network of synchronized
circadian cells. We will create methods to reveal functional neural topology and to analyze and
control dynamic structures in complex networks with different spatial and temporal scales.
Ultimately, these experiments will provide guidelines to reveal, and insights to understand, how
diverse network topologies adapt to be robust and yet sensitive to everyday cues.

## Key facts

- **NIH application ID:** 10993484
- **Project number:** 1R01NS139415-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Erik Herzog
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $542,354
- **Award type:** 1
- **Project period:** 2024-07-01 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10993484

## Citation

> US National Institutes of Health, RePORTER application 10993484, Functional Connectivity in the Circadian Clock (1R01NS139415-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10993484. Licensed CC0.

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