# CRCNS: Evidence-based modeling of neuromodulatory action on network properties

> **NIH NIH R01** · BRANDEIS UNIVERSITY · 2024 · $357,884

## Abstract

PROJECT SUMMARY (See instructions):
Overview:
The preBotzinger Complex (preBotC) is the neuronal network that drives inspiratory rhythmogenesis
whose activity is orchestrated in response to changes in homeostasis and is critical for maintaining and
adapting breathing to the demands of the organism. Respiratory networks are constantly modulated by
numerous neuromodulators through altering properties of neurons, synapses and networks.
Understanding action of neuromodulation on respiratory networks is critical to understanding control of
breathing. While there is extensive experimental effort on studying network effects of neuromodulation,
the mechanisms underlying neuromodulatory action on respiratory network properties cannot be easily
understood just by experimental work alone. Despite the well-established utility of computational
approaches to studying the neural control of breathing, a knowledge gap exists for a computational
understanding of the detailed mechanisms underlying how different neuromodulators interact to impact
respiratory rhythmogenesis. The overall objective of this proposal is to uncover the mechanism by which
the temporal order of neuromodulation with opposing actions (i.e., inhibitory and excitatory) differentially
impact respiratory network dynamics. Our preliminary data suggest that such temporal sequencing can
induce bifurcations and bistability in network states. We hypothesize that temporal order of opposing
neuromodulators yields different changes in intrinsic and synaptic properties of a network which together
produce qualitatively different network behaviors when the order is reversed. We will combine
electrophysiological experiments and computational modeling across the levels of molecules
(glutamates), neurons and networks to test this hypothesis via a focus on respiration, with three Specific
Aims: (1) Identify how changes in inhibitory neuromodulation (e.g., opioids) impacts synaptic dynamics
and properties in glutamatergic synapse. (2) Dissect the mechanisms by which excitatory
neuromodulation (e.g., norepinephrine) regulates respiratory network dynamics through changes in both
intrinsic and synaptic properties. (3) Examine the synaptic and intrinsic mechanisms by which temporal
order of opposing neuromodulators produces different network states. We will explore and identify
relevant bifurcations induced by temporal order of neuromodulators using dynamical systems theory.

## Key facts

- **NIH application ID:** 10830424
- **Project number:** 5R01DA057767-04
- **Recipient organization:** BRANDEIS UNIVERSITY
- **Principal Investigator:** Yangyang Wang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $357,884
- **Award type:** 5
- **Project period:** 2022-06-15 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10830424

## Citation

> US National Institutes of Health, RePORTER application 10830424, CRCNS: Evidence-based modeling of neuromodulatory action on network properties (5R01DA057767-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10830424. Licensed CC0.

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