# CRCNS: Mechanistic Modeling and Inference of Neuronal Synaptic Transmission

> **NIH NIH R01** · UNIVERSITY OF DELAWARE · 2020 · $110,991

## Abstract

Action potential-triggered transmitter release forms a hallmark of interneuronal communication. The
release is critically impacted by diverse noise mechanisms, such as random arrival of action potentials,
probabilistic vesicle release, and random replenishment of vesicle pools. How these noise mechanisms
 combine to impact fidelity of interneuronal communication is an intriguing fundamental problem. A key
 focus of this project is to use the mathematical formalism of Stochastic Hybrid Systems (SHS) that
combine continuous dynamics with discrete random events for modeling synaptic transmission. The
 SHS-based formalism will be used to derive analytical results connecting synaptic noise mechanisms to
 randomness in the neurotransmitter levels, and its impact on temporal precision of the responses in the
postsynaptic neuron. The project will also develop novel inference methods for inferring
neurotransmission parameters from whole-cell patch-clamp recordings in acute brain slices of juvenile
 mice. Integration of mathematical models with experimental data on long-lasting high-frequency activation
of input neurons will be used to characterize neurotransmission at various auditory and non-auditory
 synapse types. This interdisciplinary approach--coupled with genetic and pharmacological manipulation of
 neurotransmitter release, re-uptake, and vesicle replenishment--will systematically uncover the role of
 these processes in information processing at the single-cell level and how auditory brainstem synapses
 achieve exquisitely high fidelity during prolonged stimulation. Altogether, the project will reveal the
extraordinary capabilities of auditory synapses and thus form a basis for a better understanding of central
auditory processing disorders.
RELEVANCE (See instructions):
 Hearing impairment is the most prevalent sensory deficit, with major socioeconomic impact. In order to
 understand how hearing happens, we must obtain a comprehensive knowledge about neuronal
 information processing in the central auditory system. The project will thoroughly address synaptic
 processes involved in sound localization by combining empirical work with computational modeling, and
 we will achieve hitherto unreached synergistic effects towards our goal.

## Key facts

- **NIH application ID:** 10147289
- **Project number:** 1R01DC019268-01
- **Recipient organization:** UNIVERSITY OF DELAWARE
- **Principal Investigator:** Abhyudai Singh
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $110,991
- **Award type:** 1
- **Project period:** 2020-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10147289

## Citation

> US National Institutes of Health, RePORTER application 10147289, CRCNS: Mechanistic Modeling and Inference of Neuronal Synaptic Transmission (1R01DC019268-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10147289. Licensed CC0.

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