# Synaptic Mechanisms in the Auditory System

> **NIH NIH R01** · OREGON HEALTH & SCIENCE UNIVERSITY · 2024 · $385,000

## Abstract

Summary
This research will examine the synaptic and circuit-level properties of neurons of the mouse cochlear nucleus
in vitro, based on recent work that defined cell types through transcriptomic profiles. Major cell types will be
recorded from using patch clamp techniques monitoring the properties of their axonal projections, synaptic
input from auditory nerve, and intrinsic properties and then correlate these with the cells individual
transcriptomic profile using Patch-seq. This will provide new functional insight into the diversity within major
classes of cells in cochlear nucleus. Next, we will use mouse cre lines to drive expression of optogenetic tools
in order to resolve functional differences in the connectivity and inhibitory synapses of different classes of
interneuron. Last, we will optogenetically activate specific populations of principal cell while recording from
single principal cells in order to examine homotypic synaptic connections among principal cells. These results
will provide unprecedented insight into the capacity of neurons in the cochlear nucleus to perform
computations on incoming sensory signals. Moreover the results will provide a foundation for future studies
examining how these computations are distorted with hearing impairment.

## Key facts

- **NIH application ID:** 10838515
- **Project number:** 5R01DC004450-26
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** LAURENCE O TRUSSELL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $385,000
- **Award type:** 5
- **Project period:** 1999-09-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10838515

## Citation

> US National Institutes of Health, RePORTER application 10838515, Synaptic Mechanisms in the Auditory System (5R01DC004450-26). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10838515. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*