# Evaluating how inhibition shapes granule cell population codes

> **NIH NIH F31** · DUKE UNIVERSITY · 2020 · $37,509

## Abstract

ABSTRACT
Linking experience and movement is fundamental to nearly all life, as is the ability to predict, based on previous
experience, that a condition warrants a motor response. Such associations often rely on the cerebellum, which
harnesses diverse sensory, motor, and cognitive information encoded by a densely-packed layer of granule
cells (GC) as a substrate for learning. Classical models of cerebellar learning posit that synaptic inhibition of
GCs from local interneurons called Golgi cells is essential for establishing a non-overlapping, sparse population
code. However, recent studies have called such models into question by revealing that unimodal sensory
stimulation can activate widespread GC activity, suggesting that responses can be dense and redundant even
for simple sensory representations under some conditions. These observations call into question whether and
how GCs encode discrete stimulus features at the population level and the degree to which synaptic inhibition
generates sparsity and pattern separation. To test how GCs encode stimulus features at the population level
and how these representations are regulated by local inhibition, I propose to measure stimulus evoked GC
activity using video-rate in vivo calcium imaging in awake mice in conjunction with a GC-specific manipulation
of synaptic inhibition. In Aim 1, I will test whether and how GCs encode feature-specific representations of
stimulus intensity and identity by measuring how single and population GC calcium transients change in
response to varied stimulus features over many randomly interleaved trials, while controlling for movement-
related activity with high-speed video and vibration sensors. Establishing when and how stimulus features are
represented by unique or overlapping GC populations will allow us to test how these activity patterns are
shaped by local inhibition. In Aim 2, I will test how GCs integrate multiple sensory inputs. I will image GC
responses to combined sensory stimuli of either different modalities (i.e. auditory and somatosensory) or the
same modality (i.e. two tones with differing frequencies) and measure how single and population GC calcium
transients change in response to additional, simultaneous stimuli. Based on preliminary data, I anticipate that,
while converging inputs can be summed to drive GCs past spike threshold, GCs will exhibit subtractive, as well
as additive, signal integration due to stimulus-specific recruitment of inhibition. Finally in Aim 3, I will test how
inhibition from Golgi cells shapes the population responses identified in Aim 1 and enables the multisensory
integration by GCs assessed in Aim 2 by acutely blocking GABAergic inputs to GCs using a novel enzymatic
capture system. These experiments will provide novel insight into how GCs encode information at the
individual and population level and reveal how this encoding is regulated by local synaptic inhibition. Hence,
this study will test longstanding models of cerebell...

## Key facts

- **NIH application ID:** 9991060
- **Project number:** 1F31NS113742-01A1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Elizabeth Ann Fleming
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $37,509
- **Award type:** 1
- **Project period:** 2020-05-01 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9991060

## Citation

> US National Institutes of Health, RePORTER application 9991060, Evaluating how inhibition shapes granule cell population codes (1F31NS113742-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9991060. Licensed CC0.

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