# Mechanisms underlying rapid adaptation in mouse visual cortex

> **NIH NIH F31** · DUKE UNIVERSITY · 2022 · $37,278

## Abstract

ABSTRACT
 Adaptation is a fundamental feature of visual processing that enables the nervous system to adjust to
features of our surrounding environment. The temporal statistics of natural scenes and saccadic eye movements
suggest that in most animals, visual input changes at time scales on the order of hundreds of milliseconds. A
proposed function for adaptation is to reduce neurons’ responsivity to same or similar visual input over time, thus
maximizing stimulus information while reducing redundancy of encoding. Identification of the mechanisms
involved in adaptation can reveal how basic biological principles imbue neurons with the ability to perform this
kind of computation. Previous studies have largely used stimuli presented for much longer time scales—on the
order of tens of seconds—to identify mechanisms underlying adaptation in primary visual cortex (V1). Our lab
has identified a form of rapid adaptation in V1 where presentation of a brief, 100 ms static grating is sufficient to
suppress responses to subsequent stimuli for seconds. Preliminary data I have collected using in vivo whole-cell
recordings in awake mice has shown that in V1 neurons, adaptation is characterized by a reduction in stimulus-
evoked excitatory and inhibitory inputs. Here, we seek to test the hypothesis that adaptation to brief stimuli is
primarily mediated by reduction in synaptic inputs that cells receive through activity-dependent reduction of
feedforward synapses between layer 4 and layer 2/3. Proposed experiments will use in vivo recordings with
causal manipulations to address how rapid adaptation could be generated within V1. In Aim 1, I will address
potential mechanisms that could contribute to adaptation in addition to changes in synaptic inputs, such as
changes in cell-intrinsic properties. In Aim 2, I will further characterize activity-induced changes in synaptic inputs
by manipulating the number and orientation of stimuli presented. Finally, in Aim 3 I will specify where these
changes could occur within V1 circuitry using layer-specific optogenetic manipulation of feedforward or recurrent
pathways. Altogether, the findings of this proposal will improve our understanding of how features of cortical
circuits enable the brain to dynamically and efficiently encode stimulus information at naturalistic time scales.

## Key facts

- **NIH application ID:** 10456899
- **Project number:** 5F31EY031941-03
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Jennifer Ying Li
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $37,278
- **Award type:** 5
- **Project period:** 2020-08-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10456899

## Citation

> US National Institutes of Health, RePORTER application 10456899, Mechanisms underlying rapid adaptation in mouse visual cortex (5F31EY031941-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10456899. Licensed CC0.

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