# Determining how neural coding and readout depend on internal state and past experience

> **NIH NIH U19** · UNIVERSITY OF CHICAGO · 2021 · $617,820

## Abstract

Sensory representations in the brain and an animal’s perception change in many ways over many time scales.
Over tens or hundreds of milliseconds, ongoing neuronal activity contributes substantially to response
variability in primary sensory areas. Effort and arousal typically vary over seconds or minutes, and are also
associated with major changes in sensory representations and behavioral performance. Perceptual learning
occurs over hours and days, imparting new perceptual capabilities. Working with all these forms of variability in
stimulus processing, the brain maintains (in the case of ongoing activity) and improves (in the case of arousal
and learning) behavioral outcomes.
It is commonly assumed that maintenance and improvements in behavioral outcome depend primarily on
changes in the corresponding sensory representation, yet this is far from certain. New methods of two-photon
stimulation are ideal for probing how much the contributions of different cortical neurons change across
behavioral states or as animals learn new perceptual tasks. The proposed experiments take advantage of the
experimental accessibility of stimulus-response associations in primary sensory cortices to identify
mechanisms and principles in neuronal circuits that maintain and improve behavioral outcome in the context of
brain state changes over many timescales. These studies will test whether the high spatiotemporal variability of
ongoing activity reflects higher-order statistics of neuronal population activity that ensure the most informative
stimulus processing and best behavioral outcomes. The impact of effort and arousal will be addressed at
cellular resolution by identifying changes in population representations and readout in primary sensory cortex
between different behavioral states and during saccadic suppression. Perceptual learning experiments will
probe the contributions to behavioral performance of individual neurons in the olfactory bulb, primary auditory
cortex, and primary visual cortex, and determine how those contributions change and can be manipulated over
the course of perceptual learning.
Collectively, these experiments will provide a far more precise and granular view of how sensory
representations vary over different time scales, and new information on how the decoding of those
representations can change over time.

## Key facts

- **NIH application ID:** 10231069
- **Project number:** 5U19NS107464-04
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Dietmar Plenz
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $617,820
- **Award type:** 5
- **Project period:** 2018-09-15 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10231069

## Citation

> US National Institutes of Health, RePORTER application 10231069, Determining how neural coding and readout depend on internal state and past experience (5U19NS107464-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10231069. Licensed CC0.

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