# The Impact of Sleep on Network Coding and Perceptual Performance

> **NIH NIH R01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2020 · $311,000

## Abstract

PROJECT SUMMARY/ABSTRACT
Although sleep is generally believed to be essential for survival, the neuronal mechanisms by which it
affects brain function are largely unknown. Does sleep constitute a passive state in which the brain is `quiet'
or does it play an important role for network coding and behavior in subsequent tasks? Even though the
functional significance of sleep is not well understood, the available data suggest that significant
improvements in learning and memory are found even after brief naps. A critical issue for understanding
sleep function is whether and how it impacts the accuracy of neuronal network computations to
improve behavioral performance. We will address these issues for the first time by examining whether brief
sleep (20 min of rest) influences visual perceptual performance and the coding of visual information across
neuronal populations. We propose to use multiple-electrode recording simultaneously in two visual cortical
areas (V1 and V4) of awake behaving monkey to examine the dynamics and coding in neuronal populations
before, during, and after sleep, and their impact on perceptual performance. Aim 1 will examine how
sensory experience changes the structure of network activity during rest by determining (i) how task
exposure modifies the distribution of neuronal correlations across networks during rest, and (ii) if cells that
are coactivated during stimulus exposure are more likely to be reactivated during subsequent rest. Aim 2 will
examine whether brief sleep influences subsequent stimulus coding by individual neurons and networks by
determining (i) whether single neuron discrimination performance is improved after rest, and (ii) whether and
how correlated activity across the network is modified after rest. By decoding the population response we
will determine (iii) whether neuronal populations encode more information after rest, and (iv) whether and how
rest changes the synchrony between individual neurons and local population activity. Aim 3 will examine
whether rest influences the relationship between neuronal and behavioral performance by determining (i)
whether behavioral performance is improved after rest, (ii) whether the post-sleep neuronal and behavioral
performance are correlated, (iii) whether LFP activity and spike-LFP synchronization during sleep are
correlated with post-rest behavioral performance, (iv) whether there is a relationship between the amount of
rest and the improvement in network and behavioral performance. Our research has the potential to
advance our understanding of the neural mechanisms underlying rest and sleep and thus provide future
solutions to ameliorate the detrimental effects of sleep disorder on cognitive performance, including
practical applications for non-invasive neuronal prosthetic devices.

## Key facts

- **NIH application ID:** 9984382
- **Project number:** 5R01EY026156-05
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** VALENTIN DRAGOI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $311,000
- **Award type:** 5
- **Project period:** 2016-08-01 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9984382

## Citation

> US National Institutes of Health, RePORTER application 9984382, The Impact of Sleep on Network Coding and Perceptual Performance (5R01EY026156-05). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9984382. Licensed CC0.

---

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