Domain-Specific Circadian Rescue following Sleep Deprivation

These findings clarify how circadian and homeostatic drives interact to shape cognitive task performance and subjective sleepiness outcomes under sleep loss, with practical implications for optimizing performance in fatigue-prone environments.

Authors

Institutions

Publication Details

Journal
SLEEP
Published
2026-02-25
DOI
https://doi.org/10.1093/sleep/zsag054
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Domain-Specific Circadian Rescue following Sleep Deprivation

Kaikai Yan, Hengyi Rao, Peng Quan, Mathias Basner et al.
SLEEP
Sleep and Work-Related Fatigue
article

Domain-Specific Circadian Rescue following Sleep Deprivation

Kaikai Yan, Hengyi Rao, Peng Quan, Mathias Basner, Tianxin Mao, Namni Goel, Yao Deng, Weiwei Zhao, Bowen Guo, Chenye Xue, Ya Chai, Xing Chen
article en

Abstract

These findings clarify how circadian and homeostatic drives interact to shape cognitive task performance and subjective sleepiness outcomes under sleep loss, with practical implications for optimizing performance in fatigue-prone environments.

SLEEP
Shanghai International Studies University (CN), University of Science and Technology of China (CN), Rush University Medical Center (US), Hefei University of Technology (CN), Beijing Normal University (CN), Dongguan People’s Hospital (CN), Indiana University – Purdue University Indianapolis (US), University of Pennsylvania (US)
Openalex Percentile: Top 43%
Sleep and Work-Related Fatigue
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.