OSCR

Oscillatory network efficiency predicts mood and fatigue during sleep deprivation.

Overview

Authors: David Negelspach1, Alisa Huskey1, Kathryn E R Kennedy1, Jungwon Cha1, Michael A Grandner2, Daniel Forger3, William D S Killgore1
ORCID iDs: David Negelspach, Kathryn E R Kennedy, Daniel Forger, William D S Killgore
  1. Department of Psychiatry, Social, Cognitive, and Affective Neuroscience Lab, College of Medicine, University of Arizona, Tucson, AZ USA
  2. Department of Psychiatry, Sleep and Health Research Program, College of Medicine, University of Arizona, Tucson, AZ USA
  3. Department of Mathematics, University of Michigan, Ann Arbor, MI USA
Institutions: University of Arizona (United States); University of Michigan (United States)
Journal: Communications biology, volume 9, issue 1, article 1041
Dates: received 8 November 2025; accepted 1 May 2026; published online 16 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s42003-026-10250-8 · PMID 42143171 · PMCID PMC13438542 · OpenAlex W7161416073
Open access: gold, a free copy (OpenAlex)
Status: code found, not verified yet
Categories: human (organism), systems (subfield)
Methods: Spectral & time-frequency, Connectivity, Statistics, Smoothing, state filtering, decompositions, Graphs, fMRI & imaging
Keywords: Neuroscience, Sleep deprivation
MeSH: Affect*, Brain*, Circadian Rhythm*, Fatigue*, Nerve Net*, Sleep Deprivation*, Connectome, Female, Humans, Magnetic Resonance Imaging, Wakefulness (* major topic)
Topic: Mental Health Research Topics (Experimental and Cognitive Psychology, Psychology), according to OpenAlex
Funding: United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO) (W911NF2210223)
Citations: not cited yet (Europe PMC); 94 references in the paper
Research resources: RRID:SCR_001476, RRID:SCR_009550

Abstract

Fluctuations in performance and mood across the day have been traced to circadian and homeostatic modulation of motor and affective systems, although their combined influence on network topology is rarely considered. We applied a data-driven curve-fitting algorithm to capture both circadian and infradian rhythms ( ≥ 24 hours) in frontolimbic and sensorimotor regions using functional magnetic resonance imaging (fMRI) measures of connectivity. Across the course of sleep deprivation, functional network structure was not static but changed in tandem with objective and subjective behavioral measures. Oscillatory patterns in network efficiency suggest that circadian rhythmicity extends to higher-order network topology. Sleep deprivation affects functional networks in a region-specific manner, highlighting local vulnerability. Distinct cortical regions exhibited unique circadian phases of network reorganization, revealing that connectivity rhythms are spatially as well as temporally differentiated across the brain. Time-dependent alterations in connectome topology offer a systems-level framework for understanding how internal timekeeping and sleep pressure modulate non-linear trends in psychomotor vigilance, mood, and fatigue across extended wakefulness.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

mathworks.com/help/optim

License: none: the authors keep all their rights
State: unreachable at the last attempt, verified on 29 September 2026
Evidence: found in the paper
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 4 checks, the latest on 29 September 2026: unreachable at the last attempt (HTTP 403)
  • 29 September 2026: unreachable at the last attempt (HTTP 403)
  • 28 September 2026: unreachable at the last attempt (HTTP 403)
  • 28 September 2026: unreachable at the last attempt (HTTP 403)
  • 28 September 2026: unreachable at the last attempt (HTTP 403)
At the source: mathworks.com/help/optim/ug/lsqcurvefit.html

Code availability

Documentation for code and methods of the lsqcurvefit function can be found at https://www.mathworks.com/help/optim/ug/lsqcurvefit.html as part of the optimization toolbox. Function specification and parameter definitions are clearly described in the methods section.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

Data may be made available upon reasonable request to the corresponding author, provided the data being shared adheres to participant privacy rights. Source data for graphs and figures have been submitted to the University of Arizona’s Research Data Repository (ReDATA)94 under 10.25422/azu.data.32069517.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 2 keywords, 11 MeSH terms, 1 funder, 82 references, 2 RRIDs.

Cite

This paper

Negelspach, D., Huskey, A., Kennedy, K. E. R., Cha, J., Grandner, M. A., Forger, D., & Killgore, W. D. S. (2026). Oscillatory network efficiency predicts mood and fatigue during sleep deprivation. Communications biology, 9(1), 1041. https://doi.org/10.1038/s42003-026-10250-8

BibTeX

@article{negelspach2026oscillatory,
author = {Negelspach, David and Huskey, Alisa and Kennedy, Kathryn E R and Cha, Jungwon and Grandner, Michael A and Forger, Daniel and Killgore, William D S},
title = {{Oscillatory network efficiency predicts mood and fatigue during sleep deprivation}},
journal = {Communications biology},
year = {2026},
month = may,
volume = {9},
number = {1},
pages = {1041},
publisher = {Nature Publishing Group},
issn = {2399-3642},
doi = {10.1038/s42003-026-10250-8},
url = {https://doi.org/10.1038/s42003-026-10250-8},
pmid = {42143171},
pmcid = {PMC13438542}
}

RIS

TY - JOUR
AU - Negelspach, David
AU - Huskey, Alisa
AU - Kennedy, Kathryn E R
AU - Cha, Jungwon
AU - Grandner, Michael A
AU - Forger, Daniel
AU - Killgore, William D S
TI - Oscillatory network efficiency predicts mood and fatigue during sleep deprivation
T2 - Communications biology
J2 - Commun Biol
PY - 2026
DA - 2026/05/16
VL - 9
IS - 1
SP - 1041
SN - 2399-3642
PB - Nature Publishing Group
DO - 10.1038/s42003-026-10250-8
UR - https://doi.org/10.1038/s42003-026-10250-8
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s42003-026-10250-8",
"type": "article-journal",
"title": "Oscillatory network efficiency predicts mood and fatigue during sleep deprivation",
"container-title": "Communications biology",
"author": [
{
"family": "Negelspach",
"given": "David"
},
{
"family": "Huskey",
"given": "Alisa"
},
{
"family": "Kennedy",
"given": "Kathryn E R"
},
{
"family": "Cha",
"given": "Jungwon"
},
{
"family": "Grandner",
"given": "Michael A"
},
{
"family": "Forger",
"given": "Daniel"
},
{
"family": "Killgore",
"given": "William D S"
}
],
"container-title-short": "Commun Biol",
"volume": "9",
"issue": "1",
"page": "1041",
"DOI": "10.1038/s42003-026-10250-8",
"PMID": "42143171",
"PMCID": "PMC13438542",
"ISSN": "2399-3642",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s42003-026-10250-8",
"language": "en",
"issued": {
"date-parts": [
[
2026,
5,
16
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1111/ejn.70511 [code]
The Effect of Caffeine Consumption and Acute Withdrawal on Resting-State fMRI Brain Connectivity, Mood and Cognition.
Journal: The European journal of neuroscience
In common: 12 references
[2] doi:10.1186/s12974-026-03962-5
Neuroinflammation-associated thalamocortical functional connectivity and cognition in older adults.
Journal: Journal of neuroinflammation
In common: 9 references
[3] doi:10.1002/hbm.70590
Diurnal Variations and Test-Retest Reliability of Resting-State Functional MRI Metrics.
Journal: Human brain mapping
In common: 5 references
[4] doi:10.1093/braincomms/fcag134 [code]
Neurophysiological, imaging and neurobiological markers of central fatigue in multiple sclerosis.
Journal: Brain communications
In common: 5 references
[5] doi:10.1016/j.ynirp.2026.100363
Narrative coherence shapes functional connectivity in default mode and frontoparietal networks.
Journal: Neuroimage. Reports
In common: systems, 4 references
[6] doi:10.7554/elife.108208 [code]
Realistic coupling enables flexible macroscopic traveling waves in the mouse cortex.
Journal: eLife
In common: author Daniel B Forger
[7] doi:10.7554/elife.104053 [code]
Brain cognition gaps reveal associations with dopamine and factors related to brain health through artificial intelligence prediction of functional connectome.
Journal: eLife
In common: 4 references
[8] doi:10.1007/s11682-026-01167-1
Estradiol modulated brain connectivity in females during midlife performing an episodic memory task.
Journal: Brain imaging and behavior
In common: 4 references
[9] doi:10.1002/alz.71651
Longitudinal effects of physical activity on sleep in association with hippocampal-amygdala subfield structure and functional connectivity in Alzheimer's disease.
Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
In common: 3 references
[10] doi:10.1038/s41598-026-49157-z
Supportive neural mechanisms underlying successful emotion regulation for reappraisal success.
Journal: Scientific reports
In common: 4 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.