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Young and old adult brains experience opposite effects of acute sleep restriction on the functional connectivity network.

Code ↔ Paper

8 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 8 matches · 3 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Modularity ↔ community_louvain.m, lines 1–71 · score 0.90 · asymmetric treatment, COMMUNITY_LOUVAIN, resolution parameter, und sign, negative weights, modules
  2. [2] § Methods › Modularity ↔ null_model_und_sign.m, lines 1–73 · score 0.82 · NULL_MODEL_UND_SIGN, strength distributions, preserves weight, negative weights, network, matrices
  3. [3] § Methods › Dynamic functional connectivity ↔ leida-matlab-1.0/utilities/analyses_scripts/cluster_performance.m, the whole file · a weak match · score 0.78 · Calinski Harabasz, Silhouette coefficient, Leading Eigenvector, Dunn, clustering, score
  4. [4] § Methods › Dynamic functional connectivity ↔ leida-matlab-1.0/LEiDA_TransitionsK.m, the whole file · a weak match · score 0.72 · Leading Eigenvector Dynamics, transition probability matrices, LEiDA, chosen, clustering, FC
  5. [5] § Methods › Preprocessing ↔ python_packages/brainvistools/src/brainvistools/visualization.py, lines 73–138 · score 0.61 · Tian atlas, subcortical regions, Library, Schaefer
  6. [6] § Results › Network modularity ↔ community_louvain.m, lines 1–71 · score 0.60 · resolution parameter, modularity increased, Louvain, algorithm, modules, model
  7. [7] § Methods › Partial least squares (PLS) ↔ leida-matlab-1.0/utilities/analyses_scripts/LEiDA_stats_TransitionMatrix.m, lines 1–65 · score 0.53 · transition probability, fractional occupancy, LEiDA, scans, bootstrap, permutation
  8. [8] § Methods › Partial least squares (PLS) ↔ leida-matlab-1.0/LEiDA_TransitionsK.m, the whole file · a weak match · score 0.53 · transition probability, LEiDA, reliable, bootstrap, variables, permutation

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

MATLAB · 198 lines · 7.6 KB · no license · 2 matches

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It can be read at the source: community_louvain.m.

Overview

Authors: Josh Neudorf1,2, Leanne Rokos1,3,4, Kelly Shen1, Brianne Kent1,5, Anthony R. McIntosh1,3
ORCID iDs: Josh Neudorf, Leanne Rokos, Kelly Shen, Brianne Kent, Anthony R. McIntosh
  1. Institute for Neuroscience and Neurotechnology, Simon Fraser University, Burnaby, Canada
  2. Centre for Social Sciences, Athabasca University, Athabasca, Canada
  3. Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, Canada
  4. Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
  5. Department of Psychology, Simon Fraser University, Burnaby, Canada
Institutions: Simon Fraser University (Canada); Baycrest Hospital (Canada); Baycrest Academy for Research and Education (Canada); Rotman Research Institute (Canada)
Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1278
Dates: received 25 July 2025; accepted 20 May 2026; published online 18 June 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/imag.a.1278 · PMID 42326561 · PMCID PMC13281775 · OpenAlex W4412792471
Open access: diamond, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.07.25.666859
Status: code verified
Categories: fMRI (modality), human (organism), healthy (population)
Methods: Spectral & time-frequency, Connectivity, Statistics, Preprocessing, Graphs, Smoothing, state filtering, decompositions
Keywords: resting-state functional magnetic resonance imaging, dynamic functional connectivity, graph theory, healthy ageing, acute sleep restriction
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) (RGPIN-2018-04457); Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada) (PJT-168980)
Citations: not cited yet (Europe PMC); 87 references in the paper

Abstract

Chronic, long-term sleep loss is detrimental to brain health and cognitive ability. However, older adults are affected differently by acute, short-term loss of sleep than young and middle-aged adults. Older adults are more resilient to the effects of acute sleep loss and, depending on the cognitive domain, may be completely unaffected while younger adults suffer. To elucidate the brain network responses to sleep loss underlying these cognitive differences between age groups, we investigated the static and dynamic functional connectivity effects of acute sleep restriction (sleep limited to 3 hours) and how these effects differ between younger adults (20–30 years) and older adults (65–75 years). We found a functional connectivity subnetwork that was primarily strengthened in younger adults after acute sleep restriction but weakened in older adults after acute sleep restriction. Similar crossover interactions were consistently observed in further analyses of functional connectivity degree, modularity, and dynamic functional connectivity state fractional occupancy. Our findings demonstrate that the effect of acute sleep restriction on older adults is fundamentally different from that on younger adults. These results most strongly support the compensation theory of ageing, which predicts a fundamental shift in the effects of acute sleep loss, rather than a mere dampening of the sleep benefits experienced by younger adults.

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

Repository

Its files are read in the Code ↔ Paper reader above, with 8 matches between paragraphs and lines of code.

McIntosh-Lab/SleepyBrain_analyses

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 9ac5ad3bbe28feaa8cc7925ccf9adee716ae3877, 31 July 2025
Languages: MATLAB (56), Shell (8), Python (8), R (6)
Size: 134 files, 78 scripts
Software Heritage: not archived
Found in: “Data and Code Availability”
Holds: README, environment (requirements_hpc.txt, python_packages/brainvistools/pyproject.toml, python_packages/PyNeudorf/pyproject.toml)
Not found: license file, CITATION.cff, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (13 files), Image Processing Toolbox (11 files), ggplot2 (6 files), tidyverse (5 files), FSL (4 files), NumPy (4 files), SciPy (4 files), ggseg (3 files), lme4 (3 files), Signal Processing Toolbox (3 files), Matplotlib (3 files), NiBabel (3 files), Brain Connectivity Toolbox (2 files), NetworkX (2 files), Nilearn (2 files), pandas (2 files), Parallel Computing Toolbox (1 file), neuromaps (1 file), Pillow (1 file), seaborn (1 file), statsmodels (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
79 files, not copied: shown from their source

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At the source: github.com/McIntosh-Lab/SleepyBrain_analyses

The paper's code and data availability statement is in the Data section.

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;
  • 78 scripts, each with its path and the digest of its content;
  • 8 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • 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

Datasets cited

Data and Code Availability

Data were downloaded from OpenfMRI (https://openfmri.org/dataset/ds000201/). Code used to produce analyses are available via github repository (https://github.com/McIntosh-Lab/SleepyBrain_analyses).

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 2, 28 September 2026

  • Authors: added Kelly Shen (0000-0001-8780-9299); Brianne Kent (0000-0003-0074-028X); removed Kelly Shen; Brianne Kent

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 5 authors, 5 keywords, 2 funders, 85 references.

Cite

This paper

Neudorf, J., Rokos, L., Shen, K., Kent, B., & McIntosh, A. R. (2026). Young and old adult brains experience opposite effects of acute sleep restriction on the functional connectivity network. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1278. https://doi.org/10.1162/imag.a.1278

BibTeX

@article{neudorf2026young,
author = {Neudorf, Josh and Rokos, Leanne and Shen, Kelly and Kent, Brianne and McIntosh, Anthony R.},
title = {{Young and old adult brains experience opposite effects of acute sleep restriction on the functional connectivity network}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = jun,
volume = {4},
pages = {IMAG.a.1278},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/imag.a.1278},
url = {https://doi.org/10.1162/imag.a.1278},
pmid = {42326561},
pmcid = {PMC13281775}
}

RIS

TY - JOUR
AU - Neudorf, Josh
AU - Rokos, Leanne
AU - Shen, Kelly
AU - Kent, Brianne
AU - McIntosh, Anthony R.
TI - Young and old adult brains experience opposite effects of acute sleep restriction on the functional connectivity network
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/06/18
VL - 4
SP - IMAG.a.1278
SN - 2837-6056
PB - MIT Press
DO - 10.1162/imag.a.1278
UR - https://doi.org/10.1162/imag.a.1278
LA - en
ER -

CSL-JSON

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