OSCR

Effects of light on brain-state dynamics and energy landscape.

Overview

Authors: Rui Zhang1, Nora D Volkow2
ORCID iDs: Rui Zhang
  1. Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
  2. National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA
Institutions: University of Alabama at Birmingham (United States); National Institutes of Health (United States); National Institute on Drug Abuse (United States)
Journal: Network neuroscience (Cambridge, Mass.), volume 10, issue 3, pages 838-852
Dates: received 7 November 2025; accepted 13 April 2026; published online 25 August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/netn.a.586 · PMID 42730460 · PMCID PMC13569334 · OpenAlex W7160282384
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: computational (subfield)
Methods: Spectral & time-frequency, Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, Preprocessing, fMRI & imaging
Keywords: Light intensity, Brain-state dynamics, Control energy, Network control theory
Topic: Optical Imaging and Spectroscopy Techniques (Radiology, Nuclear Medicine and Imaging, Medicine), according to OpenAlex
Funding: Intramural NIH HHS (ZIA AA000550); NIAAA NIH HHS (R00 AA030031)
Citations: not cited yet (Europe PMC); 53 references in the paper

Abstract

Light influences human cognition and behavior, and neuroimaging studies show that brain activity is modulated by light intensity. However, how light affects temporal brain-state transitions and the control energy required for these transitions remains unclear. To investigate this, we applied a network control theory approach to fMRI data collected from 20 healthy participants who performed an auditory discrimination task under four light intensities. Despite similar task performance, higher light intensity increased the number of transitions between brain states. Increasing light intensity enhanced the occurrence of a visual network dominated brain state, while decreasing the occurrence of brain states characterized by suppressed default mode activity and elevated frontoparietal activity. Furthermore, light intensity affected transition probabilities among different brain states contributed by redistributions of energy demands with the dorso-posterior thalamus appearing to play a key role in mediating light-related effects. Regionally, higher light intensity was associated with a trend toward reduced control energy in the visual network; frontal, cingulate, and insular cortices; and caudate and task-related regions, while showing a trend toward increased control energy in the somatomotor network and temporal pole. These findings suggest that high-intensity light may enhance neural efficiency and flexibility by redistributing control energy demands across brain regions.

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

Code

The paper links to its data, not to its authors' code: see the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 4 keywords, 2 funders, 53 references.

Cite

This paper

Zhang, R., & Volkow, N. D. (2026). Effects of light on brain-state dynamics and energy landscape. Network neuroscience (Cambridge, Mass.), 10(3), 838-852. https://doi.org/10.1162/netn.a.586

BibTeX

@article{zhang2026effects,
author = {Zhang, Rui and Volkow, Nora D},
title = {{Effects of light on brain-state dynamics and energy landscape}},
journal = {Network neuroscience (Cambridge, Mass.)},
year = {2026},
month = aug,
volume = {10},
number = {3},
pages = {838--852},
publisher = {MIT Press},
issn = {2472-1751},
doi = {10.1162/netn.a.586},
url = {https://doi.org/10.1162/netn.a.586},
pmid = {42730460},
pmcid = {PMC13569334}
}

RIS

TY - JOUR
AU - Zhang, Rui
AU - Volkow, Nora D
TI - Effects of light on brain-state dynamics and energy landscape
T2 - Network neuroscience (Cambridge, Mass.)
J2 - Netw Neurosci
PY - 2026
DA - 2026/08/25
VL - 10
IS - 3
SP - 838
EP - 852
SN - 2472-1751
PB - MIT Press
DO - 10.1162/netn.a.586
UR - https://doi.org/10.1162/netn.a.586
LA - en
ER -

CSL-JSON

{
"id": "10.1162/netn.a.586",
"type": "article-journal",
"title": "Effects of light on brain-state dynamics and energy landscape",
"container-title": "Network neuroscience (Cambridge, Mass.)",
"author": [
{
"family": "Zhang",
"given": "Rui"
},
{
"family": "Volkow",
"given": "Nora D"
}
],
"container-title-short": "Netw Neurosci",
"volume": "10",
"issue": "3",
"page": "838-852",
"DOI": "10.1162/netn.a.586",
"PMID": "42730460",
"PMCID": "PMC13569334",
"ISSN": "2472-1751",
"publisher": "MIT Press",
"URL": "https://doi.org/10.1162/netn.a.586",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
25
]
]
}
}

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:10.1038/s41467-026-71961-4 [code]
Spatiotemporal asymmetries on brain energy landscape uncover system entrapment related to depression severity.
Journal: Nature communications
In common: computational, 5 references
[2] doi:10.1038/s41467-026-74215-5 [code]
Multi-metric evaluations of acute psychedelic effects on fMRI brain entropy.
Journal: Nature communications
In common: computational, 6 references
[3] doi:10.1007/s11920-026-01671-7 [code]
Light Exposure as a Modifiable Determinant of Mental Health.
Journal: Current psychiatry reports
In common: 4 references
[4] doi:10.1093/pnasnexus/pgag245 [code]
Reduced integrity in the frontal aslant tract's premotor connections is associated with dysfluency severity in stuttering.
Journal: PNAS nexus
In common: 4 references
[5] doi:10.1038/s41398-026-04025-2 [code]
Brain energetic landscapes shape state dysregulation in major depressive disorder: a morphological network controllability perspective.
Journal: Translational psychiatry
In common: 5 references
[6] doi:10.1162/imag.a.1282 [code]
Metabolic syndrome severity and the energetic cost of brain network transitions: A normative modeling study of accelerated brain aging.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: computational, 4 references
[7] doi:10.1038/s41467-026-75585-6 [code]
Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.
Journal: Nature communications
In common: 5 references
[8] doi:10.1126/sciadv.aef2894 [code]
Human cortical networks trade communication efficiency for computational reliability.
Journal: Science advances
In common: 4 references
[9] doi:10.1093/braincomms/fcag220 [code]
When pain becomes self: limbic-default mode network hyperconnectivity predicts microvascular decompression failure in trigeminal neuralgia.
Journal: Brain communications
In common: 4 references
[10] doi:10.1038/s41562-026-02447-y [code]
Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers.
Journal: Nature human behaviour
In common: 3 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.