Evidence map›Paper›PMID 37788939›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2023

Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep.

Joline M Fan, Kiwamu Kudo, Parul Verma, Kamalini G Ranasinghe, Hirofumi Morise, Anne M Findlay, Keith Vossel, Heidi E Kirsch, Ashish Raj, Andrew D Krystal and 1 more

Open access · greenAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Joline M FanDepartment of Neurology, University of California-San Francisco, San Francisco, California 94143 joline.fan@ucsf.edu.
Kiwamu KudoDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.ORCID 0000-0002-5732-7229
Parul VermaDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.
Kamalini G RanasingheDepartment of Neurology, University of California-San Francisco, San Francisco, California 94143.
Hirofumi MoriseDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.
Anne M FindlayDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.
Keith VosselDepartment of Neurology, University of California-San Francisco, San Francisco, California 94143.
Heidi E KirschDepartment of Neurology, University of California-San Francisco, San Francisco, California 94143.
Ashish RajDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.
Andrew D KrystalDepartment of Psychiatry, University of California-San Francisco, San Francisco, California 94143.
Srikantan S NagarajanDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143.
University of California, San Francisco · USUniversity of California, Los Angeles · US

Funding

Understanding disorder-specific neural pathophysiology in laryngeal dystonia and voice tremorP50DC019900 · NIDCD · MASSACHUSETTS EYE AND EAR INFIRMARY · PI Kristina Simonyan · 2021 to 2026
$11.9M
NRSA Training CoreTL1TR001871 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KANAYA, ALKA M., SOMSOUK, MA · 2016 to 2025
$10.1M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaR01NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI, John Francis Houde · 2017 to 2026
$3.6M
Network Modelling of Multimodal Dynamics in Alzheimer’s Disease and DementiaRF1AG062196 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAGARAJAN, SRIKANTAN S., RAJ, ASHISH · 2019 to 2019
$3.0M
Network dynamics of sleep-wake states in epilepsyK23NS125123 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Joline Fan · 2023 to 2026
$868k
Neurophysiological Assessments of Network Dysfunction in Alzheimer's DiseaseK08AG058749 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RANASINGHE, KAMALINI GAYATHREE · 2019 to 2023
$859k
Mechanisms and Treatment of Network Dysfunction in Alzheimer's DiseaseK23AG038357 · NIA · J. DAVID GLADSTONE INSTITUTES · PI VOSSEL, KEITH ALAN · 2011 to 2015
$764k
Multimodal imaging measures to assess synaptic dysfunction in Alzheimer's diseaseR21AG077498 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RANASINGHE, KAMALINI GAYATHREE · 2022 to 2022
$484k
NCATS NIH HHS TL1 TR001871NIA NIH HHS K08 AG058749NIA NIH HHS K23 AG038357NIA NIH HHS R21 AG077498NIA NIH HHS RF1 AG062196NIDCD NIH HHS P50 DC019900NIDCD NIH HHS R01 DC017091NINDS NIH HHS K23 NS125123NINDS NIH HHS R01 NS100440
6 · The paper itself

Abstract

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.

Indexed as

ElectroencephalographyWakefulnessEye MovementsFemaleHumansSleepSleep Stagesfunctional connectivityinformation flowMEGneural mass modelingNREMsleep

Identifiers

PMID37788939
PMCPMC10697405
OpenAlexW4387299625

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.