Evidence map›Paper›PMID 30090873›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2018

High-energy brain dynamics during anesthesia-induced unconsciousness.

James R Riehl, Ben J Palanca, ShiNung Ching

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
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  12. High-energy brain dynamics during anesthesia-induced unconsciousness.Network neuroscience (Cambridge, Mass.) · 2018
    Article
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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

3 authors.

James R RiehlDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA.ORCID 0000-0001-9555-7036
Ben J PalancaDepartment of Anesthesiology, Washington University School of Medicine, St. Louis, MO, USA.ORCID 0000-0001-7535-5701
ShiNung ChingDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA.ORCID 0000-0003-4063-7068

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Washington University Institute of Clinical and Translational SciencesKL2TR000450 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$8.8M
THE DEFAULT MODE NETWORK DURING THE PATHOGENESIS OF POSTOPERATIVE DELIRIUMR21AG052821 · NIA · WASHINGTON UNIVERSITY · PI PALANCA, BEN JULIAN · 2016 to 2017
$419k
Disambiguating coma etiologies by assessing the lability of EEG dynamicsR21NS096590 · NINDS · WASHINGTON UNIVERSITY · PI CHING, SHINUNG, KUMMER, TERRANCE T · 2016 to 2017
$404k
NCATS NIH HHS KL2 TR000450NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR002345NIA NIH HHS R21 AG052821NINDS NIH HHS R21 NS096590
6 · The paper itself

Abstract

Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined through neuroimaging. However, the effects of anesthesia on temporal dynamics at functional network scales is less well understood. Here, we examine such dynamics in view of the free-energy principle, which postulates that brain dynamics tend to promote lower energy (more organized) states. We specifically engaged the hypothesis that such low-energy states play an important role in maintaining conscious awareness. To investigate this hypothesis, we analyzed resting-state BOLD fMRI data from human volunteers during wakefulness and under sevoflurane general anesthesia. Our approach, which extends an idea previously used in the characterization of neuron-scale populations, involves thresholding the BOLD time series and using a normalized Hamiltonian energy function derived from the Ising model. Our major finding is that the brain spends significantly more time in lower energy states during eyes-closed wakefulness than during general anesthesia. This effect is especially pronounced in networks thought to be critical for maintaining awareness, suggesting a crucial cognitive role for both the structure and the dynamical landscape of these networks.

Indexed as

ConsciousnessFree energyFunctional connectivityGeneral anesthesiaNetwork dynamicsResting-state networks

Identifiers

PMID30090873
PMCPMC6063715

What OpenQuestion holds

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Registered trials

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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.