An electrophysiological marker of arousal level in humans

  1. Janna Desiree Lendner  Is a corresponding author
  2. Randolph F Helfrich
  3. Bryce A Mander
  4. Luis Romundstad
  5. Jack J Lin
  6. Matthew P Walker
  7. Pal G Larsson
  8. Robert T Knight
  1. University of California, Berkeley, United States
  2. University of Tübingen, Germany
  3. University of California, Irvine, United States
  4. University of Oslo, Norway
  5. Univsersity of Oslo, Norway

Abstract

Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, 'wake-like' EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.

Data availability

Source data files have been updated and are provided here:Lendner, Janna (2020), An Electrophysiological Marker of Arousal Level in Humans, UC Berkeley, Dataset, https://doi.org/10.6078/D1NX1V

The following data sets were generated

Article and author information

Author details

  1. Janna Desiree Lendner

    Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    For correspondence
    janna.lendner@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1967-6110
  2. Randolph F Helfrich

    Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8045-3111
  3. Bryce A Mander

    Psychiatry and Human Behavior, University of California, Irvine, Irvine, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Luis Romundstad

    Anesthesiology, University of Oslo, Oslo, Norway
    Competing interests
    The authors declare that no competing interests exist.
  5. Jack J Lin

    Neurology, University of California, Irvine, Irvine, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Matthew P Walker

    Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Pal G Larsson

    Neurosurgery, Univsersity of Oslo, Oslo, Norway
    Competing interests
    The authors declare that no competing interests exist.
  8. Robert T Knight

    Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

Deutsche Forschungsgemeinschaft (LE 3863/2-1)

  • Janna Desiree Lendner

National Institute of Neurological Disorders and Stroke (R37NS21135)

  • Robert T Knight

Deutsche Forschungsgemeinschaft (HE 8329/2-1)

  • Randolph F Helfrich

National Institute of Mental Health (R01AG03116408)

  • Matthew P Walker

National Institute of Mental Health (RF1AG05401901)

  • Matthew P Walker

National Institute of Mental Health (RF1AG05410601)

  • Matthew P Walker

National Institute of Mental Health (F32-AG039170)

  • Bryce A Mander

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Saskia Haegens, Columbia University College of Physicians and Surgeons, United States

Ethics

Human subjects: We collected four independent datasets for this study to assess the neurophysiological basis of states of reduced arousal, namely sleep and general anesthesia.Study 1 - Anesthesia scalp EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Regional Committees for Medical and Health Research Ethics in Oslo case number 2012/2015 and extension 2012/2015-8).Study 2 - Anesthesia intracranial EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Regional Committees for Medical and Health Research Ethics in Oslo case number 2012/2015 and extension 2012/2015-8).Study 3 - Sleep scalp EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Berkeley Committee for Protection of Human Subjects Protocol Number 2010-01-595).Study 4 - Sleep intracranial EEG: All patients provided informed consent according to the local ethics committees of the University of California at Berkeley and at Irvine (University of California at Berkeley Committee for the Protection of Human Subjects Protocol Number 2010-01-520; University of California at Irvine Institutional Review Board Protocol Number 2014-1522, UCB relies on UCI Reliance Number 1817) and gave their written consent before data collection.

Version history

  1. Received: January 12, 2020
  2. Accepted: July 6, 2020
  3. Accepted Manuscript published: July 28, 2020 (version 1)
  4. Version of Record published: July 31, 2020 (version 2)

Copyright

© 2020, Lendner et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 11,756
    views
  • 1,600
    downloads
  • 205
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Janna Desiree Lendner
  2. Randolph F Helfrich
  3. Bryce A Mander
  4. Luis Romundstad
  5. Jack J Lin
  6. Matthew P Walker
  7. Pal G Larsson
  8. Robert T Knight
(2020)
An electrophysiological marker of arousal level in humans
eLife 9:e55092.
https://doi.org/10.7554/eLife.55092

Share this article

https://doi.org/10.7554/eLife.55092

Further reading

    1. Neuroscience
    Alina Tetereva, Narun Pat
    Research Article

    One well-known biomarker candidate that supposedly helps capture fluid cognition is Brain Age, or a predicted value based on machine-learning models built to predict chronological age from brain MRI. To formally evaluate the utility of Brain Age for capturing fluid cognition, we built 26 age-prediction models for Brain Age based on different combinations of MRI modalities, using the Human Connectome Project in Aging (n=504, 36–100 years old). First, based on commonality analyses, we found a large overlap between Brain Age and chronological age: Brain Age could uniquely add only around 1.6% in explaining variation in fluid cognition over and above chronological age. Second, the age-prediction models that performed better at predicting chronological age did NOT necessarily create better Brain Age for capturing fluid cognition over and above chronological age. Instead, better-performing age-prediction models created Brain Age that overlapped larger with chronological age, up to around 29% out of 32%, in explaining fluid cognition. Third, Brain Age missed around 11% of the total variation in fluid cognition that could have been explained by the brain variation. That is, directly predicting fluid cognition from brain MRI data (instead of relying on Brain Age and chronological age) could lead to around a 1/3-time improvement of the total variation explained. Accordingly, we demonstrated the limited utility of Brain Age as a biomarker for fluid cognition and made some suggestions to ensure the utility of Brain Age in explaining fluid cognition and other phenotypes of interest.

    1. Developmental Biology
    2. Neuroscience
    Jonathan AC Menzies, André Maia Chagas ... Claudio R Alonso
    Research Article

    Movement is a key feature of animal systems, yet its embryonic origins are not fully understood. Here, we investigate the genetic basis underlying the embryonic onset of movement in Drosophila focusing on the role played by small non-coding RNAs (microRNAs, miRNAs). To this end, we first develop a quantitative behavioural pipeline capable of tracking embryonic movement in large populations of fly embryos, and using this system, discover that the Drosophila miRNA miR-2b-1 plays a role in the emergence of movement. Through the combination of spectral analysis of embryonic motor patterns, cell sorting and RNA in situs, genetic reconstitution tests, and neural optical imaging we define that miR-2b-1 influences the emergence of embryonic movement by exerting actions in the developing nervous system. Furthermore, through the combination of bioinformatics coupled to genetic manipulation of miRNA expression and phenocopy tests we identify a previously uncharacterised (but evolutionarily conserved) chloride channel encoding gene – which we term Movement Modulator (Motor) – as a genetic target that mechanistically links miR-2b-1 to the onset of movement. Cell-specific genetic reconstitution of miR-2b-1 expression in a null miRNA mutant background, followed by behavioural assays and target gene analyses, suggest that miR-2b-1 affects the emergence of movement through effects in sensory elements of the embryonic circuitry, rather than in the motor domain. Our work thus reports the first miRNA system capable of regulating embryonic movement, suggesting that other miRNAs are likely to play a role in this key developmental process in Drosophila as well as in other species.