Cortical excitability signatures for the degree of sleepiness in human

  1. Chin-Hsuan Chia
  2. Xin-Wei Tang
  3. Yue Cao
  4. Hua-Teng Cao
  5. Wei Zhang
  6. Jun-Fa Wu
  7. Yu-Lian Zhu
  8. Ying Chen
  9. Yi Lin
  10. Yi Wu
  11. Zhe Zhang  Is a corresponding author
  12. Ti-Fei Yuan  Is a corresponding author
  13. Rui-Ping Hu  Is a corresponding author
  1. Huashan hospital, Fudan University, China
  2. Institute of Neuroscience, China
  3. Institute of Brain Science, Fudan University, China
  4. Nantong University, China

Abstract

Sleep is essential in maintaining physiological homeostasis in the brain. While the underlying mechanism is not fully understood, a 'synaptic homeostasis' theory has been proposed that synapses continue to strengthen during awake, and undergo downscaling during sleep. This theory predicts that brain excitability increases with sleepiness. Here, we collected transcranial magnetic stimulation (TMS) measurements in 38 subjects in a 34-hour program, and decoded the relationship between cortical excitability and self-report sleepiness using advanced statistical methods. By utilizing a combination of partial least squares (PLS) regression and mixed-effect models, we identified a robust pattern of excitability changes, which can quantitatively predict the degree of sleepiness. Moreover, we found that synaptic strengthen occurred in both excitatory and inhibitory connections after sleep deprivation. In sum, our study provides supportive evidence for the synaptic homeostasis theory in human sleep and clarifies the process of synaptic strength modulation during sleepiness.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Chin-Hsuan Chia

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Xin-Wei Tang

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Yue Cao

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Hua-Teng Cao

    CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Wei Zhang

    Brain Science, Institute of Brain Science, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Jun-Fa Wu

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Yu-Lian Zhu

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Ying Chen

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Yi Lin

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  10. Yi Wu

    rehabilitation medicine, Huashan hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  11. Zhe Zhang

    CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Shanghai, China
    For correspondence
    zhezhang@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0899-8077
  12. Ti-Fei Yuan

    Psychology, Nantong University, Nantong, China
    For correspondence
    ytf0707@126.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0510-715X
  13. Rui-Ping Hu

    rehabilitation medicine, Huashan hospital, Fudan University, shanghai city, China
    For correspondence
    wuyi4000@163.com
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Key Research and Development Program of China (2018YFC2001700)

  • Yi Wu

the Key Projects of Shanghai Science and Technology on Biomedicine (18411962300)

  • Rui-Ping Hu

Shanghai Health and Family Planning Commission project (201840225)

  • Yu-Lian Zhu

Shanghai Municipal Key Clinical Specialty (s.shslczdzk02702)

  • Yi Wu

the Key Projects of Shanghai Science and Technology on Biomedicine (20412420200)

  • Yi Wu

Natural Science Foundation of China grant (32071010)

  • Zhe Zhang

Shanghai Pujiang Program (20PJ1415000)

  • Zhe Zhang

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

Reviewing Editor

  1. Laura Dugué, Uni­ver­sité de Paris, France

Ethics

Human subjects: 1. That informed consent, and consent to publish, was obtained2. This study was designed as a prospective self-controlled study. The Ethics Committee of Huashan Hospital approved the study (2017-410) and was registered on the Chinese Clinical Trial Registry (ChiCTR1800016771).

Version history

  1. Received: November 22, 2020
  2. Accepted: July 26, 2021
  3. Accepted Manuscript published: July 27, 2021 (version 1)
  4. Version of Record published: August 18, 2021 (version 2)

Copyright

© 2021, Chia 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

  • 1,530
    views
  • 271
    downloads
  • 8
    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. Chin-Hsuan Chia
  2. Xin-Wei Tang
  3. Yue Cao
  4. Hua-Teng Cao
  5. Wei Zhang
  6. Jun-Fa Wu
  7. Yu-Lian Zhu
  8. Ying Chen
  9. Yi Lin
  10. Yi Wu
  11. Zhe Zhang
  12. Ti-Fei Yuan
  13. Rui-Ping Hu
(2021)
Cortical excitability signatures for the degree of sleepiness in human
eLife 10:e65099.
https://doi.org/10.7554/eLife.65099

Share this article

https://doi.org/10.7554/eLife.65099

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.