K-complexes are a sensitive marker of noise-related sensory processing during sleep: A pilot study

Bastien Lechat, Kristy Hansen, Gorica Micic, Felix Decup, Claire Dunbar, Tessa Liebich, Peter Catcheside, Branko Zajamsek

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Study Objectives: The primary aim of this study was to examine dose-response relationships between sound pressure levels (SPLs) and K-complex occurrence probability for wind farm and road traffic noise. A secondary aim was to compare K-complex dose-responses to manually scored electroencephalography arousals and awakenings.

Methods: Twenty-five participants underwent polysomnography recordings and noise exposure during sleep in a laboratory. Wind farm and road traffic noise recordings of 20-sec duration were played in random order at 6 SPLs between 33 and 48 dBA during established N2 or deeper sleep. Noise periods were separated with periods of 23 dBA background noise. K-complexes were scored using a validated algorithm. K-complex occurrence probability was compared between noise types controlling for noise SPL, subjective noise sensitivity, and measured hearing acuity.

Results: Noise-induced K-complexes were observed in N2 sleep at SPLs as low as 33 dBA (Odds ratio, 33 dBA vs 23 dBA, mean (95% confidence interval); 1.75 (1.16, 2.66)) and increased with SPL. EEG arousals and awakenings were only associated with noise above 39 dBA in N2 sleep. K-complexes were 2 times more likely to occur in response to noise than EEG arousals or awakenings. Subjective noise sensitivity and hearing acuity were associated with the K-complex occurrence, but not arousal or awakening. Noise type did not detectably influence K-complexes, EEG arousals, or awakening responses.

Conclusion: These findings support that K-complexes are a sensitive marker of sensory processing of environmental noise during sleep and that increased hearing acuity and decreased self-reported noise sensitivity increase K-complex probability.

Original languageEnglish
Article numberzsab065
Number of pages10
JournalSLEEP
Volume44
Issue number9
DOIs
Publication statusPublished - Sep 2021

Bibliographical note

Publisher Copyright:
© 2021 Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Keywords

  • arousals
  • artificial Intelligence
  • awakenings
  • deep learning
  • disrupted sleep
  • environmental noise
  • K-complex
  • noise sensitivity
  • sleep fragmentation

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