RoWDI: rolling window detection of sleep intrusions in the awake brain using fMRI
Journal article
Poudel, Govinda R., Hawes, Stephanie, Innes, Carrie R. H., Parsons, Nicholas, Drummond, Sean P. A., Caeyensberghs, Karen and Jones, Richard D.. (2021). RoWDI: rolling window detection of sleep intrusions in the awake brain using fMRI. Journal of Neural Engineering. 18(5), p. Article 056063. https://doi.org/10.1088/1741-2552/ac2bb9
Authors | Poudel, Govinda R., Hawes, Stephanie, Innes, Carrie R. H., Parsons, Nicholas, Drummond, Sean P. A., Caeyensberghs, Karen and Jones, Richard D. |
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Abstract | Objective. Brief episodes of sleep can intrude into the awake human brain due to lack of sleep or fatigue—compromising the safety of critical daily tasks (i.e. driving). These intrusions can also introduce artefactual activity within functional magnetic resonance imaging (fMRI) experiments, prompting the need for an objective and effective method of removing them. Approach. We have developed a method to track sleep-like events in awake humans via rolling window detection of intrusions (RoWDI) of fMRI signal template. These events can then be used in voxel-wise event-related analysis of fMRI data. To test this approach, we generated a template of fMRI activity associated with transition to sleep via simultaneous fMRI and electroencephalogram (EEG) (N = 10). RoWDI was then used to identify sleep-like events in 20 individuals performing a cognitive task during fMRI after a night of partial sleep deprivation. This approach was further validated in an independent fMRI dataset (N = 56). Main results. Our method (RoWDI) was able to infer frequent sleep-like events during the cognitive task performed after sleep deprivation. The sleep-like events were associated with on average of 20% reduction in pupil size and prolonged response time. The blood-oxygen-level-dependent activity during the sleep-like events covered thalami-cortical regions, which although spatially distinct, co-existed with, task-related activity. These key findings were validated in the independent dataset. Significance. RoWDI can reliably detect spontaneous sleep-like events in the human brain. Thus, it may also be used as a tool to delineate and account for neural activity associated with wake-sleep transitions in both resting-state and task-related fMRI studies. |
Keywords | sleep; drowsiness; local sleep; vigilance; mental fatigue; sleep deprivation |
Year | 2021 |
Journal | Journal of Neural Engineering |
Journal citation | 18 (5), p. Article 056063 |
Publisher | Institute of Physics Publishing Ltd. |
ISSN | 1741-2560 |
Digital Object Identifier (DOI) | https://doi.org/10.1088/1741-2552/ac2bb9 |
Scopus EID | 2-s2.0-85118665512 |
Page range | 1-9 |
Funder | Australian Catholic University (ACU) |
Royal Society of New Zealand | |
Monash University | |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 19 Oct 2021 |
Publication process dates | |
Accepted | 30 Sep 2021 |
Deposited | 23 Nov 2022 |
https://acuresearchbank.acu.edu.au/item/8y73v/rowdi-rolling-window-detection-of-sleep-intrusions-in-the-awake-brain-using-fmri
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