ArticleSleep2025
EEG-based prediction of reaction time during sleep deprivation.
Article in Sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
Who cites it
4 citing papers in PubMed.
- Exploring the differences in neural oscillation mechanisms before and after sleep deprivation.Frontiers in neuroscience · 2026Article
- Article
- Adaptive proximity to criticality underlies amplification of ultra-slow fluctuations during free recall.PLoS computational biology · 2025Article
- Acute Sleep Deprivation Suppresses Sleep Spindles in Mice.Nature and science of sleep · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Prolonged wakefulness is known to adversely affect basic cognitive abilities such as object recognition and decision-making. It affects the dynamics of neuronal networks in the brain and can even lead to hallucinations and epileptic seizures. In cognitive-intensive workplaces, there is a requirement to refine an objective method of quantifying the current level of cognitive capabilities, rather than relying on subjective self-reporting. In this study, we compiled electroencephalography (EEG) recordings from several sleep-deprivation workshops held by the Israeli Air Force, done by flight cadets and unmanned aerial vehicle operators. By extracting a wide range of EEG features and applying machine-learning techniques, we were able to accurately predict the reaction time of participants undergoing a simple psychomotor vigilance task, which acted as a stand-in for basic cognitive functions. Furthermore, through the use of interpretability methods, we examined the importance of different EEG features and their contribution to changes in the behavioral metrics.
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Registered trials
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.