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Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency

Overview of attention for article published in Frontiers in Psychology, April 2016
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Title
Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency
Published in
Frontiers in Psychology, April 2016
DOI 10.3389/fpsyg.2016.00492
Pubmed ID
Authors

B. Alexander Diaz, Richard Hardstone, Huibert D. Mansvelder, Eus J. W. Van Someren, Klaus Linkenkaer-Hansen

Abstract

Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
United States 1 1%
Unknown 96 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 20%
Researcher 14 14%
Student > Master 13 13%
Student > Bachelor 8 8%
Student > Doctoral Student 7 7%
Other 12 12%
Unknown 24 24%
Readers by discipline Count As %
Psychology 22 22%
Neuroscience 19 19%
Medicine and Dentistry 7 7%
Engineering 4 4%
Agricultural and Biological Sciences 3 3%
Other 10 10%
Unknown 33 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2016.
All research outputs
#20,320,000
of 22,862,742 outputs
Outputs from Frontiers in Psychology
#24,171
of 29,906 outputs
Outputs of similar age
#254,967
of 300,876 outputs
Outputs of similar age from Frontiers in Psychology
#395
of 427 outputs
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We're also able to compare this research output to 427 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.