Objectives: EEG arousals are associated with autonomic activations. Visual EEG arousal scoring is time consuming and suffers from low interobserver agreement. We hypothesized that information on changes in heart rate alone suffice to predict the occurrence of cortical arousal.
Methods: Two visual AASM EEG arousal scorings of 56 healthy subject nights (mean age 37.0 +/- 12.8 years, 26 male) were obtained. For each of 5 heartbeats following the onset of 3581 consensus EEG arousals and of an equal number of control conditions, differences to a moving median were calculated and used to estimate likelihood ratios (LRs) for 10 categories of heartbeat differences. Comparable to 5 consecutive diagnostic tests, these LRs were used to calculate the probability of heart rate responses being associated with cortical arousals.
Results: EEG and ECG arousal indexes agreed well across a wide range of decision thresholds, resulting in a receiver operating characteristic (ROC) with an area under the curve of 0.91. For the decision threshold chosen for the final analyses, a sensitivity of 68.1% and a specificity of 95.2% were obtained. ECG and EEG arousal indexes were poorly correlated (r = 0.19, P <0.001, ICC = 0.186), which could in part be attributed to 3 outliers. The Bland-Altman plot showed an unbiased estimation of EEG arousal indexes by ECG arousal indexes with a standard deviation of +/- 7.9 arousals per hour sleep. In about two-thirds of all cases, ECG arousal scoring was matched by at least one (22.2%) or by both (42.5%) of the visual scorings. Sensitivity of the algorithm increased with increasing duration of EEG arousals. The ECG algorithm was also successfully validated with 30 different nights of 10 subjects (mean age 35.3 [ 13.6 years, 5 male).
Conclusions: In its current version, the ECG algorithm cannot replace visual EEG arousal scoring. Sensitivity for detecting <10-s EEG arousals needs to be improved. However, in a nonclinical population, it may be valuable to supplement visual EEG arousal scoring by this automatic, objective, reproducible, cheap, and time-saving method.
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http://dx.doi.org/10.1093/sleep/30.10.1349 | DOI Listing |
Psychophysiology
March 2025
Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state.
View Article and Find Full Text PDFJ Biomed Sci
March 2025
GIGA-Institute, CRC-Human Imaging, University of Liège, Bâtiment B30, 8 Allée du Six Août, Sart Tilman, 4000, Liège, Belgium.
Background: Animal studies established that the locus coeruleus (LC) plays important roles in sleep and wakefulness regulation. Whether it contributes to sleep variability in humans is not yet established. Here, we investigated if the in vivo activity of the LC is related to the variability in the quality of Rapid Eye Movement (REM) sleep.
View Article and Find Full Text PDFSci Rep
March 2025
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, 400715, China.
Anxiety is an interactive disorder of the mind and body, characterized by excessive worry about uncertain future events and a dysfunction of the autonomic nervous system. Previous studies have shown that slow, deep breathing can reduce physical tension, and anxiety. Although we know that slow and deep breathing techniques can effectively regulate anxiety and other emotions, the psychological and neurophysiological mechanisms of slow breathing on anxiety have not been systematically explored.
View Article and Find Full Text PDFFront Behav Neurosci
February 2025
Department of Cognitive Science, University of California, Irvine, CA, United States.
Emotional memories change over time, but the mechanisms supporting this change are not well understood. Sleep has been identified as one mechanism that supports memory consolidation, with sleep selectively benefitting negative emotional consolidation at the expense of neutral memories, with specific oscillatory events linked to this process. In contrast, the consolidation of neutral and positive memories, compared to negative memories, has been associated with increased vagally mediated heart rate variability (HRV) during wakefulness.
View Article and Find Full Text PDFSci Rep
March 2025
School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Music can effectively influence human emotions, with different melodies and rhythms eliciting varying emotional responses. Among these, tempo is one of the most important parameters affecting emotions. This study explores the impact of music tempo on emotional states and the associated brain functional networks.
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