Enhanced Vigilance Stability during Daytime in Insomnia Disorder
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Participants
2.2. Procedures
2.3. Resting-State EEG Measurement
2.4. Polysomnography
2.5. Psychometric Measures
2.6. EEG Vigilance Classification Using VIGALL
- Stage 0 representing an activated wake state as seen in mental effort. This stage is recognized by a low amplitude EEG with non-alpha-activity, typically without the presence of slow horizontal eye movements.
- Stage A represents relaxed wakefulness: The EEG is dominated by prominent alpha activity. Stage A can be subdivided into A1, A2 and A3, according to the degrees of frontalization of alpha activity from occipital to anterior brain regions. A predominant occipital alpha-activity characterizes stage A1, while alpha-activity shifts to frontal and temporal regions in A2/3 stages accompanied by a decrease in amplitude.
- Stage B corresponds to drowsiness. This stage can be divided into sub-stages B1 (characterized by low amplitude EEG without alpha-activity, with the presence of slow horizontal eye movements) and B2/3 (dominated by theta and/or delta activity).
- Stage C reflects sleep onset. Since this stage is characterized by sleep spindles and K-complexes, its classification is bound to the manually set markers of these EEG phenomena in EEG epochs of 1 s. Spindles and K-complexes were identified according to the criteria of the American Academy of Sleep Medicine [31] by an experienced rater certified in sleep medicine.
- (a)
- For each recording minute as well as the total recording period, the absolute amount of vigilance stages (0, A1, A2/3, B1, B2/3 and C) was counted, and the percentage amount was calculated (amount ∗ 100/total number of non-artefact segments).
- (b)
- Furthermore, each EEG vigilance stage is assigned a numerical score ranging from 1–7 (C = 1, B2/3 = 2, B1 = 3, A3 = 4, A2 = 5, A1 = 6, 0 = 7). Again for each recording minute as well as the total recording, a mean vigilance value (MVV) was calculated by averaging the scores of all non-artefact segments.
- (c)
- In addition, an arousal stability score (ASS) was determined for each subject’s EEG vigilance time course to quantify the speed and extent of the respective decline in brain arousal. For this, successive blocks with a duration of 1 min were analyzed concerning fulfilment of one of the following criteria: (I) at least 2/3 of all segments classified as 0/A or 0/A1 stages; (II) at least 1/3 of all segments classified as B stages (B1 + B2/3); (III) at least 1/3 of all segments classified as B2/3 stages; (IV) occurrence of at least 1 C stage. The 20-min EEG recording was separated into four consecutive 5-min epochs (quartiles). If only criterion I was fulfilled during the whole recording, a high ASS-score is given (14 (only 0/A1 stages) or 13 (only 0/A-stages)). Depending on which of the criteria II to IV were achieved in which quarter of the measurement, increasingly lower ASS scores were awarded (e.g., C stages reached within the last quarter: ASS = 4, C-stages reached within the first quarter: ASS = 1). Thus, higher ASS scores correspond to higher arousal stability.
- (d)
- Individual time courses were compared with prototypical time courses corresponding to the three prototypical types of brain arousal regulation according the model of Hegerl et al. [43]: adaptive vigilance regulation (graduated decrease in vigilance over time), unstable vigilance regulation (accelerated decrease in vigilance) and (hyper) stable vigilance regulation (absence of vigilance decrease). Each participant was assigned to the prototype course with the smallest sum of deviation squares. Post hoc, an additional model distinguishing four prototypes of brain arousal regulation was calculated. In this model, in addition to the adaptive and the unstable regulatory type, a stable (no vigilance decrease over time) and a hyperstable regulatory (retention in the highest arousal states) type were distinguished.
2.7. Statistical Analysis
3. Results
3.1. Group Differences in Polysomnographic and Psychometric Measures
3.2. Daytime Vigilance Stability
3.3. Insomnia Subtypes with Respect to the Extent of Objective Sleep Disturbance
4. Discussion
Author Contributions
Funding
Conflicts of Interest
References
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Insomnia (n = 34) | Healthy Controls (n = 25) | t | p | |
---|---|---|---|---|
Demographics | ||||
Age (years) | 44.1 ± 12.5 | 39.2 ± 13.0 | 1.5 | 0.153 |
Sex (w/m) | 27/7 | 19/6 | 0.1 1 | 0.755 |
Psychometric data | ||||
Disturbed sleep quality (PSQI) | 11.9 ± 3.1 2 | 4.3 ± 2.3 | 9.9 | 0.000 * |
Insomnia severity (ISI) | 17.5 ± 4.3 3 | 3.0 ± 3.1 4 | 14.2 | 0.000 * |
Sleep-related beliefs (MCQ-I) | 123.3 ± 30.1 | 98.4 ± 21.4 | 3.5 | 0.001 * |
Stress reactivity (PSRS-23) | 25.6 ± 9.1 | 16.7 ± 5.5 | 4.7 | 0.000 * |
Trait arousal (APS) | 33.9 ± 6.2 | 28.4 ± 4.3 | 3.8 | 0.000 * |
Sleepiness (ESS) | 7.0 ± 5.2 | 7.2 ± 4.3 | −0.2 | 0.876 |
Depressiveness (BDI 1–10) | 3.2 ± 3.3 2 | 1.2 ± 1.8 | 2.7 | 0.010 * |
Morningness–Eveningness (D-MEQ) | 56.0 ± 8.2 5 | 54.6 ± 9.1 | 0.6 | 0.544 |
State arousal (PSAS) | ||||
Arousal | 26.6 ± 8.6 | 18.3 ± 3.1 | 4.6 | 0.000 * |
Somatic arousal | 12.1 ± 4.6 | 8.8 ± 1.2 | 4.0 | 0.000 * |
Cognitive arousal | 14.5 ± 5.5 | 9.5 ± 2.5 | 4.6 | 0.000 * |
State Sleepiness (KSS) | ||||
Pre EEG | 5.3 ± 1.7 | 3.5 ± 1.9 | 3.8 | 0.000 * |
Post EEG | 5.3 ± 2.0 | 4.7 ± 2.1 | 1.1 | 0.274 |
pre–post diff | 0.0 ± 2.4 | 1.2 ± 2.8 | −1.8 | 0.085 (*) |
Sleep parameters | ||||
Sleep latency (min) | 31.9 ± 34.2 | 25.6 ± 17.8 | 0.8 | 0.405 |
Sleep efficiency (%) | 70.7 ± 20.1 | 83.6 ± 12.9 | −3.0 | 0.004 * |
WASO (min) | 91.7 ± 63.9 | 42.9 ± 42.8 | 3.5 | 0.001 * |
Total sleep time (min) | 323 ± 92 | 382 ± 58 | −3.0 | 0.004 * |
% Stage 1 | 14.2 ± 5.8 | 12.2 ± 5.2 | 1.4 | 0.171 |
% Stage 2 | 38.4 ± 11.3 | 43.9 ± 8.7 | −2.0 | 0.051 (*) |
% Stage 3 | 13.4 ± 7.4 | 20.8 ± 9.7 | −3.3 | 0.001 * |
% REM | 10.5 ± 5.1 | 12.7 ± 5.4 | −1.6 | 0.125 |
Arousal index | 17.3 ± 7.1 | 14.0 ± 8.0 | 1.7 | 0.104 |
Number of wake periods | 29.8 ± 13.4 | 23.8 ± 12.0 | 1.8 | 0.081 (*) |
Insomnia (n = 34) | Healthy Subjects (n = 25) | |||
---|---|---|---|---|
r | p | r | p | |
Subjective sleep | ||||
Insomnia severity (ISI) | −0.116 1 | 0.529 | 0.009 2 | 0.968 |
Objective sleep | ||||
Sleep efficiency (SE) | −0.058 | 0.372 3 | −0.064 | 0.761 |
Arousal index (AI) | 0.199 | 0.129 3 | −0.106 | 0.614 |
Psychometric parameters | ||||
Stress reactivity (PSRS-23) | −0.035 | 0.846 | −0.093 | 0.660 |
Trait arousal (APS) | 0.075 | 0.671 | 0.058 | 0.784 |
State arousal (PSAS) | ||||
Arousal | 0.135 | 0.447 | −0.139 | 0.507 |
Somatic arousal | 0.145 | 0.414 | −0.121 | 0.565 |
Cognitive arousal | 0.148 | 0.403 | 0.124 | −0.554 |
Insomnia-related beliefs (MCQ-I) | −0.205 | 0.244 | 0.045 | 0.836 |
Depressiveness (BDI 1–10) | −0.060 1 | 0.745 | 0.236 | 0.257 |
Low Sleep Efficiency (n = 17) | High Sleep Efficiency (n = 17) | t | p | |
---|---|---|---|---|
Arousal Stability Score | 7.9 ± 4.4 | 8.8 ± 3.8 | 0.6 1 | 0.534 |
Subjective insomnia severity | ||||
Disturbed sleep quality (PSQI) | 11.7 ± 3.2 | 12.1 ± 3.0 | 0.3 | 0.755 |
Insomnia severity (ISI) | 17.4 ± 3.9 | 17.7 ± 4.8 | 0.2 | 0.805 |
Psychometrics | ||||
Insomnia-related beliefs (MCQ-I) | 114.8 ± 24.4 | 131.8 ± 33.4 | 2.9 | 0.100 |
Depressiveness (BDI 1–10) | 2.5 ± 2.3 | 4.0 ± 4.0 | 1.3 | 0.191 |
Stress reactivity (PSRS-23) | 27.1 ± 8.6 | 24.1 ± 9.5 | −0.9 | 0.352 |
Sleepiness (ESS) | 6.4 ± 5.5 | 7.9 ± 5.0 | 0.7 | 0.520 |
Trait arousal (APS) | 34.2 ± 5.1 | 33.6 ± 7.2 | −0.3 | 0.786 |
State sleepiness (KSS) | ||||
pre EEG | 5.8 ± 1.5 | 4.8 ± 1.9 | −1.7 | 0.095 (*) |
post EEG | 5.4 ± 1.7 | 5.1 ± 2.3 | −0.4 | 0.671 |
pre post diff | −0.4 ± 1.8 | 0.4 ± 3.0 | 0.8 | 0.410 |
State Arousal (PSAS) | ||||
Arousal | 26.2 ± 7.9 | 26.9 ± 9.4 | 0.2 | 0.830 |
Somatic arousal | 11.7 ± 4.0 | 12.4 ± 5.1 | 0.4 | 0.659 |
Cognitive arousal | 14.5 ± 5.2 | 14.5 ± 5.9 | 0.0 | 1.00 |
History of previous depressive episode | 6/17 | 3/17 | 1.4 2 | 0.244 |
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Losert, A.; Sander, C.; Schredl, M.; Heilmann-Etzbach, I.; Deuschle, M.; Hegerl, U.; Schilling, C. Enhanced Vigilance Stability during Daytime in Insomnia Disorder. Brain Sci. 2020, 10, 830. https://doi.org/10.3390/brainsci10110830
Losert A, Sander C, Schredl M, Heilmann-Etzbach I, Deuschle M, Hegerl U, Schilling C. Enhanced Vigilance Stability during Daytime in Insomnia Disorder. Brain Sciences. 2020; 10(11):830. https://doi.org/10.3390/brainsci10110830
Chicago/Turabian StyleLosert, Ariane, Christian Sander, Michael Schredl, Ivonne Heilmann-Etzbach, Michael Deuschle, Ulrich Hegerl, and Claudia Schilling. 2020. "Enhanced Vigilance Stability during Daytime in Insomnia Disorder" Brain Sciences 10, no. 11: 830. https://doi.org/10.3390/brainsci10110830
APA StyleLosert, A., Sander, C., Schredl, M., Heilmann-Etzbach, I., Deuschle, M., Hegerl, U., & Schilling, C. (2020). Enhanced Vigilance Stability during Daytime in Insomnia Disorder. Brain Sciences, 10(11), 830. https://doi.org/10.3390/brainsci10110830