2 items tagged with 'eeg'.
Recorded and Reported Sleepiness: The Association Between Brain Arousal in Resting State and Subjective Daytime Sleepiness.
Objectives: Daytime sleepiness is a significant public health concern. Early evidence points toward the computerized VIGALL (Vigilance Algorithm Leipzig) as time-efficient tool to assess sleepiness … objectively. In the present study, we investigated the association between VIGALL variables of EEG vigilance (indicating brain arousal in resting state) and subjective daytime sleepiness in the LIFE cohort study. Additionally, we validated VIGALL against the self-rated likelihood of having fallen asleep during the conducted resting EEG and against heart periods. Methods: Participants of the primary sample LIFE 60+ (N = 1927, 60-79 years) and replication sample LIFE 40+ (N = 293, 40-56 years) completed the Epworth Sleepiness Scale (ESS). After an average interval of 3 weeks (LIFE 60+) and 65 weeks (LIFE 40+), respectively, participants underwent a single 20-minute resting EEG, analyzed using VIGALL 2.1. Results: Analyses revealed significant associations between ESS and EEG vigilance in LIFE 60+ (rho = -0.17, p = 1E-14) and LIFE 40+ (rho = -0.24, p = 2E-5). Correlations between EEG vigilance and self-rated sleep likelihood reached rho = -0.43 (p = 2E-91) in LIFE 60+ and rho = -0.50 (p = 5E-20) in LIFE 40+. Overall, strongest correlations were obtained for EEG vigilance variable "slope index." Furthermore, lower EEG vigilance was consistently associated with longer heart periods. Conclusions: The present study contributes to the validation of VIGALL. Despite the considerable interval between ESS and EEG assessment dates, the strength of ESS-VIGALL association approximates prior ESS-Multiple Sleep Latency Test results. In this light, VIGALL might constitute an economical choice for the objective assessment of daytime sleepiness in large cohort studies. The discriminative power to identify disorders of hypersomnolence, however, remains to be addressed.
Authors: P. Jawinski, J. Kittel, C. Sander, J. Huang, J. Spada, C. Ulke, K. Wirkner, T. Hensch, U. Hegerl
Date Published: 1st Jul 2017
Publication Type: Journal article
PubMed ID: 28605521
Citation: Sleep. 2017 Jul 1;40(7). pii: 3866822. doi: 10.1093/sleep/zsx099.
Created: 13th May 2019 at 09:58, Last updated: 7th Dec 2021 at 17:58
Tobacco use is associated with reduced amplitude and intensity dependence of the cortical auditory evoked N1-P2 component.
RATIONALE: Tobacco use is linked to cerebral atrophy and reduced cognitive performance in later life. However, smoking-related long-term effects on brain function remain largely uncertain. Previous … studies suggest that nicotine affects serotonergic signaling, and the intensity dependence (alias loudness dependence) of the auditory evoked N1-P2 potential has been proposed as a marker of serotonergic neurotransmission. OBJECTIVE: In the present study, we assesed the effects of chronic smoking on amplitude and intensity dependence of the auditory evoked N1-P2 potential. METHODS: Subjects underwent a 15-min intensity dependence of auditory evoked potentials (IAEP) paradigm. From N = 1739 eligible subjects (40-79 years), we systematically matched current smokers, ex-smokers, and never-smokers by sex, age, alcohol and caffeine consumption, and socioeconomic status. Between-group differences and potential dose-dependencies were evaluated. RESULTS: Analyses revealed higher N1-P2 amplitudes and intensity dependencies in never-smokers relative to ex- and current smokers, with ex-smokers exhibiting intermediate intensity dependencies. Moreover, we observed pack years and number of cigarettes consumed per day to be inversely correlated with amplitudes in current smokers. CONCLUSIONS: According to the IAEP serotonin hypothesis, our results suggest serotonin activity to be highest in current smokers, intermediate in ex-smokers, and lowest in never-smokers. To our knowledge, the present study is the first providing evidence for a dose-dependent reduction in N1-P2 amplitudes. Further, we extend prior research by showing reduced amplitudes and intensity dependencies in ex-smokers even 25 years, on average, after cessation. While we can rule out several smoking-related confounders to bias observed associations, causal inferences remain to be established by future longitudinal studies.
Authors: P. Jawinski, N. Mauche, C. Ulke, J. Huang, J. Spada, C. Enzenbach, C. Sander, U. Hegerl, T. Hensch
Date Published: 18th Mar 2016
Publication Type: Not specified
PubMed ID: 26983415
Citation: Psychopharmacology (Berl). 2016 Jun;233(11):2173-2183. doi: 10.1007/s00213-016-4268-z. Epub 2016 Mar 17.
Created: 10th May 2019 at 13:58, Last updated: 7th Dec 2021 at 17:58