Search

Background: The aim of the present study was to evaluate the stability of brain arousal in adult attention-deficit/hyperactivity disorder (ADHD) outpatients with and without depressive symptomatology, and its association with depressive symptom severity and absolute electroencephalogram (EEG) power in different frequency bands., Methods: We included 31 outpatient adults (45.16% females), who were diagnosed according to DSM-IV and received no medication. Their arousal stability score (index of the steepness of arousal decline during a 15-min EEG under resting conditions), the absolute EEG power and self-reports, including depressive and ADHD-related symptoms, were analyzed. Participants were split into an unstable and stable arousal group based on the median (= 6) of the arousal stability score., Results: ADHD patients in the stable group reported more severe depressive symptoms (p = 0.018) and showed reduced absolute EEG power in the delta (0.002 ≤ p ≤ 0.025) and theta (0.011 ≤ p ≤ 0.034) bands compared to those in the unstable group. There was no correlation between the arousal stability score and self-report-scales concerning ADHD-related symptoms (0.214 ≤ p ≤ 0.989), but a positive association with self-reported depressive severity (p = 0.018) and negative association with powers in the EEG delta and theta bands (0.001 ≤ p ≤ 0.033)., Conclusions: In view of high comorbidity of depression and ADHD in adult patients, these findings support the assumption that brain arousal regulation could be considered as a helpful marker for the clinical differentiation between ADHD and depression.

Several studies have found upregulated brain arousal during 15-minute EEG recordings at rest in depressed patients. However, studies based on shorter EEG recording intervals are lacking. Here we aimed to compare measures of brain arousal obtained from 2-minute EEGs at rest under eyes-closed condition in depressed patients and healthy controls in a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). We expected that depressed patients would show stable and elevated brain arousal relative to controls. Eighty-seven depressed patients and 36 healthy controls from four research sites in the United States were included in the analyses. The Vigilance Algorithm Leipzig (VIGALL) was used for the fully automatic classification of EEG-vigilance stages (indicating arousal states) of 1-second EEG segments; VIGALL-derived measures of brain arousal were calculated. We found that depressed patients scored higher on arousal stability ( Z = -2.163, P = .015) and A stages (dominant alpha activity; P = .027) but lower on B1 stages (low-voltage non-alpha activity, P = .008) compared with healthy controls. No significant group differences were observed in Stage B2/3. In summary, we were able to demonstrate stable and elevated brain arousal during brief 2-minute recordings at rest in depressed patients. Results set the stage for examining the value of these measures for predicting clinical response to antidepressants in the entire EMBARC sample and evaluating whether an upregulated brain arousal is particularly characteristic for responders to antidepressants.

EEG measures of arousal have been suggested as diagnostic and predictive biomarkers for major depression. The aim of the present study was to examine whether self-rated depression severity in SSRI-medicated patients with major depression (MD) is associated with EEG measures of brain arousal. Based on previous studies, we expected that a higher level of brain arousal and a slower arousal decline during a 15-min EEG recording are associated with higher symptom severity as assessed with the Beck Depression Inventory (BDI) at the time of the EEG recording. EEGs of 78 MD patients and 46 healthy controls were analyzed. Brain arousal was assessed using the Vigilance Algorithm Leipzig (VIGALL 2.1). Based on automatically classified 1-s segments (EEG-vigilance Stages 0, A1, A2, A3, B1, B2/3 or C) we computed indices to assess the level (mean EEG-vigilance) and the decline of arousal (slope index) during the 15-min resting state EEG under eyes-closed condition. We found that a higher arousal level and a slower arousal decline corresponded to higher severity of depressive symptoms (rho = 0.238, p = .018; and rho = 0.236; p = .019). Self-rated non-remitters (BDI>12) had a higher arousal level (mean EEG-vigilance: t 76  = -2.19, p = .016) and slower arousal decline (slope index: Z = -2.08, p = .019) during the 15-min recording as compared to remitters. Similar results were obtained between non-remitters and healthy controls (mean EEG-vigilance: t 102  = -2.75, p = .004; slope index: Z = -1.92, p = .028), but not between remitters and controls (p > .260). The findings support the model that brain arousal regulation plays an important role in the pathophysiology and treatment of MD., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Autonomic nervous system (ANS) activity has been shown to vary with the state of brain arousal. In a previous study, this association of ANS activity with distinct states of brain arousal was demonstrated using 15-min EEG data, but without directly controlling for possible time-on-task effects. In the current study we examine ANS-activity in fine-graded EEG-vigilance stages (indicating states of brain arousal) during two conditions of a 2-h oddball task while controlling for time-on-task. In addition, we analyze the effect of time-on-task on ANS-activity while holding the level of brain arousal constant., Methods: Heart rate and skin conductance level of healthy participants were recorded during a 2-h EEG with eyes closed under simultaneous presentation of stimuli in an ignored (N = 39) and attended (N = 39) oddball condition. EEG-vigilance stages were classified using the Vigilance Algorithm Leipzig (VIGALL 2.1). The time-on-task effect was tested by dividing the EEG into four 30-min consecutive time blocks. ANS-activity was compared between EEG-vigilance stages across the entire 2 h and within each time block., Results: We found a coherent decline of ANS-activity with declining brain arousal states, over the 2-h recording and in most cases within each 30-min block in both conditions. Furthermore, we found a significant time-on-task effect on heart rate, even when arousal was kept constant. It was most pronounced between the first and all subsequent blocks and could have been a consequence of postural change at the beginning of the experiment., Conclusion: Our findings contribute to the validation of VIGALL 2.1 using ANS parameters in 2-h EEG recording under oddball conditions.

The main aim of the current study was to test the hypothesis that adult patients with attention-deficit/hyperactivity disorder (ADHD) have less stable brain arousal regulation than healthy controls. We objectively assessed brain arousal regulation using the Vigilance Algorithm Leipzig (VIGALL 2.1) to analyze 15-min resting EEG data of thirty-three ADHD patients and thirty-five matched controls. Based on automatically classified 1-s segments we computed mean EEG-vigilance (indexing arousal level) and arousal stability score (indexing arousal regulation). Adult ADHD patients showed significantly lower arousal levels and significantly less stable brain arousal regulation than controls. Multiple regression analysis indicated that arousal regulation (i.e., arousal stability score) predicted the retrospectively-assessed severity of childhood ADHD symptoms, supporting the trait aspect of brain arousal regulation. Our findings support the arousal regulation model of ADHD, which interprets hyperactivity and sensation seeking as an autoregulatory reaction to an unstable regulation of brain arousal. EEG-based arousal parameters may be candidate biomarkers for adult ADHD., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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., (© Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Objectives: The arousal regulation model of affective disorders attributes an important role in the pathophysiology of affective disorders to dysregulation of brain arousal regulation. According to this model, sensation avoidance and withdrawal in depression and sensation seeking and hyperactivity in mania can be explained as auto-regulatory attempts to counteract a tonically high (depression) or unstable (mania) arousal. The aim of this study was to compare brain arousal regulation between manic and depressive bipolar patients and healthy controls. We hypothesized that currently depressed patients with bipolar disorder show hyperstable arousal regulation, while currently manic patients show unstable arousal regulation., Methods: Twenty-eight patients with bipolar disorder received a 15-min resting electroencephalogram (EEG) during a depressive episode and 19 patients received the same during a manic/hypomanic episode. Twenty-eight healthy control subjects were matched for age and sex. The Vigilance Algorithm Leipzig (VIGALL), which classifies 1-s EEG segments as one of seven EEG-vigilance substages, was used to measure brain arousal regulation., Results: Manic patients showed more unstable EEG-vigilance regulation as compared to the control sample (P = .004) and to patients with a depressive episode (P ≤ .001). Depressive patients had significantly higher mean vigilance levels (P = .045) than controls., Conclusions: A clear difference was found in the regulation of brain arousal of manic patients vs depressive patients and controls. These data suggest that brain arousal might depend on the current mood state, which would support the arousal regulation model of affective disorders., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)