EEG-vigilance regulation during the resting state in obsessive–compulsive disorder

Olbrich, Sebastian; Olbrich, H. M.; Jahn, Ina; Sander, Christian; Adamaszek, Michael; Hegerl, Ulrich; Reque, Fred; Stengler, Katarina

doi:10.1016/j.clinph.2012.08.018

Cited by 18 publications

(14 citation statements)

References 28 publications

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“…Using VIGALL, further evidence for unstable arousal in ADHD has been given [67] . In accordance with the assumption of hyperarousal in obsessive-compulsive disorder, hyperstable arousal regulation was demonstrated in obsessive-compulsive disorder compared to matched controls [68] . Another field for the application of VIGALL are the many groups of patients suffering from fatigue.…”

Section: Application Of Vigallmentioning

confidence: 71%

Assessment of Wakefulness and Brain Arousal Regulation in Psychiatric Research

Sander¹,

Hensch²,

Wittekind³

et al. 2015

Neuropsychobiology

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tion of wakefulness to the environmental and situational needs so that the optimal balance between energy conservation and responsiveness can be obtained. Since one approach to the assessment of brain arousal regulation is the classification of EEG vigilance stages, a computer-based algorithm (Vigilance Algorithm Leipzig) has been introduced, allowing classification of EEG vigilance stages in EEG recordings under resting conditions. The time course of EEG vigilance stages in EEGs of 15-20 min duration allows estimation of the individual arousal regulation (hyperstable, adaptive, or unstable vigilance pattern). The vigilance model of affective disorders and attention-deficit/hyperactivity disorder links a disturbed arousal regulation to the pathogenesis of psychiatric disorders and accordingly helps to explain and possibly also predict treatment effects of pharmacological and nonpharmacological interventions for these conditions. AbstractDuring the last few decades, much knowledge has been gained about sleep being a heterogeneous condition with several distinct sleep stages that represent fundamentally different physiological states. The same applies for the wake state which also comprises distinct global functional states (called vigilance stages). However, various terms and concepts have been introduced describing different aspects of wakefulness, and accordingly several methods of assessment exist, e.g. sleep laboratory assessments (Multiple Sleep Latency Test, Maintenance of Wakefulness Test), questionnaires (Epworth Sleepiness Scale, Karolinska Sleepiness Scale), behavioural tasks (Psychomotor Vigilance Test) or electroencephalography (EEG)-based assessments (Alpha Attenuation Test, Karolinska Drowsiness Test). Furthermore, several theoretical concepts about the regulation of sleep and wakefulness have been put forward, and physiological correlates have been identified. Most relevant for healthy functioning is the regulation of brain arousal and the adap-

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Section: Application Of Vigallmentioning

confidence: 71%

Assessment of Wakefulness and Brain Arousal Regulation in Psychiatric Research

Sander¹,

Hensch²,

Wittekind³

et al. 2015

Neuropsychobiology

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“…For assessment of the EEG‐vigilance regulation type, two different approaches were applied. At first, each individual EEG‐vigilance time series (consisting of 900 consecutive EEG‐vigilance stages as classified via VIGALL) was compared with three different types of EEG‐vigilance regulation derived from a k‐means cluster solution described elsewhere (Olbrich et al ., ,b). Artefact segments were treated with the last observation carried forward approach for the cluster analysis.…”

Section: Methodsmentioning

confidence: 99%

“…Based on a 15‐min multichannel electroencephalogram (EEG)‐activity recorded under resting conditions, VIGALL classifies each 1‐s EEG epoch into one of seven EEG‐vigilance stages (see below). The computer‐based algorithm takes into account the information of several EEG frequency bands and their spatial cortical distribution for each analysed segment (for a detailed description of the algorithm, see Hegerl et al ., ; Olbrich et al ., , ,b; and VIGALL Manual http://uni-leipzig.de/~vigall/). VIGALL has been validated in a couple of studies: the investigations of simultaneous EEG/functional magnetic resonance imaging showed a negative correlation between EEG‐vigilance levels and blood oxygen level‐dependent signals in vast cortical areas (Olbrich et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Objective markers for sleep propensity: comparison between the Multiple Sleep Latency Test and the Vigilance Algorithm Leipzig

Olbrich

Fischer

Sander

et al. 2015

Journal of Sleep Research

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SUMMARYThe regulation of wakefulness is important for high-order organisms. Its dysregulation is involved in the pathomechanism of several psychiatric disorders. Thus, a tool for its objective but little time-consuming assessment would be of importance. The Vigilance Algorithm Leipzig allows the objective measurement of sleep propensity, based on a single resting state electroencephalogram. To compare the Vigilance Algorithm Leipzig with the standard for objective assessment of excessive daytime sleepiness, a four-trial Multiple Sleep Latency Test in 25 healthy subjects was conducted. Between the first two trials, a 15-min, 25-channel resting electroencephalogram was recorded, and Vigilance Algorithm Leipzig was used to classify the sleep propensity (i.e. type of vigilance regulation) of each subject. The results of both methods showed significant correlations with the Epworth Sleepiness Scale (q = À0.70; q = 0.45, respectively) and correlated with each other (q = À0.54). Subjects with a stable electroencephalogram-vigilance regulation yielded significant increased sleep latencies compared with an unstable regulation (multiple sleep latency 898.5 s versus 549.9 s; P = 0.03). Further, Vigilance Algorithm Leipzig classifications allowed the identification of subjects with average sleep latencies <6 min with a sensitivity of 100% and a specificity of 77%. Thus, Vigilance Algorithm Leipzig provides similar information on wakefulness regulation in comparison to the much more cost-and time-consuming Multiple Sleep Latency Test. Due to its high sensitivity and specificity for large sleep propensity, Vigilance Algorithm Leipzig could be an effective and reliable alternative to the Multiple Sleep Latency Test, for example for screening purposes in large cohorts, where objective information about wakefulness regulation is needed. IN TROD UCTI ONThe regulation of wakefulness from high alertness to relaxed quiet waking to drowsiness until sleep onset is of fundamental importance for all high-order organisms. This regulation is both a stable individual trait (Tucker et al., 2007;Van Dongen et al., 2005) and dependent on a variety of state factors, such as sleep deficits, recreational drugs and psychopharmacological treatment. Among the medical disorders affecting the wakefulness regulation are sleep disorders, such as narcolepsy (Guilleminault and Brooks, 2001), but also affective disorders and attention deficit hyperactivity disorder (Hegerl and Hensch, 2014).The Vigilance Algorithm Leipzig (VIGALL) has been developed to get an objective parameter of this regulation of wakefulness.

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“…social withdrawal, sensation avoidance). Findings of hyperstable brain arousal regulation are not exclusive to MDD, having been recently demonstrated in obsessive-compulsive disorder [47]. This pathophysiological overlap between the disorders may contribute to high reciprocal comorbidity rates [48].…”

Section: Discussionmentioning

confidence: 99%

Impact of Serum Cytokine Levels on EEG-Measured Arousal Regulation in Patients with Major Depressive Disorder and Healthy Controls

et al. 2016

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Background: In major depressive disorder (MDD), findings include hyperstable regulation of brain arousal measured by electroencephalography (EEG) vigilance analysis and alterations in serum levels of cytokines. It is also known that cytokines affect sleep-wake regulation. This study investigated the relationship between cytokines and EEG vigilance in participants with MDD and nondepressed controls, and the influence of cytokines on differences in vigilance between the two groups. Methods: In 60 patients with MDD and 129 controls, 15-min resting-state EEG recordings were performed and vigilance was automatically assessed with the VIGALL 2.0 (Vigilance Algorithm Leipzig). Serum levels of the wakefulness-promoting cytokines interleukin (IL)-4, IL-10, IL-13 and somnogenic cytokines tumor necrosis factor-α, interferon-γ and IL-2 were measured prior to the EEG. Results: Summed wakefulness-promoting cytokines, but not somnogenic cytokines, were significantly associated with the time course of EEG vigilance in the MDD group only. In both groups, IL-13 was significantly associated with the course of EEG vigilance. In MDD compared to controls, a hyperstable EEG vigilance regulation was found, significant for group and group × time course interaction. After controlling for wakefulness-promoting cytokines, differences in vigilance regulation between groups remained significant. Conclusions: The present study demonstrated a relationship between wakefulness-promoting cytokines and objectively measured EEG vigilance as an indicator for brain arousal. Altered brain arousal regulation in MDD gives support for future evaluation of vigilance measures as a biomarker in MDD. Since interactions between cytokines and EEG vigilance only moderately differed between the groups and cytokine levels could not explain the group differences in EEG vigilance regulation, cytokines and brain arousal regulation are likely to be associated with MDD in independent ways.

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EEG-vigilance regulation during the resting state in obsessive–compulsive disorder

Cited by 18 publications

References 28 publications

Assessment of Wakefulness and Brain Arousal Regulation in Psychiatric Research

Assessment of Wakefulness and Brain Arousal Regulation in Psychiatric Research

Objective markers for sleep propensity: comparison between the Multiple Sleep Latency Test and the Vigilance Algorithm Leipzig

Impact of Serum Cytokine Levels on EEG-Measured Arousal Regulation in Patients with Major Depressive Disorder and Healthy Controls

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