Dataset Information

Changes in brain arousal (EEG-vigilance) after therapeutic sleep deprivation in depressive patients and healthy controls.

ABSTRACT: Depressed patients frequently exhibit a hyperstable brain arousal regulation. According to the arousal regulation model of affective disorders, the antidepressant effect of therapeutic sleep deprivation could be achieved by counter-acting this dysregulation. We investigated the impact of partial sleep deprivation (PSD) on EEG-vigilance (an indicator of brain arousal regulation) in depressed patients (n?=?27) and healthy controls (n?=?16). PSD was hypothesized to cause a more prominent destabilisation of brain arousal regulation in depressed patients (reflected by increased occurrence of lower EEG-vigilance stages). Furthermore, it was studied whether responders (n?=?17) exhibit a more stable baseline brain arousal regulation and would show a more prominent arousal destabilisation after PSD than non-responders (n?=?10). Before PSD, patients showed a more stable EEG-vigilance with less declines to lower vigilance stages compared to controls. Contrary to the hypothesis, a greater destabilisation of brain arousal after PSD was seen in controls. Within the patient sample, responders generally showed a less stable EEG-vigilance, especially after PSD when we found significant differences compared to non-responders. EEG-vigilance in non-responders showed only little change from baseline to after PSD. In summary, PSD had a destabilizing impact on brain arousal regulation in healthy controls whereas depressed patients reacted heterogeneously depending on the outcome of treatment.

SUBMITTER: Sander C

PROVIDER: S-EPMC6180108 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Changes in brain arousal (EEG-vigilance) after therapeutic sleep deprivation in depressive patients and healthy controls.

Sander Christian C Schmidt Jonathan M JM Mergl Roland R Schmidt Frank M FM Hegerl Ulrich U

Scientific reports 20181010 1

Depressed patients frequently exhibit a hyperstable brain arousal regulation. According to the arousal regulation model of affective disorders, the antidepressant effect of therapeutic sleep deprivation could be achieved by counter-acting this dysregulation. We investigated the impact of partial sleep deprivation (PSD) on EEG-vigilance (an indicator of brain arousal regulation) in depressed patients (n = 27) and healthy controls (n = 16). PSD was hypothesized to cause a more prominent destabilis ...[more]

PMID: 30305649

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Project description:To identify measures derived from baseline psychomotor vigilance task (PVT) performance that can reliably predict vulnerability to sleep deprivation.Subjects underwent total sleep deprivation and completed a 10-min PVT every 1-2 h in a controlled laboratory setting. Participants were categorized as vulnerable or resistant to sleep deprivation, based on a median split of lapses that occurred following sleep deprivation. Standard reaction time, drift diffusion model (DDM), and wavelet metrics were derived from PVT response times collected at baseline. A support vector machine model that incorporated maximum relevance and minimum redundancy feature selection and wrapper-based heuristics was used to classify subjects as vulnerable or resistant using rested data.Two academic sleep laboratories.Independent samples of 135 (69 women, age 18 to 25 y), and 45 (3 women, age 22 to 32 y) healthy adults.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.Despite differences in experimental conditions across studies, drift diffusion model parameters associated reliably with individual differences in performance during total sleep deprivation. These results demonstrate the utility of drift diffusion modeling of baseline performance in estimating vulnerability to psychomotor vigilance decline following sleep deprivation.

Dataset Information

Changes in brain arousal (EEG-vigilance) after therapeutic sleep deprivation in depressive patients and healthy controls.

Publications

Changes in brain arousal (EEG-vigilance) after therapeutic sleep deprivation in depressive patients and healthy controls.

Similar Datasets

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