Literature DB >> 21722018

Hyperstable regulation of vigilance in patients with major depressive disorder.

Ulrich Hegerl1, Kathrin Wilk, Sebastian Olbrich, Peter Schoenknecht, Christian Sander.   

Abstract

OBJECTIVES: This study tested the hypothesis that patients with depression show less and later declines into lower EEG vigilance stages (different global functional brain states) under resting conditions than healthy controls, as proposed by the vigilance theory of affective disorders.
METHODS: Thirty patients with Major Depressive Disorder (19 female; mean age: 37.2 years, SD: 12.6) without psychotropic medication and 30 carefully age- and sex-matched controls (19 female; mean age: 37.3 years, SD: 12.8) without past or present mental disorders underwent a 15-min resting EEG. EEG-vigilance regulation was determined with a computer-based vigilance classification algorithm (VIGALL, Vigilance Algorithm Leipzig), allowing a classification of vigilance stages A (with substages A1, A2 and A3), B (with substages B1 and B2/3) and C.
RESULTS: Depressive patients spent significantly more time in the highest EEG vigilance substage A1, and less time in substages A2, A3 and B2/3 than controls. In depressive patients, a significantly longer latency until the occurrence of substages A2, A3 and B2/3 was observed. No significant group differences in the percentage of B1 segments or the latency until occurrence of B1 were found.
CONCLUSIONS: The results confirm the hypothesis that patients with depression show less (and later) declines into lower EEG vigilance stages under resting conditions than healthy controls, and support the vigilance theory of affective disorders linking a hyperstable vigilance regulation to depression.

Entities:  

Mesh:

Year:  2011        PMID: 21722018     DOI: 10.3109/15622975.2011.579164

Source DB:  PubMed          Journal:  World J Biol Psychiatry        ISSN: 1562-2975            Impact factor:   4.132


  22 in total

1.  Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

Authors:  Craig E Tenke; Jürgen Kayser; Pia Pechtel; Christian A Webb; Daniel G Dillon; Franziska Goer; Laura Murray; Patricia Deldin; Benji T Kurian; Patrick J McGrath; Ramin Parsey; Madhukar Trivedi; Maurizio Fava; Myrna M Weissman; Melvin McInnis; Karen Abraham; Jorge E Alvarenga; Daniel M Alschuler; Crystal Cooper; Diego A Pizzagalli; Gerard E Bruder
Journal:  Psychophysiology       Date:  2017-01       Impact factor: 4.016

2.  A closer look at the relationship between the default network, mind wandering, negative mood, and depression.

Authors:  Shaghayegh Konjedi; Reza Maleeh
Journal:  Cogn Affect Behav Neurosci       Date:  2017-08       Impact factor: 3.282

3.  Diffusion imaging-based subdivision of the human hypothalamus: a magnetic resonance study with clinical implications.

Authors:  Peter Schönknecht; Alfred Anwander; Friederike Petzold; Stephanie Schindler; Thomas R Knösche; Harald E Möller; Ulrich Hegerl; Robert Turner; Stefan Geyer
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2013-01-04       Impact factor: 5.270

Review 4.  Current source density analysis of resting state EEG in depression: a review.

Authors:  Ping Chai Koo; Johannes Thome; Christoph Berger; Paul Foley; Jacqueline Hoeppner
Journal:  J Neural Transm (Vienna)       Date:  2015-08-02       Impact factor: 3.575

5.  Evoked potentials and behavioral performance during different states of brain arousal.

Authors:  Jue Huang; Tilman Hensch; Christine Ulke; Christian Sander; Janek Spada; Philippe Jawinski; Ulrich Hegerl
Journal:  BMC Neurosci       Date:  2017-01-25       Impact factor: 3.288

6.  Brain arousal regulation as response predictor for antidepressant therapy in major depression.

Authors:  Frank M Schmidt; Christian Sander; Marie-Elisa Dietz; Claudia Nowak; Thomas Schröder; Roland Mergl; Peter Schönknecht; Hubertus Himmerich; Ulrich Hegerl
Journal:  Sci Rep       Date:  2017-03-27       Impact factor: 4.379

7.  Coupling and dynamics of cortical and autonomic signals are linked to central inhibition during the wake-sleep transition.

Authors:  Christine Ulke; Jue Huang; Justus T C Schwabedal; Galina Surova; Roland Mergl; Tilman Hensch
Journal:  Sci Rep       Date:  2017-09-18       Impact factor: 4.379

8.  Genetic association of objective sleep phenotypes with a functional polymorphism in the neuropeptide S receptor gene.

Authors:  Janek Spada; Christian Sander; Ralph Burkhardt; Madlen Häntzsch; Roland Mergl; Markus Scholz; Ulrich Hegerl; Tilman Hensch
Journal:  PLoS One       Date:  2014-06-04       Impact factor: 3.240

Review 9.  The effect of chronotherapy on depressive symptoms. Evidence-based practice.

Authors:  Anas H Khalifeh
Journal:  Saudi Med J       Date:  2017-05       Impact factor: 1.484

10.  Impact of brain arousal and time-on-task on autonomic nervous system activity in the wake-sleep transition.

Authors:  Jue Huang; Christine Ulke; Christian Sander; Philippe Jawinski; Janek Spada; Ulrich Hegerl; Tilman Hensch
Journal:  BMC Neurosci       Date:  2018-04-11       Impact factor: 3.288

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.