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.
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:Depressivepatients spent significantly more time in the highest EEG vigilance substage A1, and less time in substages A2, A3 and B2/3 than controls. In depressivepatients, 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.
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
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
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
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