EEG Resting-State Large-Scale Brain Network Dynamics Are Related to Depressive Symptoms
Bibliographic Data
| ID | 15518920 |
|---|---|
| Authors | Alena Damborská (0000-0002-9714-7441, University of Geneva, corresponding author), Miralena I Tomescu (0000-0002-8845-0836, University of Geneva), Eliška Honzírková (University Hospital Brno), Richard Barteček (University Hospital Brno), Jana Hořínková (Masaryk University), Sylvie Fedorová (0000-0003-2957-3403, Masaryk University), Šimon Ondruš (University Hospital Brno), Christoph M Michel (0000-0003-3426-5739, Centre d'Imagerie BioMedicale) |
| Year | 2019 |
| Volume | 10 |
| Pages | 548-548 |
| Publication date | 2019-08-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2019.00548 |
| PMID | 31474881 |
| OpenAlex | W2956626736 |
| Language | EN |
| Citations received | 7 |
| References cited | 53 |
Background: The few previous studies on resting-state electroencephalography (EEG) microstates in depressive patients suggest altered temporal characteristics of microstates compared to those of healthy subjects. We tested whether resting-state microstate temporal characteristics could capture large-scale brain network dynamic activity relevant to depressive symptomatology. Methods: To evaluate a possible relationship between the resting-state large-scale brain network dynamics and depressive symptoms, we performed EEG microstate analysis in 19 patients with moderate to severe depression in bipolar affective disorder, depressive episode, and recurrent depressive disorder and in 19 healthy controls. Results: Microstate analysis revealed six classes of microstates (A-F) in global clustering across all subjects. There were no between-group differences in the temporal characteristics of microstates. In the patient group, higher depressive symptomatology on the Montgomery-Åsberg Depression Rating Scale correlated with higher occurrence of microstate A (Spearman's rank correlation, r = 0.70, p Conclusion: Our results suggest that the observed interindividual differences in resting-state EEG microstate parameters could reflect altered large-scale brain network dynamics relevant to depressive symptomatology during depressive episodes. Replication in larger cohort is needed to assess the utility of the microstate analysis approach in an objective depression assessment at the individual level
Audiology · Brain activity and meditation · Cognition · Depression (economics · Electroencephalography · Major depressive disorder · Ministate · Psychiatry · Resting state fMRI · Clinical Psychology · EEG and Brain-Computer Interfaces · Functional Brain Connectivity Studies · Medicine · Neural dynamics and brain function · Neuroscience · Psychology
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| Unique citing works | 7 |
|---|---|
| Citations per year | 1 |
| Citation span | 2019 - 2025 (7) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |