Resting-state EEG microstates in affective disorders

DAMBORSKÁ, Alena; Thi Vy DUONG; Michal HORÁČEK; Jana HOŘÍNKOVÁ; Pavel KŘENEK a Eliška BARTEČKOVÁ. Resting-state EEG microstates in affective disorders. In World Congress of Biological Psychiatry, Berlín. 2025.

Základní údaje

Originální název

Resting-state EEG microstates in affective disorders

Autoři

DAMBORSKÁ, Alena ORCID; Thi Vy DUONG; Michal HORÁČEK; Jana HOŘÍNKOVÁ; Pavel KŘENEK a Eliška BARTEČKOVÁ

Vydání

World Congress of Biological Psychiatry, Berlín, 2025

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Další údaje

Typ výsledku

Konferenční abstrakt

Odkazy

URL

Označené pro přenos do RIV

Ne

UT WoS

https://wfsbp.org/congress/

Příznaky

Mezinárodní význam, Recenzováno

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Anotace

V originále

Introduction: Affective disorders are common and very serious psychiatric disorders. Results of recent neuroimaging studies provide evidence of impaired activity of resting-state brain networks in depression. Brain network activity can be studied by analyzing functional brain EEG microstates. EEG microstate is a global state of brain activity lasting about 100 ms, characterized by a stable topography of the potential distribution on the scalp. The aim of this study is to investigate whether antidepressant pharmacotherapy has an effect on the change of resting-state brain network activity in patients with depression. Method: Eight healthy controls and eight patients diagnosed with at least moderate depression participated in the study. Depression severity was determined using the Montgomery-Åsberg Depression Rating Scale (MADRS) questionnaire. A five-minute recording of resting brain activity captured by a 128-channel EEG system was analyzed. Patients' data were captured before stabilization of antidepressant pharmacotherapy (T1), 6 weeks after the first measurement (T2), and 6 months after the first measurement (T3). Healthy controls were measured once. Segmentation and cluster analysis of topographies was performed across all subjects and measurements. Temporal parameters of EEG microstates were evaluated usig Cartool software. Results: Pharmacotherapy led to at least temporary clinical improvement in all patients. Five microstates (A-E) were identified, differing in potential distribution on the scalp. Mean duration of microstates in healthy controls: A - 98 ± 10 ms; B - 95 ± 8 ms; C - 108 ± 12 ms; D - 93 ± 9 ms, E - 100 ± 12 ms. Average duration of microstates in patients at three time points (T1, T2, T3): A - 100 ± 11 ms, 110 ± 13 ms, 105 ± 21 ms; B - 100 ± 12 ms, 103 ± 11 ms, 103 ± 14 ms; C - 143 ± 39 ms, 144 ± 45 ms, 134 ± 41 ms; D - 99 ± 20 ms, 116 ± 38 ms, 114 ± 47 ms; E - 90 ± 8 ms, 96 ± 10 ms, 98 ± 19 ms. Temporal coverage of microstates in healthy controls: A - 20 ± 5%; B - 18 ± 6%; C - 25 ± 6%; D - 16 ± 6%; E - 21 ± 7%. Temporal coverage of microstates in patients at three time points (T1, T2, T3): A - 17 ± 5%, 18 ± 8%, 17 ± 9%; B - 16 ± 7%, 14 ± 6%, 15 ± 5%; C - 40 ± 13%, 34 ± 13%, 32 ± 12%; D - 18 ± 19%, 22 ± 20%, 21 ± 20%; E - 9 ± 5%, 12 ± 8%, 15 ± 12%. Conclusion: We identified five functional brain microstates (A-E), all of which resembled microstates previously described in the literature. For micro-state C, we observed a higher presence (longer duration and greater temporal coverage) in depressed patients than in healthy controls. Normalization of these parameters in following measurements was observed. Statistical processing in more subjects and study of these changes in relation to clinical course and intensity of pharmacotherapy will be needed for more general conclusions. Microstate analysis appears to be a promising tool to assess the effect of pharmacotherapy on the dynamics of resting large-scale brain networks in patients with depression. This work was supported by Ministry of Health, Czech Republic—conceptual development of research organization (Grant No. FNBr 65269705).