Microstate analysis of resting-state electroencephalography in patients with epilepsy with comorbid anxiety and depression

Abstract Purpose To explore the characteristics of microstates in patients with epilepsy with comorbid anxiety and depression based on resting-state electroencephalography (EEG). Methods We recruited patients with epilepsy who were monitored using video EEG between November 2021 and December 2022 at the affiliated hospital of Zunyi Medical University. Thirty patients with epilepsy with comorbid anxiety and depression (PAD) and 32 patients with epilepsy without anxiety and depression (nPAD) were recruited for this study. Resting-state EEG was conducted for 5 min (in eyes-closed, relaxed, and awake states). EEGLAB and MATLAB were used to process EEG data. Four typical microstate types were observed, including A (auditory), B (visual), C (insular-cingulate), and D (attention). The duration, occurrence, coverage, and transition probabilities of microstates A, B, C, and D of the patients in the two groups were compared, and their correlations with anxiety and depression were analyzed. Results Compared to the nPAD group, patients in the PAD group had a shorter disease course and a higher frequency of seizures. Second, the occurrence of microstate C was decreased in patients in the PAD group. Third, the level of anxiety in patients with epilepsy was negatively correlated with the occurrence of microstate C and the transition probabilities from C to A and C to B. However, it was positively correlated with the transition probability from microstate D to A. The level of depression was negatively correlated with the occurrence of microstate C and the transition probabilities from C to A and C to B. Conclusion The more frequently patients had seizures (> 2 times per year), the more likely they were to have comorbid anxiety and depression. Moreover, the network connections between the insula and cingulate regions were weakened in patients with epilepsy with comorbid anxiety and depression..

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

ResearchSquare.com - (2024) vom: 04. Apr. Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Yan, Rong [VerfasserIn]
Zhang, Lijia [VerfasserIn]
Li, Fangjing [VerfasserIn]
Liu, Wanyu [VerfasserIn]
Tai, Zhenzhen [VerfasserIn]
Yang, Juan [VerfasserIn]
Tuo, Jinmei [VerfasserIn]
Yu, Changyin [VerfasserIn]
Zhang, Haiqing [VerfasserIn]
Xu, zucai [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.21203/rs.3.rs-3777110/v1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XRA042051533