EEG microstate in first-episode drug-naive adolescents with depression

Abstract

Background: A growing number of studies have revealed significant abnormalities in EEG microstate in patients with depression, but these findings may be affected by medication. Therefore, how the EEG microstates abnormally change in patients with depression in the early stage and without the influence of medication has not been investigated so far. Methods: Resting-state EEG data and Hamilton Depression Rating Scale (HDRS) were collected from 34 first-episode drug-naïve adolescent with depression and 34 matched healthy controls. EEG microstate analysis was applied and nonlinear characteristics of EEG microstate sequences were studied by sample entropy and Lempel-Ziv complexity (LZC). The microstate temporal parameters and complexity were tried to train a SVM for classification of patients with depression. Results: Four typical EEG microstate topographies were obtained in both groups, but microstate C topography was significantly abnormal in depression patients. The duration of microstate B, C, D and the occurrence and coverage of microstate B significantly increased, the occurrence and coverage of microstate A, C reduced significantly in depression group. Sample entropy and LZC in the depression group were abnormally increased and were negatively correlated with HDRS. When the combination of EEG microstate temporal parameters and complexity of microstate sequence was used to classify patients with depression from healthy controls, a classification accuracy of 90.9% was obtained. Conclusion: Abnormal EEG microstate has appeared in early depression, reflecting an underlying abnormality in configuring neural resources and transitions between distinct brain network states. EEG microstate can be used as a neurophysiological biomarker for early auxiliary diagnosis of depression.

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

“…Different views exist regarding the characteristics of the changes in microstate A. For instance, according to Zhao et al, patients with depression exhibit a decrease in the occurrence and coverage of microstate A in their EEG characteristics [39]. In the current research, there was a negative correlation found between microstate C-to-A transition and the anxiety and depression levels in patients.…”

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer’s Disease continuum?

“…LZ complexity is known to be a robust marker of brain dysfunction, both when computed at the signal level (e.g. in depression ( Bachmann et al, 2015 ), schizophrenia ( Ibáñez-Molina et al, 2018 ) and epilepsy ( Abásolo et al, 2007 , Bai et al, 2015 )) and at microstates level (for example ( Artoni et al, 2022 , Tait et al, 2020 , Zhao et al, 2022 )).…”

Beyond Frequency Bands: Complementary-Ensemble-Empirical-Mode-Decomposition-Enhanced Microstate Sequence Non-Randomness Analysis for Aiding Diagnosis and Cognitive Prediction of Dementia

“…Furthermore, the biological significance of LZC may differ from that indicated by other microstate indicators [34]. For instance, in other studies, MSLZC was found to be higher in patients with depression than in controls [35], and LZC in patients with thalamic ischemic stroke has been found to be higher compared to the controls [36].…”