EEG Microstates and Its Relationship With Clinical Symptoms in Patients With Schizophrenia

Analysis of microstate features for Parkinson's disease based on reliability validation

BACKGROUND

Parkinson's disease (PD) is a disorder with abnormal changes in brain activity. The lack of objective indicators makes the assessment of PD progression difficult. Assessment of brain activity changes in PD may offer a potential solution.

NEW METHOD

Electroencephalogram (EEG) microstates reflect global dynamic changes in the brain. Therefore, we utilized microstates to assess changes in PD brain activity. However, the effect of epoch duration on the reliability of microstate analyses in PD is unclear. Thus, we first assessed the effect of data duration on the reliability of microstate topography and temporal features in PD and older healthy individuals. According to the reliability assessment, EEG epochs with high reliability were selected for microstate analysis in PD. Finally, we investigated the correlation between microstate features and clinical scales to determine whether these features could serve as objective indicators to evaluate PD progression.

RESULTS

Microstate analysis features that show high reliability for 3 min and above epoch durations. The topology of microstate D was significantly changed in PD compared to healthy controls, as well as the temporal features of microstates C and D. Additionally, the occurrence of C was negatively correlated with MoCA, and the duration of D was positively correlated with UPDRS.

COMPARISON WITH EXISTING METHOD(S)

High reliability of PD microstate features obtained by our approach.

CONCLUSION

EEG for PD microstate analysis should be at least 3 min. Microstate analysis is expected to provide new ideas and objective indicators for assessing Parkinson's disease progression in the clinical setting.

Shared and distinct electroencephalogram microstate abnormalities across schizophrenia, bipolar disorder, and depression

BACKGROUND

Microstates of an electroencephalogram (EEG) are canonical voltage topographies that remain quasi-stable for 90 ms, serving as the foundational elements of brain dynamics. Different changes in EEG microstates can be observed in psychiatric disorders like schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). However, the similarities and disparatenesses in whole-brain dynamics on a subsecond timescale among individuals diagnosed with SCZ, BD, and MDD are unclear.

METHODS

This study included 1112 participants (380 individuals diagnosed with SCZ, 330 with BD, 212 with MDD, and 190 demographically matched healthy controls [HCs]). We assembled resting-state EEG data and completed a microstate analysis of all participants using a cross-sectional design.

RESULTS

Our research indicates that SCZ, BD, and MDD exhibit distinct patterns of transition among the four EEG microstate states (A, B, C, and D). The analysis of transition probabilities showed a higher frequency of switching from microstates A to B and from B to A in each patient group compared to the HC group, and less frequent transitions from microstates A to C and from C to A in the SCZ and MDD groups compared to the HC group. And the probability of the microstate switching from C to D and D to C in the SCZ group significantly increased compared to those in the patient and HC groups.

CONCLUSIONS

Our findings provide crucial insights into the abnormalities involved in distributing neural assets and enabling proper transitions between different microstates in patients with major psychiatric disorders.

Dynamics of Cerebral Function in Patients with Acute Cerebellar Infarction

Few studies were devoted to investigating cerebral functional changes after acute cerebellar infarction (CI). The purpose of this study was to examine the brain functional dynamics of CI using electroencephalographic (EEG) microstate analysis. And the possible heterogenicity in neural dynamics between CI with vertigo and CI with dizziness was explored. Thirty-four CI patients and 37 age- and gender-matched healthy controls(HC) were included in the study. Each included subject underwent a 19-channel video EEG examination. Five 10-s resting-state EEG epochs were extracted after data preprocessing. Then, microstate analysis and source localization were performed using the LORETA-KEY tool. Microstate parameters such as duration, coverage, occurrence, and transition probability are all extracted. The current study showed that the duration, coverage, and occurrence of microstate(Ms) B significantly increased in CI patients, but the duration and coverage of MsA and MsD decreased. Compared CI with vertigo to dizziness, finding a decreased trend in the coverage of MsD and the transition from MsA and MsB to MsD. Taken together, our study sheds new light on the dynamics of cerebral function after CI, mainly reflecting increased activity in functional networks involved in MsB and decreased activity in functional networks involved in MsA and MsD. Vertigo and dizziness post-CI may be suggested by cerebral functional dynamics. Further longitudinal studies are needed to validate and explore the alterations in brain dynamics to what extent depict the clinical traits and their potential applications in the recovery of CI.

Normative Temporal Dynamics of Resting EEG Microstates

The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.

Abnormalities of electroencephalography microstates in patients with depression and their association with cognitive function

BACKGROUND

A growing number of recent studies have explored underlying activity in the brain by measuring electroencephalography (EEG) in people with depression. However, the consistency of findings on EEG microstates in patients with depression is poor, and few studies have reported the relationship between EEG microstates, cognitive scales, and depression severity scales.

AIM

To investigate the EEG microstate characteristics of patients with depression and their association with cognitive functions.

METHODS

A total of 24 patients diagnosed with depression and 32 healthy controls were included in this study using the Structured Clinical Interview for Disease for The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. We collected information relating to demographic and clinical characteristics, as well as data from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS; Chinese version) and EEG.

RESULTS

Compared with the controls, the duration, occurrence, and contribution of microstate C were significantly higher [depression (DEP): Duration 84.58 ± 24.35, occurrence 3.72 ± 0.56, contribution 30.39 ± 8.59; CON: Duration 72.77 ± 10.23, occurrence 3.41 ± 0.36, contribution 24.46 ± 4.66; Duration F = 6.02, P = 0.049; Occurrence F = 6.19, P = 0.049; Contribution F = 10.82, P = 0.011] while the duration, occurrence, and contribution of microstate D were significantly lower (DEP: Duration 70.00 ± 15.92, occurrence 3.18 ± 0.71, contribution 22.48 ± 8.12; CON: Duration 85.46 ± 10.23, occurrence 3.54 ± 0.41, contribution 28.25 ± 5.85; Duration F = 19.18, P < 0.001; Occurrence F = 5.79, P = 0.050; Contribution F = 9.41, P = 0.013) in patients with depression. A positive correlation was observed between the visuospatial/constructional scores of the RBANS scale and the transition probability of microstate class C to B (r = 0.405, P = 0.049).

CONCLUSION

EEG microstate, especially C and D, is a possible biomarker in depression. Patients with depression had a more frequent transition from microstate C to B, which may relate to more negative rumination and visual processing.

EEG microstate quantifiers and state space descriptors during anaesthesia in patients with postoperative delirium: a descriptive analysis

Postoperative delirium is a serious sequela of surgery and surgery-related anaesthesia. One recommended method to prevent postoperative delirium is using bi-frontal EEG recording. The single, processed index of depth of anaesthesia allows the anaesthetist to avoid episodes of suppression EEG and excessively deep anaesthesia. The study data presented here were based on multichannel (19 channels) EEG recordings during anaesthesia. This enabled the analysis of various parameters of global electrical brain activity. These parameters were used to compare microstate topographies under anaesthesia with those in healthy volunteers and to analyse changes in microstate quantifiers and EEG global state space descriptors with increasing exposure to anaesthesia. Seventy-three patients from the Surgery Depth of Anaesthesia and Cognitive Outcome study (SRCTN 36437985) received intraoperative multichannel EEG recordings. Altogether, 720 min of artefact-free EEG data, including 210 min (29.2%) of suppression EEG, were analysed. EEG microstate topographies, microstate quantifiers (duration, frequency of occurrence and global field power) and the state space descriptors sigma (overall EEG power), phi (generalized frequency) and omega (number of uncorrelated brain processes) were evaluated as a function of duration of exposure to anaesthesia, suppression EEG and subsequent development of postoperative delirium. The major analyses involved covariate-adjusted linear mixed-effects models. The older (71 ± 7 years), predominantly male (60%) patients received a median exposure of 210 (range: 75-675) min of anaesthesia. During seven postoperative days, 21 patients (29%) developed postoperative delirium. Microstate topographies under anaesthesia resembled topographies from healthy and much younger awake persons. With increasing duration of exposure to anaesthesia, single microstate quantifiers progressed differently in suppression or non-suppression EEG and in patients with or without subsequent postoperative delirium. The most pronounced changes occurred during enduring suppression EEG in patients with subsequent postoperative delirium: duration and frequency of occurrence of microstates C and D progressed in opposite directions, and the state space descriptors showed a pattern of declining uncorrelated brain processes (omega) combined with increasing EEG variance (sigma). With increasing exposure to general anaesthesia, multiple changes in the dynamics of microstates and global EEG parameters occurred. These changes varied partly between suppression and non-suppression EEG and between patients with or without subsequent postoperative delirium. Ongoing suppression EEG in patients with subsequent postoperative delirium was associated with reduced network complexity in combination with increased overall EEG power. Additionally, marked changes in quantifiers in microstate C and in microstate D occurred. These putatively adverse intraoperative trajectories in global electrical brain activity may be seen as preceding and ultimately predicting postoperative delirium.

Abnormalities in electroencephalographic microstates among violent patients with schizophrenia

Schizophrenia is often associated with a remarkably increased risk of violence, which has become a public health concern and brought a great economic burden. Recent studies have reported changes in the electroencephalograms (EEG) of patients with schizophrenia. The evidence for an association between EEG and violence in patients with schizophrenia is not conclusive. This study aimed to investigate EEG microstates in violent patients with schizophrenia. Forty-three violent patients with schizophrenia (the VS group) and 51 non-violent patients with schizophrenia (the NVS group) were included, and their EEG microstates were recorded using 21-Channel EEG recordings. The two groups were compared for differences of four microstate classes (A-D) with regards to three microstate parameters (duration, occurrence, and coverage). Compared with the NVS group, the VS group exhibited increased duration, occurrence, and coverage of microstate class A and decreased occurrence of microstate class B. The VS group also had lower probabilities of transitions from "B to C" and from "C to B", as compared with the NVS group. In addition, the MOAS score was positively correlated with the duration, occurrence, and coverage of microstate A. The present study found an abnormal pattern of EEG microstates in violent patients with schizophrenia, which might help clinicians identify patients with schizophrenia who might engaged in violence as well as develop intervention strategies at an early stage.

Spatiotemporal patterns of spontaneous brain activity: a mini-review

The brain exists in a state of constant activity in the absence of any external sensory input. The spatiotemporal patterns of this spontaneous brain activity have been studied using various recording and imaging techniques. This has enabled considerable progress to be made in elucidating the cellular and network mechanisms that are involved in the observed spatiotemporal dynamics. This mini-review outlines different spatiotemporal dynamic patterns that have been identified in four commonly used modalities: electrophysiological recordings, optical imaging, functional magnetic resonance imaging, and electroencephalography. Signal sources for each modality, possible sources of the observed dynamics, and future directions are also discussed.

Abnormalities of Electroencephalography Microstates in Drug-Naïve, First-Episode Schizophrenia

OBJECTIVE

Microstate analysis is a powerful tool to probe the brain functions, and changes in microstates under electroencephalography (EEG) have been repeatedly reported in patients with schizophrenia. This study aimed to investigate the dynamics of EEG microstates in drug-naïve, first-episode schizophrenia (FE-SCH) and to test the relationship between EEG microstates and clinical symptoms.

METHODS

Resting-state EEG were recorded for 23 patients with FE-SCH and 23 healthy controls using a 64-channel cap. Three parameters, i.e., contribution, duration, and occurrence, of the four microstate classes were calculated. Group differences in EEG microstates and their clinical symptoms [assessed using the Positive and Negative Syndrome Scale (PANSS)] were analyzed.

RESULTS

Compared with healthy controls, patients with FE-SCH showed increased duration, occurrence and contribution of microstate class C and decreased contribution and occurrence of microstate class D. In addition, the score of positive symptoms in PANSS was negatively correlated with the occurrence of microstate D.

CONCLUSION

Our findings showed abnormal patterns of EEG microstates in drug-naïve, first-episode schizophrenia, which might help distinguish individuals with schizophrenia in the early stage and develop early intervention strategies.