Canonical EEG microstates transitions reflect switching among BOLD resting state networks and predict fMRI signal

Abnormal nonlinear features of EEG microstate sequence in obsessive-compulsive disorder

BACKGROUND

At present, only a few studies have explored electroencephalography (EEG) microstates of patients with obsessive-compulsive disorder (OCD) and the results are inconsistent. Additionally, the nonlinear features of EEG microstate sequences contain rich information about the brain, yet how the nonlinear features of EEG microstate sequences abnormally change in patients with OCD is still unknown.

METHODS

Resting-state EEG data were collected from 48 OCD patients and macheted 48 healthy controls (HC). Subsequently, EEG microstate analysis was used to extract the microstate temporal parameters (duration, occurrence, coverage) and nonlinear features of EEG microstate sequences (sample entropy, Lempel-Ziv complexity, Hurst index). Finally, the temporal parameters and nonlinear features of EEG microstate sequences were sent to three kinds of machine learning models to classify OCD patients.

RESULTS

Both groups obtained four typical EEG microstate topographies. The duration of microstates A, B, and C in OCD patients decreased significantly, while the occurrence of microstate D increased significantly compared to HC. Sample entropy and Lempel-Ziv complexity of microstate sequences in OCD patients increased significantly, while Hurst index decreased significantly compared to HC. The classification accuracy using the nonlinear features of microstate sequences reached up to 85%, significantly higher than that based on microstate temporal parameter models.

CONCLUSION

This study provides supplementary findings on EEG microstates in OCD patients with a larger sample size. We found that the nonlinear features of EEG microstate sequences in OCD patients can serve as potential electrophysiological biomarkers for distinguishing OCD patients.

Abnormal EEG microstates in Alzheimer's disease: predictors of β-amyloid deposition degree and disease classification

Electroencephalography (EEG) microstates are used to study cognitive processes and brain disease-related changes. However, dysfunctional patterns of microstate dynamics in Alzheimer's disease (AD) remain uncertain. To investigate microstate changes in AD using EEG and assess their association with cognitive function and pathological changes in cerebrospinal fluid (CSF). We enrolled 56 patients with AD and 38 age- and sex-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Patients with AD also underwent CSF examinations to assess biomarkers related to the disease. Stepwise regression was used to analyze the relationship between changes in microstate patterns and CSF biomarkers. Receiver operating characteristics analysis was used to assess the potential of these microstate patterns as diagnostic predictors for AD. Compared with HC, patients with AD exhibited longer durations of microstates C and D, along with a decreased occurrence of microstate B. These microstate pattern changes were associated with Stroop Color Word Test and Activities of Daily Living scale scores (all P < 0.05). Mean duration, occurrences of microstate B, and mean occurrence were correlated with CSF Aβ 1-42 levels, while duration of microstate C was correlated with CSF Aβ 1-40 levels in AD (all P < 0.05). EEG microstates are used to predict AD classification with moderate accuracy. Changes in EEG microstate patterns in patients with AD correlate with cognition and disease severity, relate to Aβ deposition, and may be useful predictors for disease classification.

A Study on the Effects of Repetitive Transcranial Magnetic Stimulation on EEG Microstate in Patients With Parkinson's Disease

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technology that can modulate cerebral cortical excitability. Electroencephalography (EEG) microstate analysis is an important tool for studying dynamic changes in brain functional activity. This study explores the pathophysiological changes in Parkinson's disease (PD) patients by analyzing the EEG microstate of PD patients, and analyzes the impact of rTMS on the clinical symptoms of PD patients. In a trial, 25 patients with PD and 18 healthy subjects of the same age were included. The clinical scale (the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and Montreal Cognitive Assessment (MoCA)) scores of each patient were evaluated and the microstate characteristic parameters of all subjects were calculated. 10 Hz rTMS was used to stimulate the bilateral primary motor cortex (M1) of PD patients. After two weeks of treatment (10 times), the clinical scale score of each patient was re-evaluated and the microstate characteristic parameters were calculated. At the baseline, the occurrence, duration and coverage of microstate C in PD patients were significantly higher than those in healthy controls (P <0.05),and were significantly negatively correlated with the MoCA score (P <0.05). The duration and coverage of microstate D in PD patients were significantly lower than those in healthy controls (P <0.05), and were significantly negatively correlated with UPDRS-III score (P <0.05). After rTMS treatment in the PD group, the scale score of UPDRS-III was significantly reduced (P <0.05) and the scale score of MoCA was significantly increased. Moreover, the occurrence and coverage of microstate B were significantly increased (p <0.05). The occurrence, duration and coverage of microstate C were significantly reduced (P <0.05). The occurrence, duration and coverage of microstate D were significantly increased (P <0.05). This study shows that abnormal brain functional activity of PD patients can change microstate characteristic parameters, and these changes are significantly related to the decline of motor and cognitive functions. Furthermore, rTMS can improve the motor and cognitive functions and adjust the microstate characteristic parameters of PD patients. EEG microstate analysis can reflect the therapeutic effect of rTMS on PD patients.

Causal link between prefrontal cortex and EEG microstates: evidence from patients with prefrontal lesion

Introduction

At present, elucidating the cortical origin of EEG microstates is a research hotspot in the field of EEG. Previous studies have suggested that the prefrontal cortex is closely related to EEG microstate C and D, but whether there is a causal link between the prefrontal cortex and microstate C or D remains unclear.

Methods

In this study, pretrial EEG data were collected from ten patients with prefrontal lesions (mainly located in inferior and middle frontal gyrus) and fourteen matched healthy controls, and EEG microstate analysis was applied.

Results

Our results showed that four classical EEG microstate topographies were obtained in both groups, but microstate C topography in patient group was obviously abnormal. Compared to healthy controls, the average coverage and occurrence of microstate C significantly reduced. In addition, the transition probability from microstate A to C and from microstate B to C in patient group was significantly lower than those of healthy controls.

Discussion

The above results demonstrated that the damage of prefrontal cortex especially inferior and middle frontal gyrus could lead to abnormalities in the spatial distribution and temporal dynamics of microstate C not D, showing that there is a causal link between the inferior and middle frontal gyrus and the microstate C. The significance of our findings lies in providing new evidence for elucidating the cortical origin of microstate C.