Alpha rhythm of electroencephalography was modulated differently by three transcranial direct current stimulation protocols in patients with ischemic stroke.

The heterogeneity of transcranial direct current stimulation (tDCS) protocols and clinical profiles may explain variable results in modulating excitability in the motor cortex after stroke. However, the cortical electrical effects induced by different tDCS protocols remain unclear. Here, we aimed to compare rhythm changes in electroencephalography (EEG) induced by three tDCS position protocols and the association between tDCS effects and clinical factors in stroke. Nineteen patients with chronic ischemic stroke underwent four experimental sessions with three tDCS protocols [anodal (atDCS), cathodal (ctDCS), and bilateral (bi-tDCS)] and a sham protocol, according to a single-blind randomized crossover design. Resting-state EEG was acquired before and after each protocol. First, a paired-sample t-test was used to examine the difference in spectral power between pre- and post-stimulation. Then, linear and quadratic regression models were used separately to describe the association between the clinical factors of stroke and changes in spectral power which was significantly different between pre- and post-tDCS. Finally, repeated measures analysis of variance with lesion hemisphere, stimulation protocol, and the location was performed to investigate the effects of tDCS over time. The induced effect of tDCS was mainly reflected in the alpha rhythms. The alpha power was increased by atDCS, especially low-alpha (8-10 Hz), in localized areas of the central and distant areas of the frontal and parietal lobes. Bi-tDCS also affected alpha power but in a smaller area that mainly focused on high-alpha rhythms (10-13 Hz). However, ctDCS and sham had no significant effects on any EEG rhythm. The clinical factors of time since stroke and motor impairment level were related to the change in high-alpha induced by atDCS and bi-tDCS following quadratic regression models. The above-mentioned modulation effect lasted for 20 min without attenuation. In conclusion, our findings provide evidence that the alpha rhythm of EEG is modulated differently by different tDCS protocols and that high alpha is affected by clinical characteristics such as post-stroke time and motor deficits, which is of great significance for understanding the modulation effect of different tDCS protocols on stroke and the guidance of protocols to promote motor recovery following stroke.

Varied Response of EEG Rhythm to Different tDCS Protocols and Lesion Hemispheres in Stroke Subjects with Upper Limb Dysfunction.

Transcranial direct current stimulation (tDCS) provides a way to modulate the cortical activity and promote motor rehabilitation following stroke. However, evidence indicates that the response to tDCS is highly variable. This study was aimed at exploring rhythmic response of Electroencephalography (EEG) to three tDCS protocols in stroke subjects. We hypothesize that tDCS protocols may interact with stoke characteristics, and electrode placement may affect cortical activity which could be reflected by the EEG rhythm. 32 subjects with unilateral stroke were recruited to a single-blinded, randomized, and controlled crossover experiment. All of the subjects underwent four tDCS protocols (anodal (atDCS), cathodal (ctDCS), and bilateral tDCS (bi-tDCS) and sham) with an interval of at least 1 week. Resting-state EEG was acquired before and after the stimulation. We tested the change of EEG spectral power after tDCS and the difference of change among four protocols using the paired-sample t-test and repeated measures analysis of variance. Then, we investigated the clinical factors affecting the above changes using the linear and quadratic regression model. According to the results, EEG responded to atDCS and bi-tDCS protocols on alpha and beta rhythm and subjects with a left lesion had higher response than those with the right lesion. Besides that, the change of alpha and beta power after atDCS and of beta power after bi-tDCS showed association with clinical characteristics only in subjects with the left lesion. In conclusion, the study found varied EEG response with different protocols, lesion hemispheres, and other clinical characteristics supporting the individualized cortical oscillatory effect induced by tDCS.

Effect of Transcranial Direct Current Stimulation on the Mismatch Negativity Features of Deviated Stimuli in Children With Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a devastating mental disorder in children. Currently, there is no effective treatment for ASD. Transcranial direct current stimulation (tDCS), which is a non-invasive brain stimulation neuromodulation technology, is a promising method for the treatment of ASD. However, the manner in which tDCS changes the electrophysiological process in the brain is still unclear. In this study, we used tDCS to stimulate the dorsolateral prefrontal cortex area of children with ASD (one group received anode tDCS, and the other received sham tDCS) and investigated the changes in evoked EEG signals and behavioral abilities before and after anode and sham stimulations. In addition to tDCS, all patients received conventional rehabilitation treatment. Results show that although conventional treatment can effectively improve the behavioral ability of children with ASD, the use of anode tDCS with conventional rehabilitation can boost this improvement, thus leading to increased treatment efficacy. By analyzing the electroencephalography pre- and post-treatment, we noticed a decrease in the mismatch negativity (MMN) latency and an increase in the MMN amplitude in both groups, these features are considered similar to MMN features from healthy children. However, no statistical difference between the two groups was observed after 4 weeks of treatment. In addition, the MMN features correlate well with the aberrant behavior checklist (ABC) scale, particularly the amplitude of MMN, thus suggesting the feasibility of using MMN features to assess the behavioral ability of children with ASD.

Mutual Information-Based Brain Network Analysis in Post-stroke Patients With Different Levels of Depression.

Post-stroke depression (PSD) is the most common stroke-related emotional disorder, and it severely affects the recovery process. However, more than half cases are not correctly diagnosed. This study was designed to develop a new method to assess PSD using EEG signal to analyze the specificity of PSD patients' brain network. We have 107 subjects attended in this study (72 stabilized stroke survivors and 35 non-depressed healthy subjects). A Hamilton Depression Rating Scale (HDRS) score was determined for all subjects before EEG data collection. According to HDRS score, the 72 patients were divided into 3 groups: post-stroke non-depression (PSND), post-stroke mild depression (PSMD) and post-stroke depression (PSD). Mutual information (MI)-based graph theory was used to analyze brain network connectivity. Statistical analysis of brain network characteristics was made with a threshold of 10-30% of the strongest MIs. The results showed significant weakened interhemispheric connections and lower clustering coefficient in post-stroke depressed patients compared to those in healthy controls. Stroke patients showed a decreasing trend in the connection between the parietal-occipital and the frontal area as the severity of the depression increased. PSD subjects showed abnormal brain network connectivity and network features based on EEG, suggesting that MI-based brain network may have the potential to assess the severity of depression post stroke.

Electrophysiological changes in poststroke subjects with depressed mood: A quantitative EEG study.

BACKGROUND: We aimed to explore the electrophysiological changes in poststroke subjects with depressed mood. METHODS: Resting-state electroencephalogram (EEG) signals of 16 electrodes in 35 poststroke depressed, 24 poststroke nondepressed, and 35 age-matched healthy control subjects were analyzed by means of spectral power analysis, a quantitative EEG measurement of different frequency bands. The relationship among depressed mood, functional status, lesion side, and poststroke time was assessed by using variance and Spearman correlation analysis. Multiple analysis of variance was used to compare the differences among the 3 groups. Binary logistic regression analysis was used to establish a regression model to predict depressed mood in stroke subjects and to explore the association between depression and EEG band power. Receiver operating characteristic curves were used to estimate the ability of spectral power selected by binary logistic regression to indicate depressed mood in stroke subjects. RESULTS: We found that the hemisphere in which the lesion was located and the time since stroke onset had no effect on depressed mood. Only the patient's functional status was related to emotional symptoms. Quantitative EEG analysis revealed increased delta, theta, and beta2 power in stroke subjects with depressed mood, particularly in temporal regions. The theta and beta2 power in the right temporal area were shown to be highly sensitive to depressed mood, and these parameters showed good discriminatory ability for depressed subjects following stroke. CONCLUSION: Depressed mood after stroke is associated with functional status. Quantitative EEG parameters may be a useful tool in timely screening for depressed mood after stroke.

Long-range temporal correlations of broadband EEG oscillations for depressed subjects following different hemispheric cerebral infarction.

Abnormal long-range temporal correlation (LRTC) in EEG oscillation has been observed in several brain pathologies and mental disorders. This study examined the relationship between the LRTC of broadband EEG oscillation and depression following cerebral infarction with different hemispheric lesions to provide a novel insight into such depressive disorders. Resting EEGs of 16 channels in 18 depressed (9 left and 9 right lesions) and 21 non-depressed (11 left and 10 right lesions) subjects following cerebral infarction and 19 healthy control subjects were analysed by means of detrended fluctuation analysis, a quantitative measurement of LRTC. The difference among groups and the correlation between the severity of depression and LRTC in EEG oscillation were investigated by statistical analysis. The results showed that LRTC of broadband EEG oscillations in depressive subjects was still preserved but attenuated in right hemispheric lesion subjects especially in left pre-frontal and right inferior frontal and posterior temporal regions. Moreover, an association between the severity of psychiatric symptoms and the attenuation of the LRTC was found in frontal, central and temporal regions for stroke subjects with right lesions. A high discriminating ability of the LRTC in the frontal and central regions to distinguish depressive from non-depressive subjects suggested potential feasibility for LRTC as an assessment indicator for depression following right hemispheric cerebral infarction. Different performance of temporal correlation in depressed subjects following the two hemispheric lesions implied complex association between depression and stroke lesion location.

Quantitative EEG abnormalities in major depressive disorder with basal ganglia stroke with lesions in different hemispheres.

BACKGROUND: This study aimed to examine the aberrant EEG oscillation in major depressive subjects with basal ganglia stroke with lesions in different hemispheres. METHODS: Resting EEG of 16 electrodes in 58 stroke subjects, 26 of whom had poststroke depression (13 with left-hemisphere lesion and 13 with right) and 32 of whom did not (18 with left lesion and 14 with right), was recorded to obtain spectral power analysis for several frequency bands. Multiple analysis of variance and receiver operating characteristic (ROC) curves were used to identify differences between poststroke depression (PSD) and poststroke non-depression (PSND), treating the different lesion hemispheres separately. Moreover, Pearson linear correlation analysis was conducted to test the severity of depressive symptoms and EEG indices. RESULTS: PSD with left-hemisphere lesion showed increased beta2 power in frontal and central areas, but PSD with right-hemisphere lesion showed increased theta and alpha power mainly in occipital and temporal regions. Additionally, for left-hemisphere lesions, beta2 power in central and right parietal regions provided high discrimination between PSD and PSND, and for right-hemisphere lesions, theta power was similarly discriminative in most regions, especially temporal regions. We also explored the association between symptoms of depression and the power of abnormal bands, but we found no such relationship. LIMITATIONS: The sample size was relatively small and included subjects with different lesions of the basal ganglia. CONCLUSIONS: The aberrant EEG oscillation in subjects with PSD differs between subjects with lesions of the left and right hemispheres, suggesting a complex association between depression and lesion location in stroke patients.

Event-Related Beta EEG Changes During Active, Passive Movement and Functional Electrical Stimulation of the Lower Limb.

A number of electroencephalographic (EEG) studies have reported on event-related desynchronization/synchronization (ERD/ERS) during active movements, passive movements, and the movements induced by functional electrical stimulation (FES). However, the quantitative differences in ERD values and affected frequency bands associated with the lower limb have not been discussed. The goal of this paper was to quantitatively compare the ERD patterns during active movement, passive movement and FES-induced movement of the lower limb. 64-channel EEG signals were recorded to investigate the brain oscillatory patterns during active movement, passive movement and FES-induced movement of the lower limb in twelve healthy subjects. And passive movement and FES-induced movement were also performed in a hemiplegic stroke patient. For healthy subjects, FES-induced movement presented significantly higher characteristic frequency of central beta ERD while there was no significant difference in ERD values compared with active or passive movement. Meanwhile, beta ERD values of FES-induced movement were significantly correlated with those of active movement, and spatial distribution of beta ERD pattern for FES-induced movement was more correlated with that for active movement. In addition, the stroke patient presented central ERD patterns during FES-induced movement, while no ERD with similar frequencies could be found during passive movement. This work implies that the EEG oscillatory pattern under FES-induced movement tends more towards active movement instead of passive movement. The quantification of ERD patterns could be expected as a potential technique to evaluate the brain response during FES-induced movement.

Neural complexity in patients with poststroke depression: A resting EEG study.

BACKGROUND: Poststroke depression (PSD) is one of the most common emotional disorders affecting post-stroke patients. However, the neurophysiological mechanism remains elusive. This study was aimed to study the relationship between complexity of neural electrical activity and PSD. METHODS: Resting state eye-closed electroencephalogram (EEG) signals of 16 electrodes were recorded in 21 ischemic poststroke depression (PSD) patients, 22 ischemic poststroke non-depression (PSND) patients and 15 healthy controls (CONT). Lempel-Ziv Complexity (LZC) was used to evaluate changes in EEG complexity in PSD patients. Statistical analysis was performed to explore difference among different groups and electrodes. Correlation between the severity of depression (HDRS) and EEG complexity was determined with pearson correlation coefficients. Receiver operating characteristic (ROC) and binary logistic regression analysis were conducted to estimate the discriminating ability of LZC for PSD in specificity, sensitivity and accuracy. RESULTS: PSD patients showed lower neural complexity compared with PSND and CONT subjects in the whole brain regions. There was no significant difference among different brain regions, and no interactions between group and electrodes. None of the LZC significantly correlated with overall depression severity or differentiated symptom severity of 7 items in PSD patients, but in stroke patients, significant correlation was found between HDRS and LZC in the whole brain regions, especially in frontal and temporal. LZC parameters used for PSD recognition possessed more than 85% in specificity, sensitivity and accuracy, suggesting the feasibility of LZC to serve as screening indicators for PSD. Increased slow wave rhythms were found in PSD patients and clearly correlation was confirmed between neuronal complexity and spectral power of the four EEG rhythms. LIMITATIONS: Lesion location of stroke patients in the study distributed in different brain regions, and most of the PSD patients were mild or moderate in depressive severity. CONCLUSIONS: Compared with conventional spectral analysis, complexity of neural activity using LZC was more sensitive and stationary in the measurement of abnormal brain activity in PSD patients and may offer a potential approach to facilitate clinical screening of this disease.