Neural Mechanisms of Neuro-Rehabilitation Using Transcranial Direct Current Stimulation (tDCS) over the Front-Polar Area.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation (NIBS) technique that applies a weak current to the scalp to modulate neuronal excitability by stimulating the cerebral cortex. The technique can produce either somatic depolarization (anodal stimulation) or somatic hyperpolarization (cathodal stimulation), based on the polarity of the current used by noninvasively stimulating the cerebral cortex with a weak current from the scalp, making it a NIBS technique that can modulate neuronal excitability. Thus, tDCS has emerged as a hopeful clinical neuro-rehabilitation treatment strategy. This method has a broad range of potential uses in rehabilitation medicine for neurodegenerative diseases, including Parkinson's disease (PD). The present paper reviews the efficacy of tDCS over the front-polar area (FPA) in healthy subjects, as well as patients with PD, where tDCS is mainly applied to the primary motor cortex (M1 area). Multiple evidence lines indicate that the FPA plays a part in motor learning. Furthermore, recent studies have reported that tDCS applied over the FPA can improve motor functions in both healthy adults and PD patients. We argue that the application of tDCS to the FPA promotes motor skill learning through its effects on the M1 area and midbrain dopamine neurons. Additionally, we will review other unique outcomes of tDCS over the FPA, such as effects on persistence and motivation, and discuss their underlying neural mechanisms. These findings support the claim that the FPA could emerge as a new key brain region for tDCS in neuro-rehabilitation.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling.

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

Classification of Motor Impairments of Post-Stroke Patients Based on Force Applied to a Handrail.

Many patients suffer from declined motor abilities after a brain injury. To provide appropriate rehabilitation programs and encourage motor-impaired patients to participate further in rehabilitation, sufficient and easy evaluation methodologies are necessary. This study is focused on the sit-to-stand motion of post-stroke patients because it is an important daily activity. Our previous study utilized muscle synergies (synchronized muscle activation) to classify the degree of motor impairment in patients and proposed appropriate rehabilitation methodologies. However, in our previous study, the patient was required to attach electromyography sensors to his/her body; thus, it was difficult to evaluate motor ability in daily circumstances. Here, we developed a handrail-type sensor that can measure the force applied to it. Using temporal features of the force data, the relationship between the degree of motor impairment and temporal features was clarified, and a classification model was developed using a random forest model to determine the degree of motor impairment in hemiplegic patients. The results show that hemiplegic patients with severe motor impairments tend to apply greater force to the handrail and use the handrail for a longer period. It was also determined that patients with severe motor impairments did not move forward while standing up, but relied more on the handrail to pull their upper body upward as compared to patients with moderate impairments. Furthermore, based on the developed classification model, patients were successfully classified as having severe or moderate impairments. The developed classification model can also detect long-term patient recovery. The handrail-type sensor does not require additional sensors on the patient's body and provides an easy evaluation methodology.

Decreased frontotemporal connectivity in patients with parkinson's disease experiencing face pareidolia.

The precise neural underpinnings of face pareidolia in patients with Parkinson's disease (PD) remain unclear. We aimed to clarify face recognition network abnormalities associated with face pareidolia in such patients. Eighty-three patients with PD and 40 healthy controls were recruited in this study. Patients with PD were classified into pareidolia and nonpareidolia groups. Volumetric analyses revealed no significant differences between the pareidolia (n = 39) and nonpareidolia (n = 44) patient groups. We further observed decreased functional connectivity among regions of interest in the bilateral frontotemporal lobes in patients with pareidolia. Seed-based analysis using bilateral temporal fusiform cortices as seeds revealed significantly decreased connectivity with the bilateral inferior medial prefrontal cortices in the pareidolia group. Post hoc regression analysis further demonstrated that the severity of face pareidolia was negatively correlated with functional connectivity between the bilateral temporal fusiform and medial prefrontal cortices. Our findings suggest that top-down modulation of the face recognition network is impaired in patients with PD experiencing face pareidolia.

Effect of Neurofeedback Facilitation on Poststroke Gait and Balance Recovery: A Randomized Controlled Trial.

OBJECTIVE: To test the hypothesis that supplementary motor area (SMA) facilitation with functional near-infrared spectroscopy-mediated neurofeedback (fNIRS-NFB) augments poststroke gait and balance recovery, we conducted a 2-center, double-blind, randomized controlled trial involving 54 Japanese patients using the 3-meter Timed Up and Go (TUG) test. METHODS: Patients with subcortical stroke-induced mild to moderate gait disturbance more than 12 weeks from onset underwent 6 sessions of SMA neurofeedback facilitation during gait- and balance-related motor imagery using fNIRS-NFB. Participants were randomly allocated to intervention (28 patients) or placebo (sham: 26 patients). In the intervention group, the fNIRS signal contained participants' cortical activation information. The primary outcome was TUG improvement 4 weeks postintervention. RESULTS: The intervention group showed greater improvement in the TUG test (12.84 ± 15.07 seconds, 95% confidence interval 7.00-18.68) than the sham group (5.51 ± 7.64 seconds, 95% confidence interval 2.43-8.60; group difference 7.33 seconds, 95% CI 0.83-13.83; p = 0.028), even after adjusting for covariates (group × time interaction; F 1.23,61.69 = 4.50, p = 0.030, partial η2 = 0.083). Only the intervention group showed significantly increased imagery-related SMA activation and enhancement of resting-state connectivity between SMA and ventrolateral premotor area. Adverse effects associated with fNIRS-mediated neurofeedback intervention were absent. CONCLUSION: SMA facilitation during motor imagery using fNIRS neurofeedback may augment poststroke gait and balance recovery by modulating the SMA and its related network. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients with gait disturbance from subcortical stroke, SMA neurofeedback facilitation improves TUG time (UMIN000010723 at UMIN-CTR; umin.ac.jp/english/).

Electroencephalographic Phase Synchrony Index as a Biomarker of Poststroke Motor Impairment and Recovery.

Background. Motor recovery after stroke is of great clinical interest. Besides magnetic resonance imaging functional connectivity, electroencephalographic synchrony is also an available biomarker. However, the clinical relevance of electroencephalographic synchrony in hemiparesis has not been fully understood. Objective. We aimed to demonstrate the usefulness of the phase synchrony index (PSI) by showing associations between the PSI and poststroke outcome in patients with hemiparesis. Methods. This observational study included 40 participants with cortical ischemic stroke (aged 69.8 ± 13.8 years) and 22 healthy controls (aged 66.9 ± 6.5 years). Nineteen-channel electroencephalography was recorded at 36.9 ± 11.8 days poststroke. Upper extremity Fugl-Meyer scores were assessed at the time of admission/before discharge (FM-UE1/FM-UE2; 32.6 ± 12.3/121.0 ± 44.7 days poststroke). Then, correlations between the PSIs and FM-UE1 as well as impairment reduction after rehabilitation (FM-UEgain) were analyzed. Results. The interhemispheric PSI (alpha band) between the primary motor areas (M1s) was lower in patients than in controls and was selectively correlated with FM-UE1 (P = .001). In contrast, the PSI (theta band) centered on the contralesional M1 was higher in patients than in controls and was selectively correlated with FM-UEgain (P = .003). These correlations remained significant after adjusting for confounding factors (age, time poststroke, National Institute of Health Stroke Scale, and lesion volume). Furthermore, the latter correlation was significant in severely impaired patients (FM-UE1 ≤ 10). Conclusions. This study showed that the PSIs were selectively correlated with motor impairment and recovery. Therefore, the PSIs may be potential biomarkers in persons with a hemispheric infarction.

Temporal Features of Muscle Synergies in Sit-to-Stand Motion Reflect the Motor Impairment of Post-Stroke Patients.

Sit-to-stand (STS) motion is an important daily activity, and many post-stroke patients have difficulty performing STS motion. Previous studies found that there are four muscle synergies (synchronized muscle activations) in the STS motion of healthy adults. However, for post-stroke patients, it is unclear whether muscle synergies change and which features primarily reflect motor impairment. Here, we use a machine learning method to demonstrate that temporal features in two muscle synergies that contribute to hip rising and balance maintenance motion reflect the motor impairment of post-stroke patients. Analyzing the muscle synergies of age-matched healthy elderly people ( n = 12 ) and post-stroke patients ( n = 33 ), we found that the same four muscle synergies could account for the muscle activity of post-stroke patients. Also, we were able to distinguish post-stroke patients from healthy people on the basis of the temporal features of these muscle synergies. Furthermore, these temporal features were found to correlate with motor impairment of post-stroke patients. We conclude that post-stroke patients can still utilize the same number of muscle synergies as healthy people, but the temporal structure of muscle synergies changes as a result of motor impairment. This could lead to a new rehabilitation strategy for post-stroke patients that focuses on activation timing of muscle synergies.

Organization of functional modularity in sitting balance response and gait performance after stroke.

BACKGROUND: Recovery of postural adjustment, especially when seated, is important for performing activities of daily living after stroke. However, conventional clinical measures provide little insight into a common strategy for dynamic sitting balance and gait. We aimed to evaluate functional re-organization of posture and ambulatory performance after stroke. METHODS: The subjects of the study included 5 healthy men and 21 post-stroke patients. The spatiotemporal modular organization of ground reaction forces during a balance task in which the leg on the non-affected side was lifted off the ground while seated was quantified by using complex principal component analysis. FINDINGS: A 3% decrease in the temporal strength of the primary module in post-stroke patients was an independent predictor of gait performance in the hospital setting with high sensitivity and specificity. Tuning of the temporal strength was accompanied by the recovery of sitting and ambulation. INTERPRETATION: Our findings suggest that evaluation of the modular characteristics of ground reaction forces during a sitting balance task allows us to predict recovery and functional adaptation through daily physical rehabilitation.

Involvement of cortical dysfunction in frequent falls in patients with Parkinson's disease.

INTRODUCTION: Gait and balance disorders are common clinical features of Parkinson's disease (PD). Although falls significantly affect the activities of daily living (ADL) and quality of life (QOL) of patients with PD, the underlying neural mechanisms associated with frequent falls in PD patients are still unclear. METHODS: Hypothesizing that the cerebral cortex would contribute to frequent falls in PD, we obtained 3D T1-weighted images from 91 non-dementia patients with PD and performed voxel-based morphometric analysis (VBM). Gray matter volume was compared between patients with and without frequent falls to investigate the structural basis for frequent falls in PD. As an ancillary analysis, we also performed resting-state functional magnetic resonance analysis using data from 58 patients. RESULTS: Among the 91 patients, 36 had experienced frequent falls. Gray matter volume in the right superior temporal gyrus (STG) and the right inferior parietal lobule (IPL) of these patients was significantly lower than that of the non-frequent fallers. There was also a significant correlation between fall frequency and gray matter volume in these two regions. Additionally, resting-state functional analysis revealed lower connectivity in the right posterior perisylvian region, including in the IPL and STG, in frequent fallers than in non-frequent fallers. CONCLUSION: Frequent falls in PD are associated with structural and functional abnormality of the cerebral cortex including the right IPL and STG.

Large-Scale Phase Synchrony Reflects Clinical Status After Stroke: An EEG Study.

BACKGROUND AND PURPOSE: Stroke-induced focal brain lesions often exert remote effects via residual neural network activity. Electroencephalographic (EEG) techniques can assess neural network modifications after brain damage. Recently, EEG phase synchrony analyses have shown associations between the level of large-scale phase synchrony of brain activity and clinical symptoms; however, few reports have assessed such associations in stroke patients. OBJECTIVE: The aim of this study was to investigate the clinical relevance of hemispheric phase synchrony in stroke patients by calculating its correlation with clinical status. METHODS: This cross-sectional study included 19 patients with post-acute ischemic stroke admitted for inpatient rehabilitation. Interhemispheric phase synchrony indices (IH-PSIs) were computed in 2 frequency bands (alpha [α], and beta [ß]), and associations between indices and scores of the Functional Independence Measure (FIM), the National Institutes of Health Stroke Scale (NIHSS), and the Fugl-Meyer Motor Assessment (FMA) were analyzed. For further assessments of IH-PSIs, ipsilesional intrahemispheric PSIs (IntraH-PSIs) as well as IH- and IntraH-phase lag indices (PLIs) were also evaluated. RESULTS: IH-PSIs correlated significantly with FIM scores and NIHSS scores. In contrast, IH-PSIs did not correlate with FMA scores. IntraH-PSIs correlate with FIM scores after removal of the outlier. The results of analysis with PLIs were consistent with IH-PSIs. CONCLUSIONS: The PSIs correlated with performance on the activities of daily living scale but not with scores on a pure motor impairment scale. These results suggest that large-scale phase synchrony represented by IH-PSIs provides a novel surrogate marker for clinical status after stroke.