Neurorehabilitation and neural repair最新文献

Objective: To compare the therapeutic effect of intermittent theta burst stimulation (iTBS) and repetitive transcranial magnetic stimulation (rTMS) on cognitive function in patients with post-stroke cognitive impairment (PSCI) and investigate underlying neuroelectrophysiological mechanisms using microstate analysis.

Methods: In this randomized, double-blind, sham-controlled trial, 45 patients with PSCI were assigned 2:2:1 to iTBS, rTMS, and sham groups, with stimulation targeting the left dorsolateral prefrontal cortex. All participants also received therapist-delivered cognitive training in addition to stimulation. Outcomes were evaluated before (T0) and 10 days after (T1). The primary outcome measure was Montreal Cognitive Assessment (MoCA) score. Secondary outcomes were auditory verbal learning test, Wechsler Adult Intelligence Scale-Ⅲ digit symbol coding test and digit span test scores as well as microstate indices.

Results: ΔMoCA(T1-T0) scores were significantly improved in both the iTBS (median [interquartile range]: 2.00 [1.00, 4.00]) and rTMS groups (2.00 [1.00, 3.00]) compared with sham group (P < .05). There was no significant difference in ΔMoCA between the 2 active protocols. Significant within-group improvements in memory and working memory were observed in the iTBS group (P < .05). Both iTBS and rTMS group showed significantly increased microstate C parameters between T0 and T1 (P < .05). Furthermore, the transition probabilities in the iTBS group showed more diversity between microstates, while the other groups showed no significant transformation.

Conclusion: iTBS and 5-Hz rTMS were effective in improving overall cognitive ability in PSCI, and iTBS may represent a practical, time-efficient alternative to 5-Hz rTMS. EEG microstate suggested distinct modulation patterns, serving as a useful exploratory tool.Clinical Trial Registry Name:Effect of different transcranial magnetic stimulation protocols on cognitive function in patients with post-stroke cognitive impairment.

Clinical trial registration-url: https://www.chictr.org.cn/Clinical Trial Registration Number:ChiCTR2200064233.

BackgroundFatigue, a complex and multidimensional complaint, is highly prevalent after stroke and contributes to adverse outcomes and impaired motor recovery. Here, we focus on post-stroke motor fatigability (PSMF), which refers to objective limitations in continuous motor performance post-stroke. PSMF can impair the performance of activities of daily living and may significantly hinder rehabilitation efforts, limiting progress and recovery.ObjectivesThe purpose of this review is to summarize the current understanding of PSMF and to evaluate various tools used to investigate its underlying mechanisms.ResultsPrior studies on PMSF differ significantly in their approaches, with some employing neurophysiology and neurostimulation to investigate neural mechanisms, while others focus on functional assessments. Inconsistent terminology and the lack of standardized methodology are key barriers to reaching meaningful conclusions. While there is some consensus that central factors in the neuromuscular pathway limit sustained motor activity more than peripheral factors, additional research is needed to understand the timing and pathophysiology of PSMF including its relationship with other impairments of motor control. We present several specific recommendations for future studies, including the use of proper taxonomy to demystify the patient complaint, consistent paradigms to evoke fatigability, and neurophysiological tools to locate its origin.ConclusionApplying these guidelines to future investigations will help researchers better identify stroke-specific limitations in continuous motor performance and develop tailored interventions to help patients adjust to the persistent, repetitive demands of daily life.

BackgroundFugl-Meyer Assessment of upper and lower extremity is the recommended primary clinical outcome measure of motor function in stroke rehabilitation. However, variations between different manuals undermine the reliability of the assessment, making it difficult to compare results and pool data across trials and centers.ObjectiveTo develop a consensus-based international Fugl-Meyer Assessment (FMA) manual aligned with the original assessment along with agreed recommendations for assessor training. Additionally, the study aims to provide a critical review of current evidence on the measurement properties.MethodsFourteen experienced health professionals and expert FMA users, working in 3 different continents, 6 countries and 13 research centers, participated in an iterative consensus process to generate a comprehensive agreed FMA manual. Agreement of at least 75% determined by voting was the minimum accepted threshold for each section of the manual. Consensus on assessor training was also sought. The evidence on measurement properties was compiled through a systematic literature review.ResultsGreater than 79% agreement was reached for each section of the final FMA manual. Assessors should have strong foundation in neurorehabilitation and clinical assessment. Novice assessors should undergo structured training including supervised practical training with patients to ensure consistent and accurate scoring. Previous research adherent to the original FMA assessment, confirms strong validity and reliability, but provide limited information of minimal clinically important difference thresholds.ConclusionsThis internationally agreed manual provides a common ground for improved consistency in administration of FMA worldwide and thereby will enable reliable data pooling and increase the comparability of results in future trials and clinical practice.

BackgroundSpatial neglect (SN) is a common visual attention deficit affecting stroke patients due to large-scale disruptions within brain networks. Most studies have focused only on resting-state, but effective rehabilitation requires a clearer understanding of how brain networks change during visuospatial tasks.ObjectiveThis study aims to identify network disruptions associated with neglect by comparing resting-state and task-based electroencephalography (EEG) connectivity patterns in stroke patients with and without neglect.MethodsWe recorded EEG data from 28 stroke patients using the augmented reality (AR)-based EEG-guided neglect detection system (AREEN) during resting-state and a visuospatial task. Connectivity was measured using coherence in delta, theta, alpha, and beta bands for both conditions, with gamma-band coherence assessed only during the task. Graph-based metrics were applied to model network-level disruptions. Classification models evaluated the significance of connectivity features to find patterns predictive of neglect.ResultsThe neglect group showed reduced connectivity in frontal and right parieto-occipital (ParOcc) regions, primarily in beta and theta bands, during both conditions, with additional gamma-band connectivity differences in the task condition, compared to the non-neglect group. Conversely, connectivity was greater in central and midline regions, which may indicate a maladaptive shift in network organization. Classification models accurately classified patients into neglect and non-neglect groups (resting-state: 87.0% ± 0.7%; task: 80.9% ± 16.0%). Feature importance analysis identified eigenvector and closeness centrality within frontal, right ParOcc, and central regions as key predictors.ConclusionsNetwork disruptions can effectively identify SN and provide potential targets for connectivity-based rehabilitation. Future studies should investigate whether these interventions improve attention and recovery in stroke patients.This study was registered at ClinicalTrials.gov under ID NCT04187131.

IntroductionCorticospinal tract lesion load (CST-LL) is a biomarker used for studying motor outcomes after stroke. However, the optimal method for calculating this metric is unknown.MethodsThis is a cross-sectional study of a large ischemic stroke cohort from the ENIGMA Stroke Recovery Consortium (n = 221; mean age = 59.8 years, 56% male) to compare 4 lesion load metrics across 3 CST templates. We then validate these findings in another large, independent stroke cohort (n = 125; mean age = 64.6 years, 54% male).ResultsResults indicate that variance in behavioral outcome was best explained using the maximum weighted cross-sectional overlap between lesion and the CST (Max-WLL), and when using an age-appropriate normative CST template (generated from the HCP Aging study). This was true both when the outcome was motor impairment, measured using the Fugl-Meyer Upper Extremity scale (FMUE, relative explained variance (REV) = 58.9%), and when it was global function, measured using the Barthel Index (BI, REV = 60%). In the validation cohort, FMUE results were replicated (REV = 47.6%).ConclusionThe findings indicate that Max-WLL, which represents the proportion of transected CST fibers, most accurately captures CST injury as it relates to motor and functional outcomes after stroke. Additionally, results suggest the importance of an age-appropriate template, a key consideration given that stroke is largely a disease of the elderly. Together, these findings provide an independently validated tool to optimize future research examining CST injury after stroke.

BackgroundThe Wolf Motor Function Test (WMFT) is a well-recognized measure for assessing upper extremity motor function in stroke rehabilitation. However, prolonged administration time limits the WMFT in clinical use.ObjectiveThis study aimed to reduce the number of WMFT tasks using machine learning and explore its measurement structure and psychometric properties, using data from 3 stroke rehabilitation trials that together engaged 543 participants with a wide range of motor impairment during subacute and chronic recovery phases.MethodsWMFT performance time data were converted to rates and outliers were eliminated using multivariate normality tests. Random forest regression with the elbow method was employed to determine the optimal number of items in the WMFT. Further, a machine learning technique with cross-validation and bootstrapping was used to select items. We used confirmatory factor analysis to determine the measurement structure of the original and shortened version of WMFT. Psychometric properties of the shortened version were also assessed.ResultsMachine learning-based item reduction identified 4 items (Hand to Table, Hand to Box, Extend Elbow Without Weight, and Lift Can) as representative tasks. Factor analysis revealed a 2-factor structure for both original and shorten versions, comprising non-manipulative/transport and manipulative/dexterity factors. WMFT-4 showed strong convergent validity with WMFT-15 (R = 0.98, P < .001) and moderate cross-domain validity with the Fugl-Meyer Assessment of Upper Extremity (FMA-UE) (R = 0.523, P < .001), comparable to the original WMFT-15 (R = 0.526, P < .001).ConclusionThe streamlined WMFT-4 enhances the feasibility of the WMFT for both clinical and research settings while maintaining its original measurement characteristics.

Cognitive impairment is highly prevalent post-stroke and is associated with poor functional outcomes. Stroke experts have highlighted 2 fundamental barriers to progress in rehabilitation and research related to post-stroke cognitive impairment: (1) there is no agreed-upon definition of post-stroke cognitive impairment, and (2) there is no consensus on the appropriate screening and diagnostic procedures. In this paper, we will discuss recent progress and remaining challenges to developing a standard general definition and understanding of post-stroke cognitive impairment. We will provide recommendations to advance the definition of post-stroke cognitive impairment, informed by the steps taken to develop a general definition for mild cognitive impairment. Finally, we discuss the impact these advances might have on stroke rehabilitation, highlighting the potential impact on motor rehabilitation, as an example.

BackgroundSpinocerebellar ataxia (SCA) is a degenerative cerebellar disease, causing progressive impairment of gait and balance in adults. To identify the ideal subjects for disease-modifying therapies it is critical to identify biomarkers for the earliest stages of SCA.ObjectiveWe investigated whether prefrontal cortex activity is increased during walking in in early SCA or in pre-manifest SCA compared to healthy control subjects.MethodsSixteen participants with genetically determined SCA and 15 age-matched healthy controls participated in the study. The SARA was administered by a movement disorders specialist before the gait assessment. An 8-channel, mobile, fNIRS, with 2 reference channels, was used to record changes in oxygenated hemoglobin (HbO₂) and deoxygenated hemoglobin within the PFC. Participants walked for 2-minutes at a comfortable pace while wearing wireless, inertial sensors to derive gait characteristics.ResultsOf the 16 individuals with SCA, 9 were classified as pre-manifest (SARA < 3) and 7 as early SCA (SARA < 10). PFC activity (HbO₂) while walking was greater than controls of similar age in people with SCA. Increased PFC activity was also present even in the pre-manifest stage of SCA. Increase in PFC activity was related to worse gait (double-support time and toe-out angle).ConclusionsPFC activity is increased in pre-manifest SCA, even when clinical scores are normal in the pre-manifest stage of the disease, and may serve as a biomarker that precedes onset of clinical disease. Increased PFC activity is consistent less automatic, cortical control of gait to compensate for impaired automatic, cerebellar control, even in early stages of ataxia.

BackgroundThe Predict REcovery Potential-2 (PREP2) prediction tool uses clinical assessments and transcranial magnetic stimulation (TMS) within 1 week post-stroke to predict individuals' upper limb functional outcome at 3 months (3M) post-stroke. PREP2 was successfully implemented in clinical care at Auckland City Hospital, New Zealand in 2017.ObjectiveThe primary aim was to evaluate the accuracy of PREP2 predictions made by clinicians during routine clinical care, with a threshold of 70% accuracy for validation. A secondary aim was to identify new baseline predictors that could increase PREP2 accuracy.MethodsEighty-three patients who received PREP2 predictions were recruited within 1 week of stroke and had their upper limb outcome assessed at 3M post-stroke with the Action Research Arm Test. Cognition and sensation were evaluated within 1 week of stroke.ResultsOverall accuracy of the PREP2 prediction tool in clinical practice was 66% (95% confidence interval, 55%-76%). Accuracy was highest for the Excellent (80%) and Poor (100%) categories and lowest for the Good category (36%). Prediction accuracy for Good outcomes was 67% for patients who did not require TMS and 27% for patients who did. Finger extension differentiated participants predicted to have a Good outcome using TMS who did and did not have a favorable upper limb outcome.ConclusionsExcellent and Poor predictions are highly accurate when used in clinical practice, however the full PREP2 tool is not yet validated in clinical practice. Future studies with larger samples could investigate additional measures to enhance accuracy of the Good prediction category.Clinical trial registration number ACTRN12619000225112, https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12619000225112.