Alterations of tactile and anatomical spatial representations of the hand after stroke.

Stroke often causes long-term motor and somatosensory impairments. Motor planning and tactile perception rely on spatial body representations. However, the link between altered spatial body representations, motor deficit and tactile spatial coding remains unclear. This study investigates the relationship between motor deficits and alterations of anatomical (body) and tactile spatial representations of the hand in 20 post-stroke patients with upper limb hemiparesis. Anatomical and tactile spatial representations were assessed from 10 targets (nails and knuckles) respectively cued verbally by their anatomical name or using tactile stimulations. Two distance metrics (hand width and finger length) and two structural measures (relative organization of targets positions and angular deviation of fingers from their physical posture) were computed and compared to clinical assessments, normative data and lesions sites. Over half of the patients had altered anatomical and/or tactile spatial representations. Metrics of tactile and anatomical representations showed common variations, where a wider hand representation was linked to more severe motor deficits. In contrast, alterations in structural measures were not concomitantly observed in tactile and anatomical representations and did not correlate with clinical assessments. Finally, a preliminary analysis showed that specific alterations in tactile structural measures were associated with dorsolateral prefrontal stroke lesions. This study reveals shared and distinct characteristics of anatomical and tactile hand spatial representations, reflecting different mechanisms that can be affected differently after stroke: metrics and location of tactile and anatomical representations were partially shared while the structural measures of tactile and anatomical representations had distinct characteristics.

Bimanual coordinated motor skill learning in patients with a chronic cerebellar stroke.

Cerebellar strokes induce coordination disorders that can affect activities of daily living. Evidence-based neurorehabilitation programs are founded on motor learning principles. The cerebellum is a key neural structure in motor learning. It is unknown whether and how well chronic cerebellar stroke individuals (CCSIs) can learn to coordinate their upper limbs through bimanual motor skill learning. The aim was to determine whether CCSIs could achieve bimanual skill learning through a serious game with the REAplan® robot and to compare CCSIs with healthy individuals (HIs). Over three consecutive days, sixteen CCSIs and eighteen HIs were trained on an asymmetric bimanual coordination task ("CIRCUIT" game) with the REAplan® robot, allowing quantification of speed, accuracy and coordination. The primary outcomes were the bimanual speed/accuracy trade-off (BiSAT) and bimanual coordination factor (BiCo). They were also evaluated on a bimanual REACHING task on Days 1 and 3. Correlation analyses between the robotic outcomes and clinical scale scores were computed. Throughout the sessions, BiSAT and BiCo improved during the CIRCUIT task in both HIs and CCSIs. On Day 3, HIs and CCSIs showed generalization of BiSAT, BiCo and transferred to the REACHING task. There was no significant between-group difference in progression. Four CCSIs and two HIs were categorized as "poor learners" according to BiSAT and/or BiCo. Increasing age correlated with reduced BiSAT but not BiCo progression. Over three days of training, HIs and CCSIs improved, retained, generalized and transferred a coordinated bimanual skill. There was no between-group difference, suggesting plastic compensation in CCSIs. Clinical trial NCT04642599 approved the 24th of November 2020.

Post-Stroke Impairments of Manual Dexterity and Finger Proprioception: Their Contribution to Upper Limb Activity Capacity.

BACKGROUND: Knowing how impaired manual dexterity and finger proprioception affect upper limb activity capacity is important for delineating targeted post-stroke interventions for upper limb recovery. OBJECTIVES: To investigate whether impaired manual dexterity and finger proprioception explain variance in post-stroke activity capacity, and whether they explain more variance than conventional clinical assessments of upper limb sensorimotor impairments. METHODS: Activity capacity and hand sensorimotor impairments were assessed using clinical measures in N = 42 late subacute/chronic hemiparetic stroke patients. Dexterity was evaluated using the Dextrain Manipulandum to quantify accuracy of visuomotor finger force-tracking (N = 36), timing of rhythmic tapping (N = 36), and finger individuation (N = 24), as well as proprioception (N = 27). Stepwise multivariate and hierarchical linear regression models were used to identify impairments best explaining activity capacity. RESULTS: Dexterity and proprioceptive components significantly increased the variance explained in activity capacity: (i) Box and Block Test was best explained by baseline tonic force during force-tracking and tapping frequency (adjusted R2 = .51); (ii) Motor Activity Log was best explained by success rate in finger individuation (adjusted R2 = .46); (iii) Action Research Arm Test was best explained by release of finger force and proprioceptive measures (improved reaction time related to use of proprioception; adjusted R2 = .52); and (iv) Moberg Pick-Up test was best explained by proprioceptive function (adjusted R2 = .18). Models excluding dexterity and proprioception variables explained up to 19% less variance. CONCLUSIONS: Manual dexterity and finger proprioception explain unique variance in activity capacity not captured by conventional impairment measures and should be assessed when considering the underlying causes of post-stroke activity capacity limitations.URL: https://www.clinicaltrials.gov. Unique identifier: NCT03934073.

Dexterity in the Acute Phase of Stroke: Impairments and Neural Substrates.

BACKGROUND: Stroke can impair manual dexterity, leading to loss of independence following incomplete recovery. Enhancing our understanding of dexterity impairment may improve neurorehabilitation. OBJECTIVES: The study aimed to measure dexterity components in acute stroke patients with and without hand motor deficits, compare them to those of healthy controls (HC), and to explore the neural substrates involved in specific components of dexterity. METHODS: We used the Dextrain Manipulandum to quantify fine finger force control, finger selection accuracy, coactivation, and reaction time (RT). Dexterity was evaluated twice (2 days apart) in 74 patients and 14 HC. Voxel-Lesion-Symptom-Mapping (VLSM) was used to analyze the relationship between tissue damage and dexterity. Results. Due to severe paresis or fatigue, 24 patients could not perform these tasks. In 50 patients (included 4.6 ± 3.3 days post-stroke), finger force control improved (P < .001), as it did in HC (P = .03) who performed better than patients on both evaluations. Accuracy of finger selection did not improve significantly in any group, but the HC performed better on both evaluations. Unexpectedly, coactivation was better in patients than in HC at D3 (P = .03). There were no between-group differences in RT. VLSM showed that damage to the superior temporal gyrus (STG) impaired finger force control while damage to the posterior limb of the internal capsule (PLIC) impaired finger selectivity. CONCLUSIONS: Acute stroke affecting the STG or PLIC impaired selective components of dexterity. Patients with mild to moderate impairment showed better finger force control and accuracy selection within 48 hours, suggesting the feasibility of detecting early dexterity improvements.

Efficacy of interactive manual dexterity training after stroke: a pilot single-blinded randomized controlled trial.

OBJECTIVE: To compare the efficacy of Dextrain Manipulandum™ training of dexterity components such as force control and independent finger movements, to dose-matched conventional therapy (CT) post-stroke. METHODS: A prospective, single-blind, pilot randomized clinical trial was conducted. Chronic-phase post-stroke patients with mild-to-moderate dexterity impairment (Box and Block Test (BBT) > 1) received 12 sessions of Dextrain or CT. Blinded measures were obtained before and after training and at 3-months follow-up. Primary outcome was BBT-change (after-before training). Secondary outcomes included changes in motor impairments, activity limitations and dexterity components. Corticospinal excitability and short intracortical inhibition (SICI) were measured using transcranial magnetic stimulation. RESULTS: BBT-change after training did not differ between the Dextrain (N = 21) vs CT group (N = 21) (median [IQR] = 5[2-7] vs 4[2-7], respectively; P = 0.36). Gains in BBT were maintained at the 3-month post-training follow-up, with a non-significant trend for enhanced BBT-change in the Dextrain group (median [IQR] = 3[- 1-7.0], P = 0.06). Several secondary outcomes showed significantly larger changes in the Dextrain group: finger tracking precision (mean ± SD = 0.3 ± 0.3N vs - 0.1 ± 0.33N; P < 0.0018), independent finger movements (34.7 ± 25.1 ms vs 7.7 ± 18.5 ms, P = 0.02) and maximal finger tapping speed (8.4 ± 7.1 vs 4.5 ± 4.9, P = 0.045). At follow-up, Dextrain group showed significantly greater improvement in Motor Activity Log (median/IQR = 0.7/0.2-0.8 vs 0.2/0.1-0.6, P = 0.05). Across both groups SICI increased in patients with greater BBT-change (Rho = 0.80, P = 0.006). Comparing Dextrain subgroups with maximal grip force higher/lower than median (61.2%), BBT-change was significantly larger in patients with low vs high grip force (7.5 ± 5.6 vs 2.9 ± 2.8; respectively, P = 0.015). CONCLUSIONS: Although immediate improvements in gross dexterity post-stroke did not significantly differ between Dextrain training and CT, our findings suggest that Dextrain enhances recovery of several dexterity components and reported hand-use, particularly when motor impairment is moderate (low initial grip force). Findings need to be confirmed in a larger trial. Trial registration ClinicalTrials.gov NCT03934073 (retrospectively registered).

Bimanual motor skill learning with robotics in chronic stroke: comparison between minimally impaired and moderately impaired patients, and healthy individuals.

BACKGROUND: Most activities of daily life (ADL) require cooperative bimanual movements. A unilateral stroke may severely impair bimanual ADL. How patients with stroke (re)learn to coordinate their upper limbs (ULs) is largely unknown. The objectives are to determine whether patients with chronic supratentorial stroke could achieve bimanual motor skill learning (bim-MSkL) and to compare bim-MSkL between patients and healthy individuals (HIs). METHODS: Twenty-four patients and ten HIs trained over 3 consecutive days on an asymmetrical bimanual coordination task (CIRCUIT) implemented as a serious game in the REAplan® robot. With a common cursor controlled by coordinated movements of the ULs through robotic handles, they performed as many laps as possible (speed constraint) on the CIRCUIT while keeping the cursor within the track (accuracy constraint). The primary outcome was a bimanual speed/accuracy trade-off (biSAT), we used a bimanual coordination factor (biCO) and bimanual forces (biFOP) for the secondary outcomes. Several clinical scales were used to evaluate motor and cognitive functions. RESULTS: Overall, the patients showed improvements on biSAT and biCO. Based on biSAT progression, the HI achieved a larger bim-MSkL than the patients with mild to moderate impairment (Fugl-Meyer Assessment Upper Extremity (FMA-UE): 28-55, n = 15) but not significantly different from those with minimal motor impairment (FMA-UE: 66, n = 9). There was a significant positive correlation between biSAT evolution and the FMA-UE and Stroke Impact Scale. CONCLUSIONS: Both HI and patients with chronic stroke training on a robotic device achieved bim-MSkL, although the more impaired patients were less efficient. Bim-MSkL with REAplan® may be interesting for neurorehabilitation after stroke. TRIAL REGISTRATION: ClinicalTrial.gov identifier: NCT03974750. Registered 05 June 2019. https://clinicaltrials.gov/ct2/show/NCT03974750?cond=NCT03974750&draw=2&rank=1.