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.

Generalization indicates asymmetric and interactive control networks for multi-finger dexterous movements

Finger dexterity is manifested by coordinated patterns of muscle activity and generalization of learning across contexts. Some fingers flex, others extend, and some are immobile. Whether or not the neural control processes of these direction-specific actions are independent remains unclear. We characterized behavioral principles underlying learning and generalization of dexterous flexion and extension movements, within and across hands, using an isometric dexterity task that precisely measured finger individuation, force accuracy, and temporal synchronization. Two cohorts of participants trained for 3 days in either the flexion or extension direction. All dexterity measures in both groups showed post-training improvement, although finger extension exhibited inferior dexterity. Surprisingly, learning of finger extension generalized to the untrained flexion direction, but not vice versa. This flexion bias was also evident in the untrained hand. Our study indicates direction-specific control circuits for learning of finger flexion and extension that interact by partially, but asymmetrically, transferring between directions.

Separable systems for recovery of finger strength and control after stroke

Impaired hand function after stroke is a major cause of long-term disability. We developed a novel paradigm that quantifies two critical aspects of hand function, strength, and independent control of fingers (individuation), and also removes any obligatory dependence between them. Hand recovery was tracked in 54 patients with hemiparesis over the first year after stroke. Most recovery of strength and individuation occurred within the first 3 mo. A novel time-invariant recovery function was identified: recovery of strength and individuation were tightly correlated up to a strength level of ~60% of estimated premorbid strength; beyond this threshold, strength improvement was not accompanied by further improvement in individuation. Any additional improvement in individuation was attributable instead to a second process that superimposed on the recovery function. We conclude that two separate systems are responsible for poststroke hand recovery: one contributes almost all of strength and some individuation; the other contributes additional individuation.NEW & NOTEWORTHY We tracked recovery of the hand over a 1-yr period after stroke in a large cohort of patients, using a novel paradigm that enabled independent measurement of finger strength and control. Most recovery of strength and control occurs in the first 3 mo after stroke. We found that two separable systems are responsible for motor recovery of hand: one contributes strength and some dexterity, whereas a second contributes additional dexterity.

Extracting extensor digitorum communis activation patterns using high-density surface electromyography

The extensor digitorum communis muscle plays an important role in hand dexterity during object manipulations. This multi-tendinous muscle is believed to be controlled through separate motoneuron pools, thereby forming different compartments that control individual digits. However, due to the complex anatomical variations across individuals and the flexibility of neural control strategies, the spatial activation patterns of the extensor digitorum communis compartments during individual finger extension have not been fully tracked under different task conditions. The objective of this study was to quantify the global spatial activation patterns of the extensor digitorum communis using high-density (7 × 9) surface electromyogram (EMG) recordings. The muscle activation map (based on the root mean square of the EMG) was constructed when subjects performed individual four finger extensions at the metacarpophalangeal joint, at different effort levels and under different finger constraints (static and dynamic). Our results revealed distinct activation patterns during individual finger extensions, especially between index and middle finger extensions, although the activation between ring and little finger extensions showed strong covariance. The activation map was relatively consistent at different muscle contraction levels and for different finger constraint conditions. We also found that distinct activation patterns were more discernible in the proximal–distal direction than in the radial–ulnar direction. The global spatial activation map utilizing surface grid EMG of the extensor digitorum communis muscle provides information for localizing individual compartments of the extensor muscle during finger extensions. This is of potential value for identifying more selective control input for assistive devices. Such information can also provide a basis for understanding hand impairment in individuals with neural disorders.