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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. 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.

Background Studies demonstrate that most arm motor recovery occurs within 3 months after stroke, when measured with standard clinical scales. Improvements on these measures, however, reflect a combination of recovery in motor control, increases in strength, and acquisition of compensatory strategies. Objective To isolate and characterize the time course of recovery of arm motor control over the first year post-stroke. Methods Longitudinal study of 18 participants with acute ischemic stroke. Motor control was evaluated kinematically using a 2-D reaching task designed to minimize the need for anti-gravity strength and prevent compensation. Arm impairment was evaluated with the Fugl-Meyer assessment for upper extremity (FMA-UE), activity limitation with the Action Research Arm Test (ARAT), and strength with biceps dynamometry. Assessments were conducted at: 1.5, 5, 14, 27, and 54 weeks post-stroke. Results Motor control in the paretic arm improved up to week 5, with no further improvement beyond this time point. In contrast, improvements in the FMA-UE, ARAT, and biceps dynamometry continued beyond 5 weeks, with a similar magnitude of improvement between weeks 5 and 54 as between weeks 1.5 and 5. Conclusions Recovery after stroke plateaued much earlier for arm motor control, isolated with a global kinematic measure, compared to motor function assessed with clinical scales. This dissociation between the time courses of kinematic and clinical measures of recovery may be due to the contribution of strength improvement to the latter. Novel interventions, focused on the first month post-stroke, will be required to exploit the narrower window of spontaneous recovery for motor control.

The cerebellum has long been recognized to play an important role in motor adaptation. Individuals with cerebellar ataxia exhibit impaired learning in visuomotor adaptation tasks such as prism adaptation and force field learning. Both types of tasks involve the adjustment of an internal model to compensate for an external perturbation. This updating process is error driven, with the error signal based on the difference between anticipated and actual sensory information. This process may entail a credit assignment problem, with a distinction made between error arising from faulty representation of the environment and error arising from noise in the controller. We hypothesized that people with ataxia may perform poorly at visuomotor adaptation because they attribute a greater proportion of their error to their motor control difficulties. We tested this hypothesis using a computational model based on a Kalman filter. We imposed a 20-deg visuomotor rotation in either a single large step or in a series of smaller 5-deg steps. The ataxic group exhibited a comparable deficit in both conditions. The computational analyses indicate that the patients' deficit cannot be accounted for simply by their increased motor variability. Rather, the patients' deficit in learning may be related to difficulty in estimating the instability in the environment or variability in their motor system.