Purpose of review

This review considers recent insights into the neurobiology of repair after stroke in animals and humans, the range of emerging therapies to promote repair and recovery after the acute phase of stroke, and issues related to optimizing trials of such therapies.

Recent findings

Animal studies continue to shed light on the molecular, vascular, glial, neuronal, behavioral, and environmental events that are important to the spontaneous behavioral recovery that is observed during the weeks after a stroke. Animal and human studies are examining a wide range of potential interventions that may favorably modify outcome, including small molecules, growth factors, cell-based approaches, electromagnetic stimulation, a range of devices and robots, and intense physiotherapy methods, including constraint-induced movement therapy. Optimal prescription of these restorative therapies in human patients with stroke requires further study, including defining potential roles for functional neuroimaging.

Summary

A wide range of therapies shows promise for improving poststroke brain repair. Insights into the neurobiology of brain repair after stroke in animals and in humans continue to accrue. This information might prove useful in designing and implementing clinical trials that aim to measure the clinical effects of restorative therapies after stroke.

Many different measures have been found to be related to behavioral outcome after stroke. Preclinical studies emphasize the importance of brain injury and neural function. However, the measures most important to human outcomes remain uncertain, in part because studies often examine one measure at a time or enroll only mildly impaired patients. The current study addressed this by performing multimodal evaluation in a heterogeneous population. Patients (n = 36) with stable arm paresis 3-6 months post-stroke were assessed across 6 categories of measures related to stroke outcome: demographics/medical history, cognitive/mood status, genetics, neurophysiology, brain injury, and cortical function. Multivariate modeling identified measures independently related to an impairment-based outcome (arm Fugl-Meyer motor score). Analyses were repeated (1) identifying measures related to disability (modified Rankin Scale score), describing independence in daily functions and (2) using only patients with mild deficits. Across patients, greater impairment was related to measures of injury (reduced corticospinal tract integrity) and neurophysiology (absence of motor evoked potential). In contrast, (1) greater disability was related to greater injury and poorer cognitive status (MMSE score) and (2) among patients with mild deficits, greater impairment was related to cortical function (greater contralesional motor/premotor cortex activation). Impairment after stroke is most related to injury and neurophysiology, consistent with preclinical studies. These relationships vary according to the patient subgroup or the behavioral endpoint studied. One potential implication of these results is that choice of biomarker or stratifying variable in a clinical stroke study might vary according to patient characteristics.

Background. Proprioception of fingers is essential for motor control. Reduced proprioception is common after stroke and is associated with longer hospitalization and reduced quality of life. Neural correlates of proprioception deficits after stroke remain incompletely understood, partly because of weaknesses of clinical proprioception assessments. Objective. To examine the neural basis of finger proprioception deficits after stroke. We hypothesized that a model incorporating both neural injury and neural function of the somatosensory system is necessary for delineating proprioception deficits poststroke. Methods. Finger proprioception was measured using a robot in 27 individuals with chronic unilateral stroke; measures of neural injury (damage to gray and white matter, including corticospinal and thalamocortical sensory tracts), neural function (activation of and connectivity of cortical sensorimotor areas), and clinical status (demographics and behavioral measures) were also assessed. Results. Impairment in finger proprioception was present contralesionally in 67% and bilaterally in 56%. Robotic measures of proprioception deficits were more sensitive than standard scales and were specific to proprioception. Multivariable modeling found that contralesional proprioception deficits were best explained (r² = 0.63; P = .0006) by a combination of neural function (connectivity between ipsilesional secondary somatosensory cortex and ipsilesional primary motor cortex) and neural injury (total sensory system injury). Conclusions. Impairment of finger proprioception occurs frequently after stroke and is best measured using a quantitative device such as a robot. A model containing a measure of neural function plus a measure of neural injury best explained proprioception performance. These measurements might be useful in the development of novel neurorehabilitation therapies.