Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation

Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration

Cerebellum: an explanation for dystonia?

Dystonia is a movement disorder that is characterized by involuntary muscle contractions, abnormal movements and postures, as well as by non-motor symptoms, and is due to abnormalities in different brain areas. In this article, we focus on the growing number of experimental studies aimed at explaining the pathophysiological role of the cerebellum in dystonia. Lastly, we highlight gaps in current knowledge and issues that future research studies should focus on as well as some of the potential applications of this research avenue. Clarifying the pathophysiological role of cerebellum in dystonia is an important concern given the increasing availability of invasive and non-invasive stimulation techniques and their potential therapeutic role in this condition

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke

Multiscale Topological Properties Of Functional Brain Networks During Motor Imagery After Stroke

In recent years, network analyses have been used to evaluate brain reorganization following stroke. However, many studies have often focused on single topological scales, leading to an incomplete model of how focal brain lesions affect multiple network properties simultaneously and how changes on smaller scales influence those on larger scales. In an EEG-based experiment on the performance of hand motor imagery (MI) in 20 patients with unilateral stroke, we observed that the anatomic lesion affects the functional brain network on multiple levels. In the beta (13-30 Hz) frequency band, the MI of the affected hand (Ahand) elicited a significantly lower smallworldness and local efficiency (Eloc) versus the unaffected hand (Uhand). Notably, the abnormal reduction in Eloc significantly depended on the increase in interhemispheric connectivity, which was in turn determined primarily by the rise in regional connectivity in the parieto-occipital sites of the affected hemisphere. Further, in contrast to the Uhand MI, in which significantly high connectivity was observed for the contralateral sensorimotor regions of the unaffected hemisphere, the regions that increased in connection during the Ahand MI lay in the frontal and parietal regions of the contralaterally affected hemisphere. Finally, the overall sensorimotor function of our patients, as measured by Fugl-Meyer Assessment (FMA) index, was significantly predicted by the connectivity of their affected hemisphere. These results increase our understanding of stroke-induced alterations in functional brain networks.Comment: Neuroimage, accepted manuscript (unedited version) available online 19-June-201

Altered resting-state network connectivity in stroke patients with and without apraxia of speech

Motor speech disorders, including apraxia of speech (AOS), account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS), inferior frontal gyrus (IFG), and ventral premotor cortex (PM)) in a group of 32 left hemisphere stroke patients and 18 healthy, age-matched controls. Two expert clinicians rated severity of AOS, dysarthria and nonverbal oral apraxia of the patients. Fifteen individuals were categorized as AOS and 17 were AOS-absent. Comparison of connectivity in patients with and without AOS demonstrated that AOS patients had reduced connectivity between bilateral PM, and this reduction correlated with the severity of AOS impairment. In addition, AOS patients had negative connectivity between the left PM and right aINS and this effect decreased with increasing severity of non-verbal oral apraxia. These results highlight left PM involvement in AOS, begin to differentiate its neural mechanisms from those of other motor impairments following stroke, and help inform us of the neural mechanisms driving differences in speech motor planning and programming impairment following stroke

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

Behavioral, computational, and neuroimaging studies of acquired apraxia of speech

A critical examination of speech motor control depends on an in-depth understanding of network connectivity associated with Brodmann areas 44 and 45 and surrounding cortices. Damage to these areas has been associated with two conditions-the speech motor programming disorder apraxia of speech (AOS) and the linguistic/grammatical disorder of Broca's aphasia. Here we focus on AOS, which is most commonly associated with damage to posterior Broca's area (BA) and adjacent cortex. We provide an overview of our own studies into the nature of AOS, including behavioral and neuroimaging methods, to explore components of the speech motor network that are associated with normal and disordered speech motor programming in AOS. Behavioral, neuroimaging, and computational modeling studies are indicating that AOS is associated with impairment in learning feedforward models and/or implementing feedback mechanisms and with the functional contribution of BA6. While functional connectivity methods are not yet routinely applied to the study of AOS, we highlight the need for focusing on the functional impact of localized lesions throughout the speech network, as well as larger scale comparative studies to distinguish the unique behavioral and neurological signature of AOS. By coupling these methods with neural network models, we have a powerful set of tools to improve our understanding of the neural mechanisms that underlie AOS, and speech production generally

DYNAMICS OF FUNCTIONAL CONNECTIVITY WITHIN CORTICAL MOTOR NETWORK DURING MOTOR LEARNING IN STROKE - CORRELATIONS WITH "TRUE" MOTOR RECOVERY

Arm motor recovery after stroke is usually incomplete; six months after onset about two-thirds of patients suffer from arm motor impairment that significantly impacts the individual's activities of daily living. Thus, novel concepts beyond current strategies for arm motor rehabilitation after stroke are needed. An essential approach for this is to better understand whether motor learning-related neural changes in stroke are similar with those in healthy controls and how these neural changes relate to recovery of the pre-morbid movement pattern or "true" recovery. Abnormal task-related activation in primary and non-primary motor cortices has been a consistent finding in functional MRI studies of stroke. Disturbed functional network architecture, e.g., the influence that one motor area exerts over another, also impacts stroke recovery. The outcome measures chosen to evaluate recovery are also important for the interpretation of these brain changes. Thus, the long-range goal of this work was to longitudinally investigate the changes in cortical motor function at two levels, regional (micro-circuitry, regional activation) and network (macro-circuitry, functional connectivity), following an arm-focused motor training in chronic stroke survivors and how these brain changes relate to recovery of the pre-morbid movement pattern or "true" recovery. In the Chapter I, we reviewed the literature concerning the pathophysiology of stroke, neural substrates of motor control, and motor learning principles and neural substrates in healthy and pathological (stroke) brain. In the Chapter II, we examined the relationships between task-related motor activation and clinical and kinematic metrics of arm motor impairment in survivors of subcortical stroke. We found evidence that primary motor activation was significantly correlated to kinematic metrics of arm motor impairment, but not with clinical metrics. In the Chapter III, we longitudinally investigated the regional changes in motor-related activation (functional MRI) in primary and non-primary motor areas following an arm-focused motor training in stroke survivors and age-sex matched healthy controls. We demonstrated that similar changes in the motor areas contralateral to the trained arm were found with training in both stroke and healthy participants. We also demonstrated a significant increase in motor performance in both groups as well as a normalization of the correlations between bilateral motor activation and movement kinematics in participants with stroke. In the Chapter IV, we also investigated the changes in functional connectivity between primary and non-primary motor areas following an arm-focused motor training and how these changes correlate with "true" motor recovery. We demonstrated significant enhanced functional connectivity in motor areas contralateral to the trained hand (or ipsilesional), although no "normalization" of the inter-hemispheric inhibition following training in our survivors. We also showed a "normalization" of the relationships between cortical motor functional connectivity and movement kinematics. In the Chapter V, we concluded that the present dissertation work support the hypotheses that motor system is plastic at different levels, regional and network, even in the chronic stage of stroke and some of these changes are similar with those reported in healthy controls. Further, these changes provide a substrate for "true" recovery. These findings promote the use of neuroimaging and kinematic metrics to improve our understanding of the neural substrates underlying reorganization in remaining intact brain structures after stroke. Such an approach may further enable monitoring recovery or compensation based on this reorganization and evaluating new treatment regimes that assist motor recovery