A Review of Transcranial Magnetic Stimulation and Multimodal Neuroimaging to Characterize Post-Stroke Neuroplasticity

Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted

A multimodal approach to understanding motor impairment and disability 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. © 2014 Springer-Verlag Berlin Heidelberg

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

Involvement of White Matter Language Tracts in Glioma: Clinical Implications, Operative Management, and Functional Recovery After Injury

To achieve optimal survival and quality of life outcomes in patients with glioma, the extent of tumor resection must be maximized without causing injury to eloquent structures. Preservation of language function is of particular importance to patients and requires careful mapping to reveal the locations of cortical language hubs and their structural and functional connections. Within this language network, accurate mapping of eloquent white matter tracts is critical, given the high risk of permanent neurological impairment if they are injured during surgery. In this review, we start by describing the clinical implications of gliomas involving white matter language tracts. Next, we highlight the advantages and limitations of methods commonly used to identify these tracts during surgery including structural imaging techniques, functional imaging, non-invasive stimulation, and finally, awake craniotomy. We provide a rationale for combining these complementary techniques as part of a multimodal mapping paradigm to optimize postoperative language outcomes. Next, we review local and long-range adaptations that take place as the language network undergoes remodeling after tumor growth and surgical resection. We discuss the probable cellular mechanisms underlying this plasticity with emphasis on the white matter, which until recently was thought to have a limited role in adults. Finally, we provide an overview of emerging developments in targeting the glioma-neuronal network interface to achieve better disease control and promote recovery after injury

Structural connectivity analyses in motor recovery research after stroke

Structural connectivity analyses by means of diffusion-weighted imaging have substantially advanced the understanding of stroke-related network alterations and their implications for motor recovery processes and residual motor function. Analyses of the corticospinal tract, alternate corticofugal pathways as well as intrahemispheric and interhemispheric corticocortical connections have not only been related to residual motor function in cross-sectional studies, but have also been evaluated to predict functional recovery after stroke in longitudinal studies. This review will consist of an update on the available literature about structural connectivity analyses after ischemic motor stroke, followed by an outlook of possible future directions of research and applications

Prognostic value of cortically induced motor evoked activity by TMS in chronic stroke: caveats from a very revealing single clinical case

Background: We report the case of a chronic stroke patient (62 months after injury) showing total absence of motor activity evoked by transcranial magnetic stimulation (TMS) of spared regions of the left motor cortex, but near-to-complete recovery of motor abilities in the affected hand. Case presentation: Multimodal investigations included detailed TMS based motor mapping, motor evoked potentials (MEP), and Cortical Silent period (CSP) as well as functional magnetic resonance imaging (fMRI) of motor activity, MRI based lesion analysis and Diffusion Tensor Imaging (DTI) Tractography of corticospinal tract (CST). Anatomical analysis revealed a left hemisphere subinsular lesion interrupting the descending left CST at the level of the internal capsule. The absence of MEPs after intense TMS pulses to the ipsilesional M1, and the reversible suppression of ongoing electromyographic (EMG) activity (indexed by CSP) demonstrate a weak modulation of subcortical systems by the ipsilesional left frontal cortex, but an inability to induce efficient descending volleys from those cortical locations to right hand and forearm muscles. Functional MRI recordings under grasping and finger tapping patterns involving the affected hand showed slight signs of subcortical recruitment, as compared to the unaffected hand and hemisphere, as well as the expected cortical activations. Conclusions: The potential sources of motor voluntary activity for the affected hand in absence of MEPs are discussed. We conclude that multimodal analysis may contribute to a more accurate prognosis of stroke patients

Neuroimaging predictors and biomarkers of rehabilitation gains after stroke

Stroke is a leading cause of long-term adult disability and many therapies are under study aiming to improve post-stroke motor function. Unfortunately, patient response to therapy is highly variable and the reasons for this are unknown. Clinical assessments are typically used to guide therapeutic decision-making after stroke. However, neuroimaging research over the last 15 years suggests that probes of neural injury and neural function provide crucial insight into post-stroke motor status. Limited research has examined how such measures could predict the likelihood of therapy-induced motor recovery and serve as biomarkers of treatment gains. Therefore, the current dissertation examined several neuroimaging measures of neural injury and neural function, as well as clinical and demographic variables, to 1) characterize our patient sample and understand the factors related to pre-therapy motor impairment and disability; 2) identify predictors of motor gains from a 3-week course of robotic arm therapy; and 3) elucidate potential biomarkers of motor gains from therapy. At baseline, reduced corticospinal tract (CST) integrity and neurophysiology (no motor evoked potential from transcranial magnetic stimulation) were correlated with greater pre-therapy motor impairment. Among less impaired patients, greater contralesional primary motor cortex (M1) and dorsal premotor cortex (PMd) activation correlated with greater motor impairment. The factors related to greater disability were reduced CST integrity and poorer cognitive status. The baseline measures predictive of greater motor gains from therapy were smaller CST injury (CST-lesion overlap) and greater interhemispheric functional connectivity. A notable finding was that predictors of gains varied according to lacunar stroke subtype: greater ipsilesional M1 activation and intrahemispheric functional connectivity predicted larger motor gains. Lastly, functional connectivity measures proved stronger biomarker candidates of treatment gains than changes in regional measures of motor cortex activation or an exploratory susceptibility-weighted imaging measure of peri-infarct tissue perfusion/angiogenesis. Furthermore, biomarkers differed according to stroke severity. Among less impaired patients, reductions in intra- and interhemispheric functional connectivity with therapy correlated with greater motor gains whereas in more impaired patients decreases in interhemispheric functional connectivity correlated with smaller gains. The current findings illustrate that measures of neural injury and neural function provide great insight into motor status after stroke, the likelihood of gains from therapy, and the heterogeneity of patient response to therapy. Ultimately, these measures should be incorporated into clinical trials of restorative stroke therapies to stratify patients to appropriate therapies and guide therapeutic decision-making for maximal patient gains

White Matter Integrity as a Biomarker for Stroke Recovery: Implications for TMS Treatment

White matter consists of myelinated axons which integrate information across remote brain regions. Following stroke white matter integrity is often compromised leading to functional impairment and disability. Despite its prevalence among stroke patients the role of white matter in development of post-stroke rehabilitation has been largely ignored. Rehabilitation interventions like repetitive transcranial magnetic stimulation (rTMS) are promising but reports on its efficacy have been conflicting. By understanding the role of white matter integrity in post-stroke motor recovery, brain reorganization and TMS efficacy we may be able to improve the development of future interventions. In this dissertation we set out answer these questions by investigating the relationship between white matter integrity and 1) bimanual motor performance following stroke, 2) cortical laterality following stroke and 3) TMS signal propagation (in a group of cocaine users without stroke). We identified white matter integrity of the corpus callosum as a key structure influencing bimanual performance using kinematic measures of hand symmetry (Chapter 2). Second, we found that reduced white matter integrity of corpus callosum was correlated with loss of functional laterality of the primary motor cortex during movement of the affected hand (Chapter 3). Lastly, we found that reduced white matter tract integrity from the site of stimulation to a downstream subcortical target, was correlated to the ability to modulate that target (Chapter 4). Taken together these studies support white matter integrity as a valuable biomarker for future rTMS trials in stroke. To emphasize the implications of these findings, we provide an example of how to incorporate white matter integrity at multiple levels of rTMS study design