Katie P. Wadden

Establishing the reproducibility of two approaches to quantify white matter tract integrity in stroke

Diffusion tensor imaging can provide unique and detailed information about white matter anatomy following stroke. Fiber tract reconstruction using tract-based techniques and cross-sectional region of interest delineation are two common approaches to quantify white matter integrity. After stroke, white matter tract integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption is associated with degree of functional impairment and response to skill training in participants with stroke. However, the reliability and validity of these approaches has not been systematically evaluated nor have the two approaches been directly compared in individuals with chronic stroke. Ten well-recovered individuals with chronic, right-sided, ischemic stroke in the sub-cortex and ten age-, gender- and handedness-matched healthy participants were studied. Semi-automated tractography of the ipsi- and contralesional corticospinal tract and cross-sectional region of interest drawing of the posterior limb of the internal capsule were performed bilaterally. Fractional anisotropy (FA) values and the hemispheric asymmetry in FA were the primary measures of tract integrity. Two raters performed each analysis method twice to evaluate inter- and intra-rater reliability. Participants with stroke were compared to healthy individuals to determine validity of each analysis approach. Correlational analyses were conducted to examine the relationships between the two approaches and the association between approaches and upper extremity motor impairment. Both analyses methods generally demonstrated good to excellent intra- and inter-rater reliability in each group (p<0.05). Stroke participants demonstrated lower mean FA values in both ipsi- and contralesional tract integrity, and larger FA hemispheric asymmetry as compared with healthy individuals (p<0.05). Comparison between the analysis approaches revealed significant associations between approaches across both groups and within each group (p<0.05). In stroke, individual tract integrity was not correlated between approaches for ipsilesional (r=0.26) or contralesional (0.15) tracts, nor was FA hemispheric asymmetry (r=0.18). Additionally, contralesional mean FA quantified with the cross-sectional approach correlated with upper extremity motor impairment (r=0.69). Importantly, this study is the first to systematically characterize the reliability of tract-based and cross-sectional DTI analysis approaches in well-recovered individuals with chronic stroke and matched healthy participants. Results suggest both tract-based and cross-sectional approaches to evaluate white matter tract integrity are reliable, can differentiate between groups of stroke and healthy participants, and are associated with one another. However, only mean FA values for the contralesional side derived using the cross-sectional approach were related to upper extremity impairment. Our findings suggest that each approach provides complimentary rather than redundant information regarding integrity and support the use of both approaches in combination in future investigations in well-recovered individuals with stroke.

Diffusion imaging and transcranial magnetic stimulation assessment of transcallosal pathways in chronic stroke

OBJECTIVE To examine the relationship of transcallosal pathway microstructure and transcallosal inhibition (TCI) with motor function and impairment in chronic stroke. METHODS Diffusion-weighted magnetic resonance imaging and transcranial magnetic stimulation (TMS) data were collected from 24 participants with chronic stroke and 11 healthy older individuals. Post-stroke motor function (Wolf Motor Function Test) and level of motor impairment (Fugl-Meyer score) were evaluated. RESULTS Fractional anisotropy (FA) of transcallosal tracts between prefrontal cortices and the mean amplitude decrease in muscle activity during the ipsilateral silent period evoked by TMS over the non-lesioned hemisphere (termed NL-iSPmean) were significantly associated with level of motor impairment and motor function after stroke (p<0.05). A regression model including age, post-stroke duration, lesion volume, lesioned corticospinal tract FA, transcallosal prefrontal tract FA and NL-iSPmean accounted for 84% of variance in motor impairment (p<0.01). Both transcallosal prefrontal tract FA (ΔR(2)=0.12, p=0.04) and NL-iSPmean (ΔR(2)=0.09, p=0.04) accounted for unique variance in motor impairment level. CONCLUSIONS Prefrontal transcallosal tract microstructure and TCI are each uniquely associated with motor impairment in chronic stroke. SIGNIFICANCE Utilizing a multi-modal approach to assess transcallosal pathways may improve our capacity to identify important neural substrates of motor impairment in the chronic phase of stroke.

Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke.

Diffusion tensor imaging (DTI)-based tractography has been used to demonstrate functionally relevant differences in white matter pathway status after stroke. However, it is now known that the tensor model is insensitive to the complex fiber architectures found in the vast majority of voxels in the human brain. The inability to resolve intra-voxel fiber orientations may have important implications for the utility of standard DTI-based tract reconstruction methods. Intra-voxel fiber orientations can now be identified using novel, tensor-free approaches. Constrained spherical deconvolution (CSD) is one approach to characterize intra-voxel diffusion behavior. In the current study, we performed DTI- and CSD-based tract reconstruction of the corticospinal tract (CST) and corpus callosum (CC) to test the hypothesis that characterization of complex fiber orientations may improve the robustness of fiber tract reconstruction and increase the sensitivity to identify functionally relevant white matter abnormalities in individuals with chronic stroke. Diffusion weighted magnetic resonance imaging was performed in 27 chronic post-stroke participants and 12 healthy controls. Transcallosal pathways and the CST bilaterally were reconstructed using DTI- and CSD-based tractography. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD) were calculated across the tracts of interest. The total number and volume of reconstructed tracts was also determined. Diffusion measures were compared between groups (Stroke, Control) and methods (CSD, DTI). The relationship between post-stroke motor behavior and diffusion measures was evaluated. Overall, CSD methods identified more tracts than the DTI-based approach for both CC and CST pathways. Mean FA, ADC, and RD differed between DTI and CSD for CC-mediated tracts. In these tracts, we discovered a difference in FA for the CC between stroke and healthy control groups using CSD but not DTI. CSD identified ipsilesional CST pathways in 9 stroke participants who did not have tracts identified with DTI. Additionally, CSD differentiated between stroke ipsilesional and healthy control non-dominant CST for several measures (number of tracts, tract volume, FA, ADC, and RD) whereas DTI only detected group differences for number of tracts. In the stroke group, motor behavior correlated with fewer diffusion metrics derived from the DTI as compared to CSD-reconstructed ipsilesional CST and CC. CSD is superior to DTI-based tractography in detecting differences in diffusion characteristics between the nondominant healthy control and ipsilesional CST. CSD measures of microstructure tissue properties related to more motor outcomes than DTI measures did. Our results suggest the potential utility and functional relevance of characterizing complex fiber organization using tensor-free diffusion modeling approaches to investigate white matter pathways in the brain after stroke.

Multiple measures of corticospinal excitability are associated with clinical features of multiple sclerosis

In individuals with multiple sclerosis (MS), transcranial magnetic stimulation (TMS) may be employed to assess the integrity of corticospinal system and provides a potential surrogate biomarker of disability. The purpose of this study was to provide a comprehensive examination of the relationship between multiple measures corticospinal excitability and clinical disability in MS (expanded disability status scale (EDSS)). Bilateral corticospinal excitability was assessed using motor evoked potential (MEP) input-output (IO) curves, cortical silent period (CSP), short-interval intracortical inhibition (SICI), intracortical facilitation (ICF) and transcallosal inhibition (TCI) in 26 individuals with MS and 11 healthy controls. Measures of corticospinal excitability were compared between individuals with MS and controls. We evaluated the relationship(s) between age and clinical demographics such as age at MS onset (AO), disease duration (DD) and clinical disability (EDSS) with measures of corticospinal excitability. Corticospinal excitability thresholds were higher, MEP latency and CSP onset delayed and MEP durations prolonged in individuals with MS compared to controls. Age, DD and EDSS correlated with corticospinal excitability thresholds. Also, TCI duration and the linear slope of the MEP amplitude IO curve correlated with EDSS. Hierarchical regression modeling demonstrated that combining multiple TMS-based measures of corticospinal excitability accounted for unique variance in clinical disability (EDSS) beyond that of clinical demographics (AO, DD). Our results indicate that multiple TMS-based measures of corticospinal and interhemispheric excitability provide insights into the potential neural mechanisms associated with clinical disability in MS. These findings may aid in the clinical evaluation, disease monitoring and prediction of disability in MS.

Motor Skill Acquisition Promotes Human Brain Myelin Plasticity

Experience-dependent structural changes are widely evident in gray matter. Using diffusion weighted imaging (DWI), the neuroplastic effect of motor training on white matter in the brain has been demonstrated. However, in humans it is not known whether specific features of white matter relate to motor skill acquisition or if these structural changes are associated to functional network connectivity. Myelin can be objectively quantified in vivo and used to index specific experience-dependent change. In the current study, seventeen healthy young adults completed ten sessions of visuomotor skill training (10,000 total movements) using the right arm. Multicomponent relaxation imaging was performed before and after training. Significant increases in myelin water fraction, a quantitative measure of myelin, were observed in task dependent brain regions (left intraparietal sulcus [IPS] and left parieto-occipital sulcus). In addition, the rate of motor skill acquisition and overall change in myelin water fraction in the left IPS were negatively related, suggesting that a slower rate of learning resulted in greater neuroplastic change. This study provides the first evidence for experience-dependent changes in myelin that are associated with changes in skilled movements in healthy young adults.

Correlations between brain activity and components of motor learning in middle-aged adults: an fMRI study

Implicit learning may be shown by improvements in motor performance, which occur unconsciously with practice and are typically restricted to the task that was practiced. The purpose of this study was to examine behaviorally relevant brain activation associated with change in motor behavior during sequence-specific motor learning of a perceptuomotor continuous tracking (CT) task in middle-aged adults. To gain further insight into the neural structures associated with change in motor behavior, overall improvement in tracking (root mean square error; RMSE) was decomposed into two components—temporal precision and spatial accuracy. We hypothesized that individual differences in CT task performance would be evident in unique networks of brain activation that supported overall tracking behavior as well-temporal and spatial tracking accuracy. A group of middle-aged healthy individuals performed the CT task, which contains repeated and random segments for seven days. Functional magnetic resonance imaging (fMRI) data was collected on the first and seventh day while the participants performed the task. Subjects did not gain explicit awareness of the sequence. To assess behaviorally-relevant changes in the blood oxygenation level-dependent (BOLD) response associated with individual sequence-specific tracking performance, separate statistical images were created for each participant and weighted by the difference score between repeated and random performance for days 1 and 7. Given the similarity of performance for random and repeated sequences during early practice, there were no unique networks evident at day 1. On Day 7 the resultant group statistical fMRI image demonstrated a positive correlation between RMSE difference score and bilateral cerebellar activation (lobule VI). In addition, individuals who showed greater sequence-specific temporal precision demonstrated increased activation in the precentral gyrus, middle occipital gyrus, and putamen of the right hemisphere and the thalamus, cuneus, and cerebellum of the left hemisphere. Activation of this neural network further confirms its involvement in timing of movements as it has been previously associated with task performance when individuals are instructed to emphasize speed over accuracy. In the present study, behavioral performance was associated with neural correlates of individual variation in motor learning that characterized the ability to implicitly learn a sequence-specific CT task.

Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke.

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke.

Predicting Motor Sequence Learning in Individuals With Chronic Stroke

Background. Conventionally, change in motor performance is quantified with discrete measures of behavior taken pre- and postpractice. As a high degree of movement variability exists in motor performance after stroke, pre- and posttesting of motor skill may lack sensitivity to predict potential for motor recovery. Objective. Evaluate the use of predictive models of motor learning based on individual performance curves and clinical characteristics of motor function in individuals with stroke. Methods. Ten healthy and fourteen individuals with chronic stroke performed a continuous joystick-based tracking task over 6 days, and at a 24-hour delayed retention test, to assess implicit motor sequence learning. Results. Individuals with chronic stroke demonstrated significantly slower rates of improvements in implicit sequence-specific motor performance compared with a healthy control (HC) group when root mean squared error performance data were fit to an exponential function. The HC group showed a positive relationship between a faster rate of change in implicit sequence-specific motor performance during practice and superior performance at the delayed retention test. The same relationship was shown for individuals with stroke only after accounting for overall motor function by including Wolf Motor Function Test rate in our model. Conclusion. Nonlinear information extracted from multiple time points across practice, specifically the rate of motor skill acquisition during practice, relates strongly with changes in motor behavior at the retention test following practice and could be used to predict optimal doses of practice on an individual basis.

Interhemispheric Pathways Are Important for Motor Outcome in Individuals with Chronic and Severe Upper Limb Impairment Post Stroke

Background Severity of arm impairment alone does not explain motor outcomes in people with severe impairment post stroke. Objective Define the contribution of brain biomarkers to upper limb motor outcomes in people with severe arm impairment post stroke. Methods Paretic arm impairment (Fugl-Meyer upper limb, FM-UL) and function (Wolf Motor Function Test rate, WMFT-rate) were measured in 15 individuals with severe (FM-UL ≤ 30/66) and 14 with mild–moderate (FM-UL > 40/66) impairment. Transcranial magnetic stimulation and diffusion weight imaging indexed structure and function of the corticospinal tract and corpus callosum. Separate models of the relationship between possible biomarkers and motor outcomes at a single chronic (≥6 months) time point post stroke were performed. Results Age (ΔR20.365, p = 0.017) and ipsilesional-transcallosal inhibition (ΔR20.182, p = 0.048) explained a 54.7% (p = 0.009) variance in paretic WMFT-rate. Prefrontal corpus callous fractional anisotropy (PF-CC FA) alone explained 49.3% (p = 0.007) variance in FM-UL outcome. The same models did not explain significant variance in mild–moderate stroke. In the severe group, k-means cluster analysis of PF-CC FA distinguished two subgroups, separated by a clinically meaningful and significant difference in motor impairment (p = 0.049) and function (p = 0.006) outcomes. Conclusion Corpus callosum function and structure were identified as possible biomarkers of motor outcome in people with chronic and severe arm impairment.

A structural motor network correlates with motor function and not impairment post stroke.

Combining structural and functional magnetic resonance imaging may provide insight into how residual motor networks contribute to motor outcomes post-stroke. The purpose of this study was to examine whether a structural motor network (SMN), generated with fMRI guided diffusion-based tractography, relates to motor function post-stroke. Twenty-seven individuals with mild to moderate upper limb impairment post stroke underwent diffusion magnetic resonance imaging. A bilateral motor network mask guided white matter tractography for each participant. Fractional anisotrophy (FA) was calculated for the SMN and corticospinal tracts (CST). The Wolf Motor Function Test (WMFT) rate and Fugl-Meyer Upper Limb (FM) tests characterized arm function and impairment respectively. The SMN and ipsilesional CST together explained approximately 35% of the variance in paretic arm function (WMFT-rate p=0.006). This study demonstrates that a broader motor network, like the SMN, is functionally meaningful. Given that the motor network is widely distributed, the proposed SMN warrants further investigation as a potential adjunct biomarker to characterize recovery potential after stroke.