Biology subjects

Winstein, C. J.

Publications and source records attributed to Winstein, C. J..

6 recordsLinked to original sources

bioRxiv2024

Leg choice for volitional goal-directed stepping is primarily influenced by effort rather than success: A preliminary investigation in neurotypical adults

During reaching, arm choice depends on success and motor effort. Whether these factors influence leg choice for stepping behavior is unknown. Here, we conducted two experiments (1: proof-of-principle; 2: kinematic analysis) to explore whether limb selection for goal-directed stepping depends on success and/or effort under two Choice conditions: Free (choose either leg) and Constrained (no choice - only left leg). For both experiments, in which Free trials always preceded Constrained trials, we adapted the classic center-out target array in which right-leg dominant neurotypical adults stood in the middle of the array and stepped to pre-cued targets as accurately as possible. The Free condition reflected the preferred limb choice. We compared success, effort, and self-perceived difficulty between Free and Constrained trials, separately for three (Experiment 1) and two (Experiment 2) regions. Overall, in Free condition, participants uniformly selected the limb ipsilateral to lateral left and right targets and with slight leg dominance-based bias for central targets. Success (step accuracy and consistency/precision) did not depend on Choice condition, rather, performance improved over repeated trials. Effort (peak vertical foot lift and step path ratio) depended on Choice condition. Finally, independent of Choice condition, participants perceived posterior targets (particularly far targets) as the most difficult during non-dominant left steps. Present findings suggest that effort may influence leg choice to a greater degree than success for goal-directed stepping. Future work that probes these findings robustness in patients with unilateral paresis (intrinsic constraint) may advance our understanding of the motor decision processes for goal-directed mobility behaviors.

neuroscience↗

bioRxiv2023

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9{+/-}18.0 years; time since stroke 12.2{+/-}0.2 months; normalised motor score 0.7{+/-}0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

neuroscience↗

bioRxiv2023

Multi-site identification and generalization of clusters of walking impairment in individuals with chronic stroke

BackgroundWalking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. ObjectiveWe used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: 1) identify clusters of walking behaviors in people post-stroke and neurotypical controls, and 2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants. MethodsWe gathered data from 81 post-stroke participants across four research sites and collected data from 31 control participants. Using sparse K-means clustering, we identified walking clusters based on 17 spatiotemporal and force variables. We analyzed the biomechanical features within each cluster to characterize cluster-specific walking behaviors. We also assessed the generalizability of the clusters using a leave-one-out approach. ResultsWe identified four stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. ConclusionsAlthough post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.

neuroscience↗

bioRxiv2021

Corpus callosal microstructure predicts bimanual motor performance in chronic stroke survivors

AO_SCPLOWBSTRACTC_SCPLOWMicrostructural changes in the corpus callosum are associated with more severe motor impairment in the paretic hand, poor recovery, and general disability. Considering its role in bimanual coordination, we suspected that these microstructural changes across the callosum may also be reflected in the performance of ecologically valid routine bimanual tasks. Thus, the purpose of this study was to determine if callosal microstructure predicts bimanual motor performance in chronic stroke survivors by examining the regions of the corpus callosum connecting both the sensorimotor and non-sensorimotor cortices. We examined the relationship between the fractional anisotropy across the CC and movement times for two self-initiated and self-paced bimanual tasks in 41 chronic stroke survivors. Using publicly available control datasets (n = 52), matched closely for acquisition parameters, we also explored the effect of stroke and age on callosal microstructure. There were two main findings: First, callosal microstructure was significantly associated with bimanual performance in chronic stroke survivors. Notably, a significant relationship was observed not only with the primary sensorimotor regions, but also regions of the premotor/supplementary motor and prefrontal regions. Second, chronic stroke survivors presented with significantly lower mean FA, compared to neurologically intact adults. We conclude that in mild-to-moderate chronic stroke survivors with relatively localized lesions to the motor areas, callosal microstructure can be expected to change in not only the primary sensorimotor region, but also more anteriorly in the secondary motor regions and the genu and is associated with performance on cooperative bimanual tasks. SignificanceA goal of rehabilitation after stroke is to promote the return to pre-stroke levels of upper limb function and use, predominantly characterized by coordinated bimanual activities. In this study, we find that in the chronic phase of stroke, microstructural disorganization within the corpus callosum predicts motor performance on real-world bimanual tasks and lends important insight into the indirect, remote effects of stroke. HO_SCPLOWIGHLIGHTSC_SCPLOWO_LIWe provide initial evidence that corpus callosal microstructure predicts performance on two self-initiated and self-paced bimanual tasks. C_LIO_LIAssociations were strongest for fibers connecting the primary sensorimotor cortices followed by the pre- and supplementary motor, and prefrontal cortices. C_LIO_LISignificant reductions in fractional anisotropy were observed in stroke survivors for all regions of the corpus callosum. C_LI

neuroscience↗

bioRxiv2020

The Efficiency, Efficacy, and Retention of Motor Training in Chronic Stroke

In motor skill learning, the greater the dose of training, the greater the efficacy of training, the lower the efficiency of training, and the better the long-term retention. Whether such principles apply to motor training after stroke is unclear. Here, we developed novel mixed-effects models of the change in the quality of arm movements during and following training fitted to data from a recent randomized controlled trial of the effect of the dose of training in chronic stroke. Analysis of the models learning and retention rates demonstrated an increase in efficacy of training with greater doses, a decrease in efficiency of training with both additional doses and additional bouts of training, and fast initial decay following training. Two additional effects modulated retention: a positive "self-training" effect, and an un-expected negative effect of dose. Our results suggest that for patients with sufficient arm use post-training, self-training will further improve use, but additional therapy may be in vain.

neuroscience↗

bioRxiv2019

Relationship Between Motor Capacity of the Contralesional and Ipsilesional Hand Depends on the Side of Stroke

There is considerable evidence that after a stroke, ipsilesional deficits increase as contralesional impairment increases. Here, we asked if the relationship between the motor capacities of the two limbs differs based on the side of stroke. Forty-two pre-morbidly right-handed chronic stroke survivors (left hemisphere damage, LHD = 21) with mild-to-moderate paresis performed distal items of the Wolf Motor Function Test (dWMFT). We found that compared to RHD, the relationship between contralesional arm impairment (Upper Extremity Fugl-Meyer, UEFM) and ipsilesional hand motor capacity was stronger (R2LHD= 0.42; R2RHD < 0.01; z = 2.12; p = 0.03) and the slope was steeper (t = -2.03; p = 0.04) in LHD. Similarly, the relationship between contralesional dWMFT and ipsilesional hand motor capacity was stronger (R2LHD= 0.65; R2RHD= 0.09; z = 2.45; p = 0.01) and the slope was steeper (t = 2.03; p = 0.04) in LHD compared to RHD. Multiple regression analysis confirmed the presence of an interaction between contralesional UEFM and side of stroke ({beta}3= 0.66 {+/-} 0.30; p = 0.024) but only trended towards significance for the interaction between contralesional dWMFT and side of stroke ({beta}3= -0.51 {+/-} 0.34; p = 0.05). Results were confirmed after removal of potential outliers. Our findings suggest that the relationship between contra- and ipsi-lesional motor capacity depends on the side of stroke, such that the inter-limb relationship is stronger for stroke survivors with left hemisphere damage compared to those with right hemisphere damage.

neuroscience↗