James H. Cauraugh

Artificial intelligence and stroke are an intriguing union with vast improvements in health benefits anticipated. Impactful artificial intelligence contributions are emerging in stroke diagnosis, rehabilitation protocols, and movement activity monitoring. Identifying stroke locations via magnetic renounce images will shorten the time delay post stroke and minimize the effects of the disrupted blood flow in the brain. Insightful rehabilitation protocols will be evidence-based as well as prescribed for specific individuals post stroke. Machine learning, immersive virtual reality, and deep learning will further substantiate the importance of voluntary movements as the basis for neural plasticity post stroke.

Two popular chronic stroke rehabilitation protocols are robotic-assisted movements and transcranial direct current stimulation (tDCS). Separately, both protocols have produced encouraging motor recovery improvements. An intriguing question remains: what happens to motor recovery when both protocols are administered together? Do the two protocols together produce additive dual effects? This systematic review and meta-analysis investigated the dual effect of combining robotic training and tDCS. We investigated the potential effects of tDCS protocols in addition to robotic-training programs on motor recovery of the upper and lower extremities post-stroke. A systematic literature search identified 20 qualified studies that used robotic training combined with tDCS protocols for upper limb (i.e., 15 studies) and lower limb (i.e., 5 studies) post-stroke rehabilitation. Individuals in the subacute and chronic stages of recovery were investigated. The 20 included studies compared additive effects of the combined protocols with robotic training sham control groups. Further, we estimated short-term and long-term treatment effects of the combined protocols. The random-effects model meta-analyses failed to find any significant short-term and long-term motor improvements in the upper extremities after the combined treatments. However, robotic-assisted movements combined with tDCS protocols revealed significant moderate transient and sustained improvements in functions of the lower limbs post-stroke. These meta-analytic findings suggest clinical implications concerning coupled top-down and bottom-up training protocols (i.e., robotic training and tDCS combined), which will allow us to make progress toward post-stroke motor recovery.

This updated systematic review and meta-analysis further examined potential effects of aging on bimanual movements. Forty-seven qualified studies that compared bimanual motor performances between elderly and younger adults were included in this meta-analysis. Moderator variable analyses additionally determined whether altered bimanual motor performances in older adults were different based on the task types (i.e., symmetry vs. asymmetry vs. complex) or outcome measures (i.e., accuracy vs. variability vs. movement time). The random effects model meta-analysis on 80 comparisons from 47 included studies revealed significant negative overall effects indicating more bimanual movement impairments in the elderly adults than younger adults. Moderator variable analyses found that older adults showed more deficits in asymmetrical bimanual movement tasks than symmetrical and complex tasks, and the bimanual movement impairments in the elderly adults included less accurate, more variable, and greater movement execution time than younger adults. These findings suggest that rehabilitation programs for improving motor actions in older adults are necessary to focus on functional recovery of interlimb motor control including advanced motor performances as well coordination.

Executing voluntary motor actions in the upper extremities after a stroke is frequently challenging and frustrating. Although spontaneous motor recovery can occur, reorganizing the activation of the primary motor cortex and supplementary motor area takes a considerable amount of time involving effective rehabilitation interventions. Based on motor control theory and experience-dependent neural plasticity, stroke protocols centered on bimanual movement coordination are generating considerable evidence in overcoming dysfunctional movements. Looking backward and forward in this comprehensive review, we discuss noteworthy upper extremity improvements reported in bimanual movement coordination studies including force generation. Importantly, the effectiveness of chronic stroke rehabilitation approaches that involve voluntary interlimb coordination principles look promising.

In the original article [1], we mentioned that some study characteristics of the article by Dagan and colleagues [2] were unavailable.

Background: Ageing may cause impairments in executing bilateral movement control. This study investigated age-related changes in interlimb force coordination across multiple trials by quantifying bilateral motor synergies based on the uncontrolled manifold hypothesis. Participants completed the trials with and without visual feedback. Methods: Twenty healthy individuals (10 older adults and 10 young adults) performed 12 isometric force control trials for the two vision conditions at 5% of maximal voluntary contraction. All dependent variables were analyzed in two-way mixed model (Group × Vision Condition; 2 × 2) ANOVAs with repeated measures on the last factor. Results: The analyses revealed that older adults had greater mean force produced by two hands in both vision conditions (i.e., yes and no visual feedback). Across both vision conditions, the older adult group showed greater asymmetrical force variability (i.e., standard deviation of non-dominant hand > standard deviation of dominant hand) and revealed more positive correlation coefficients between forces produced by two hands as compared with the young adult group. Finally, an index of bilateral motor synergies was significantly greater in young adults than older adults when visual feedback was available. Conclusion: The current findings indicate that deficits in interlimb force coordination across multiple trials appeared in older adults.

The purpose of this meta-analysis was to investigate the treatment effects of transcranial direct current stimulation (tDCS) on functional locomotion in people with Parkinson’s disease (PD). A systematic literature search identified 18 qualified studies that used tDCS protocols as functional locomotion rehabilitation interventions for people with PD. All included studies used either a randomized control trial or crossover designs with a sham control group. Meta-analysis quantified both (a) short-term treatment effects: change in functional locomotion between baseline and immediate posttests on 18 comparisons and (b) long-term treatment effects: change in functional locomotion between baseline and delayed retention tests on six comparisons. Moreover, we performed moderator variable analyses for comparing effect sizes between tDCS targeting multiple brain regions and tDCS targeting a single brain region. Random effects model meta-analyses revealed a significant short-term treatment effect (effect size = 0.359; P = 0.001), whereas no significant long-term treatment effects were identified (effect size = 0.164; P = 0.314). In addition, tDCS protocols that targeted multiple brain regions showed relatively more positive effects on functional locomotion than protocols that targeted a single brain region. These meta-analytic findings indicate that tDCS protocols may show immediate positive effects on functional locomotion in people with PD. However, given the relatively low effect size, exploring more appropriate tDCS protocols (i.e., targeting multiple motor and prefrontal regions and medication condition) should be a focus in future studies.