Ng, Tommy Hock Beng

Non-proficient demonstration, gross motor skill assessment, and subjective feedback are but a few of the perennial problems in physical education (PE). These problems stand to benefit from a technology-based solution that uses human pose estimation to guide learning. In this approach, a criterion motor action is embedded in a deep-learning algorithm (DLA). A learner can view this motor action on an iPad and uses its kinematic signatures to guide practice. The learner’s movement is captured by the device and the recorded motor action enters the DLA for computation of movement proficiency. The output of the DLA is a quantitative index that informs the learner how well the movement has been executed. In this way, the learner gains timely and objective feedback. A separate device held by the PE teacher collates the quantitative indices from other students in the class. Collectively, the information facilitates the teacher’s selection of instructional strategies.

Current literature lacks consolidated evidence for the impact of stimulation parameters on the effects of transcranial direct current stimulation (tDCS) in enhancing upper limb motor learning. Hence, we aim to synthesise available methodologies and results to guide future research on the usage of tDCS on upper limb motor learning, specifically in older adults and Parkinson’s disease (PD). Thirty-two studies (Healthy older adults, N = 526, M = 67.25, SD = 4.30 years; PD, N = 216, M = 66.62, SD = 6.25 years) were included in the meta-analysis. All included studies consisted of active and sham protocols. Random effect meta-analyses were conducted for (i) subjects (healthy older adults and PD); (ii) intensity (1.0, 1.5, 2 mA); (iii) electrode montage (unilateral anodal, bilateral anodal, unilateral cathodal); (iv) stimulation site (cerebellum, frontal, motor, premotor, SMA, somatosensory); (v) protocol (online, offline). Significant tDCS effect on motor learning was reported for both populations, intensity 1.0 and 2.0 mA, unilateral anodal and cathodal stimulation, stimulation site of the motor and premotor cortex, and both online and offline protocols. Regression showed no significant relationship between tDCS effects and density. The efficacy of tDCS is also not affected by the number of sessions. However, studies that reported only single session tDCS found significant negative association between duration with motor learning outcomes. Our findings suggest that different stimulation parameters enhanced upper limb motor learning in older adults and PD. Future research should combine tDCS with neuroimaging techniques to help with optimisation of the stimulation parameters, considering the type of task and population.

An increasing body of evidence points to the involvement of the cerebellum in cognition. Specifically, previous studies have shown that the superior and inferior portions of the cerebellum are involved in different verbal working memory (WM) mechanisms as part of two separate cerebro-cerebellar loops for articulatory rehearsal and phonological storage mechanisms. In comparison, our understanding of the involvement of the cerebellum in visual WM remains limited. We have previously shown that performance in verbal WM is disrupted by single-pulse transcranial magnetic stimulation (TMS) of the right superior cerebellum. The present study aimed to expand on this notion by exploring whether the inferior cerebellum is similarly involved in visual WM. Here, we used fMRI-guided, double-pulse TMS to probe the necessity of left superior and left inferior cerebellum in visual WM. We first conducted an fMRI localizer using the Sternberg visual WM task, which yielded targets in left superior and inferior cerebellum. Subsequently, TMS stimulation of these regions at the end of the encoding phase resulted in decreased accuracy in the visual WM task. Differences in the visual WM deficits caused by stimulation of superior and inferior left cerebellum raise the possibility that these regions are involved in different stages of visual WM.