Motion state-dependent motor learning based on explicit visual feedback is quickly recalled, but is less stable than adaptation to physical perturbations

Neural Underpinnings of Learning in Dementia Populations: A Review of Motor Learning Studies Combined with Neuroimaging

The intent of this review article is to serve as an overview of current research regarding the neural characteristics of motor learning in Alzheimer disease (AD) as well as prodromal phases of AD: at-risk populations, and mild cognitive impairment. This review seeks to provide a cognitive framework to compare various motor tasks. We will highlight the neural characteristics related to cognitive domains that, through imaging, display functional or structural changes because of AD progression. In turn, this motivates the use of motor learning paradigms as possible screening techniques for AD and will build upon our current understanding of learning abilities in AD populations.

Motion state-dependent motor learning based on explicit visual feedback has limited spatiotemporal properties compared with adaptation to physical perturbations

We recently showed that subjects can learn motion state-dependent changes to motor output (temporal force patterns) based on explicit visual feedback of the equivalent force field (i.e., without the physical perturbation). Here, we examined the spatiotemporal properties of this learning compared with learning based on physical perturbations. There were two human subject groups and two experimental paradigms. One group (n = 40) experienced physical perturbations (i.e., a velocity-dependent force field, vFF), whereas the second (n = 40) was given explicit visual feedback (EVF) of the force-velocity relationship. In the latter, subjects moved in force channels and we provided visual feedback of the lateral force exerted during the movement, as well as the required force pattern based on movement velocity. In the first paradigm (spatial generalization), following vFF or EVF training, generalization of learning was tested by requiring subjects to move to 14 untrained target locations (0° to ±135° around the trained location). In the second paradigm (temporal stability), following training, we examined the decay of learning over eight delay periods (0 to 90 s). Results showed that learning based on EVF did not generalize to untrained directions, whereas the generalization for the vFF was significant for targets ≤ 45° away. In addition, the decay of learning for the EVF group was significantly faster than the FF group (a time constant of 2.72 ± 1.74 s vs. 12.53 ± 11.83 s). Collectively, our results suggest that recalibrating motor output based on explicit motion state information, in contrast to physical disturbances, uses learning mechanisms with limited spatiotemporal properties.NEW & NOTEWORTHY Adjustment of motor output based on limb motion state information can be achieved based on explicit information or from physical perturbations. Here, we investigated the spatiotemporal characteristics of short-term motor learning to determine the properties of the respective learning mechanisms. Our results suggest that adjustments based on physical perturbations are more temporally stable and applied over a greater spatial range than the learning based on explicit visual feedback, suggesting largely separate learning mechanisms.

Effects of transcranial alternating current stimulation on motor performance and motor learning for healthy individuals: A systematic review and meta-analysis

Objective:Previous behavioral studies have reported the potential of transcranial alternating current stimulation in analyzing the causal relationship between neural activity and behavior. However, the efficacy of tACS on motor performance and learning in healthy individuals remains unclear. This systematic reviewexamines the effectiveness of tACS on motor performance and motor learning in healthy individuals. Methods: Literature was systematically searched through the Cochrane Library, PubMed, EMBASE, and Web of Science until 16 October 2022. Studies were eligible for review if they were randomized, parallel, or crossover experimental designs and reported the efficacy of tACS on motor performance and motor learning in healthy adults. Review Manager 5.3 was used to evaluate the methodological quality and analyze the combined effect. Results: Ten studies (270 participants) met all the inclusion criteria. The results showed that motor performance was not significantly greater than that with sham tACS stimulation [I2 = 44%, 95% CI (-0.01, 0.35), p = 0.06, standardized mean difference = 0.17], whereas motor learning ability improved significantly [I2 = 33%, 95% CI (-1.03, -0.31), p = 0.0002, SMD = -0.67]. Subgroup analysis found that gamma bend tACS could affect the changes in motor performance (I2 = 6%, 95% CI (0.05, 0.51), p = 0.02, SMD = 0.28), and online tACS did as well [I2 = 54%, 95% CI (0.12, 0.56), p = 0.002, SMD = 0.34]. Conclusion: The results showed that tACS effectively improves motor performance (gamma band and online mode) and motor learning in healthy individuals, which indicates that tACS may be a potential therapeutic tool to improve motor behavioral outcomes. However, further evidence is needed to support these promising results. Systematic Review Registration: PROSPERO, identifier CRD42022342884.