Sign in
NeurosciencebioRxiv
Preprint

Augmenting visual errors or variability does not enhance motor learning in remote web application tasks

Nobuyasu NakanoiD, Akihiko MuraiiD

Abstract

Laboratory experiments employing robotic manipulandum are far from achieving their goal of helping people improve their motor learning. Remote experiments using web applications are an effective tool for bridging the gap between robotic manipulandum experiments in the laboratory and general motor tasks outside. However, the influence of interventions that increase error or variability in remote motor tasks on motor learning has not yet been determined. In this study, we aimed to elucidate the effects of interventions that visually increase errors and variability in remote experiments using web applications. In particular, 48 people participated in a web-based study on the cursor-manipulation of motor tasks using laptops. Three motor tasks (visuomotor-rotation reaching, virtual curling, and virtual ball-throwing tasks) were conducted, and each task consisted of 120 trials a day conducted for three days in this study. For each task, no intervention was provided on Day 1 and the intervention to augment motor error or variability was provided on Days 2 and 3. Differences between the groups in post-intervention test trials were examined using statistical analyses. Contrary to our expectations, the interventions of error-augmentation did not exhibit positive effects in Experiments 1 and 2, which could be attributed to a lack of haptic and proprioceptive information or inaccuracies in movement kinematics. In addition, the interventions of variability-augmentation did not exhibit positive effects in Experiment 3, which could be attributed to the complex dynamics in the relationship between perceived body movements and motor outcomes. Further research is required to identify the differences between the conditions when the interventions are effective or ineffective. Moreover, interventions must be developed to further improve general motor skills.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISArink '24Cardis '17Moghaddam '25Nardi '25Pagano '21Tsay '21
73% semantic matchNeuroscience
Wouter Arink, Katherine L. Poggensee, Niek Beckers+2 more·IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)·Sep 1, 2024· 1 citations