Visual and proprioceptive feedback both contribute to optimal perceptual decisions, but it remains unknown how these feedback signals are integrated together or consider factors such as delays and variance during online control. We investigated this question by having participants reach to a target with randomly applied mechanical and/or visual disturbances. We observed that the presence of visual feedback during a mechanical disturbance did not increase the size of the muscle response significantly but did decrease variance, consistent with a dynamic Bayesian integration model (Experiment 1). In a control experiment we verified that vision had a potent influence when mechanical and visual disturbances were both present but opposite in sign (Experiment 2). These results highlight a complex process for multi-sensory integration, where visual feedback has a relatively modest influence when the limb is mechanically disturbed, but a substantial influence when visual feedback becomes misaligned with the limb. The dataset contains hand kinematics and EMG data recorded during each experiment, and information of visual/mechanical disturbances that were applied during the experiments.

The dataset was collected by Kinarm Exoskeleton Lab (Kinarm, Kingston ON). The data has been processd by Matlab 2018a (Mathworks Inc. Natick MA, USA) for raw data processing, analysis on intermediate files, figure creation and statistics.

Please refer "Code descriptions Exp*.docx" and "Data descriptions Exp*.docx" for more information of analysis codes and datasets.