Improved Sensorimotor Performance via Stochastic Resonance

Several studies about noise-enhanced balance control in humans support the hypothesis that stochastic resonance can enhance the detection and transmission in sensorimotor system during a motor task. The purpose of the present study was to extend these findings in a simpler and controlled task. We explored whether a particular level of a mechanical Gaussian noise (0-15 Hz) applied on the index finger can improve the performance during compensation for a static force generated by a manipulandum. The finger position was displayed on a monitor as a small white point in the center of a gray circle. We considered a good performance when the subjects exhibited a low deviation from the center of this circle and when the performance had less variation over time. Several levels of mechanical noise were applied on the manipulandum. We compared the performance between zero noise (ZN), optimal noise (ON), and high noise (HN). In all subjects (8 of 8) the data disclosed an inverted U-like graph between the inverse of the mean variation in position and the input noise level. In other words, the mean variation was significantly smaller during ON than during ZN or HN. The findings suggest that the application of a tactile-proprioceptive noise can improve the stability in sensorimotor performance via stochastic resonance. Possible explanations for this improvement in motor precision are an increase of the peripheral receptors sensitivity and of the internal stochastic resonance, causing a better sensorimotor integration and an increase in corticomuscular synchronization.