From known to unknown: moving to unvisited locations in a novel sensorimotor map.

Abstract

Sensorimotor learning requires knowledge of the relationship between movements and sensory effects: a sensorimotor map. Generally, these mappings are not innate but have to be learned. During learning, the challenge is to build a continuous map from a set of discrete observations, that is, predict locations of novel targets. One hypothesis is that the learner linearly interpolates among discrete observations that are already in the map. Here, this hypothesis is tested by exposing human subjects to a novel mapping between arm movements and sounds. Participants were passively moved to the edges of the workspace receiving the corresponding sounds and then were presented intermediate sounds and asked to make movements to locations they thought corresponded to those sounds. It is observed that average movements roughly match linear interpolation of the space. However, the actual distribution of participants' movements is best described by a bimodal reaching strategy in which they move to one of two locations near the workspace edge where they had prior exposure to the sound-movement pairing. These results suggest that interpolation happens to a limited extent only and that the acquisition of sensorimotor maps may not be driven by interpolation but instead relies on a flexible recombination of instance-based learning.