Abstract
Sensory-motor learning is commonly considered as a mapping process, whereby sensory information is transformed into the motor commands that drive actions. However, this directional mapping, from inputs to outputs, is part of a loop; sensory stimuli cause actions and vice versa. Here, we explore whether actions affect the understanding of the sensory input that they cause. Using a visuo-motor task in humans, we demonstrate two types of learning-related behavioral effects. Stimulus-dependent effects reflect stimulus-response learning, while action-dependent effects reflect a distinct learning component, allowing the brain to predict the forthcoming sensory outcome of actions. Together, the stimulus-dependent and the action-dependent learning components allow the brain to construct a complete internal representation of the sensory-motor loop.
Highlights
Meaningful interactions with the environment are based on sensory-motor learning
Inverse models allow transforming of sensory inputs and desired goals into motor commands (Figure 1, blue)
Forward models act in the opposite direction: they allow the brain to predict the sensory outcome of actions (Figure 1, red)
Summary
Meaningful interactions with the environment are based on sensory-motor learning. In order to turn a page in a journal, for example, one should first learn how to translate relevant sensory information (e.g., the location of the page) into the appropriate action. As one gains statistical knowledge of the outcome of previous actions (e.g., hand movement while gripping the page), one can learn to estimate how future actions would affect subsequent sensory information (e.g., the location of the page). Inverse models allow transforming of sensory inputs and desired goals into motor commands (Figure 1, blue). Forward models act in the opposite direction: they allow the brain to predict the sensory outcome of actions (Figure 1, red)
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