Development of reaching to the body in early infancy: From experiments to robotic models

In 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob). IEEE. pp. 112-119 (2017)
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We have been observing how infants between 3 and 21 months react when a vibrotactile stimulation (a buzzer) is applied to different parts of their bodies. Responses included in particular movement of the stimulated body part and successful reaching for and removal of the buzzer. Overall, there is a pronounced developmental progression from general to specific movement patterns, especially in the first year. In this article we review the series of studies we conducted and then focus on possible mechanisms that might explain what we observed. One possible mechanism might rely on the brain extracting “sensorimotor contingencies” linking motor actions and resulting sensory consequences. This account posits that infants are driven by intrinsic motivation that guides exploratory motor activity, at first generating random motor babbling with self-touch occurring spontaneously. Later goal-oriented motor behavior occurs, with self-touch as a possible effective tool to induce informative contingencies. We connect this sensorimotor view with a second possible account that appeals to the neuroscientific concepts of cortical maps and coordinate transformations. In this second account, the improvement of reaching precision is mediated by refinement of neuronal maps in primary sensory and motor cortices—the homunculi—as well as in frontal and parietal corti- cal regions dedicated to sensorimotor processing. We complement this theoretical account with modeling on a humanoid robot with artificial skin where we implemented reaching for tactile stimuli as well as learning the “somatosensory homunculi”. We suggest that this account can be extended to reflect the driving role of sensorimotor contingencies in human development. In our conclusion we consider possible extensions of our current experiments which take account of predictions derived from both these kinds of models.

Author Profiles

Matej Hoffmann
Czech Technical University, Prague


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