A neural network model for the acquisition of a spatial body scheme through sensorimotor interaction

Authors:
Vadim Y. Roschin;Alexander A. Frolov;Yves Burnod;Marc A. Maier
Affiliations:
-;-;-;-
Venue:
Neural Computation
Year:
2011

Citing 6
Cited 0

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Abstract

This letter presents a novel unsupervised sensory matching learning technique for the development of an internal representation of three-dimensional information. The representation is invariant with respect to the sensory modalities involved. Acquisition of the internal representation is demonstrated with a neural network model of a sensorimotor system of a simple model creature, consisting of a tactile-sensitive body and a multiple-degrees-of-freedom arm with proprioceptive sensitivity. Acquisition of the 3D representation as well as a distributed representation of the body scheme, occurs through sensorimotor interactions (i.e., the sensory-motor experience of the creature). Convergence of the learning is demonstrated through computer simulations for the model creature with a 7-DoF arm and a spherical body covered by 20 tactile fields.