Learning postures through sensorimotor training: a human simulation case study

In this paper, we present a case study showing why the modeling eort of computational neuro-sciences must call upon interactions with an environment when developmental phenomena are investigated. More specifically, in the context of a model of the spatial organization of a repertoire of postures, we show that calling upon a realistic simulation of the human kinematics (i) results in raising the question of the nature of information encoded in this repertoire ; and (ii) reveals that some previous assumptions about the functional organization of this repertoire were not necessary. Finally, we point out that conversely, robotics can benefit from such studies by using the suggested principles to design more adaptive control architectures.

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