The posterior parietal cortex of primates, and more exactly areas of the dorso-medial visual stream, are able to encode the peripersonal space of a subject in a way suitable for gathering visual information and contextually performing purposeful gazing and arm reaching movements. Such sensorimotor knowledge of the environment is not explicit, but rather emerges through the interaction of the subject with nearby objects. In this work, single-cell data regarding the activation of primate dorso-medial stream neurons during gazing and reaching movements is studied, with the purpose of discovering meaningful pattern useful for modeling purposes. The outline of a model of the mechanisms which allow humans and other primates to build dynamical representations of their peripersonal space through active interaction with nearby objects is proposed, and a detailed description of how to employ the results of the data analysis in the model is offered. The application of the model to robotic systems will allow artificial agents to improve their skills in exploring the nearby space, and will at the same time constitute a way to validate modeling assumptions.

The Dorso-medial visual stream: from Neural Activation to Sensorimotor Interaction

MARZOCCHI, NICOLETTA;BOSCO, ANNALISA;FATTORI, PATRIZIA;
2010

Abstract

The posterior parietal cortex of primates, and more exactly areas of the dorso-medial visual stream, are able to encode the peripersonal space of a subject in a way suitable for gathering visual information and contextually performing purposeful gazing and arm reaching movements. Such sensorimotor knowledge of the environment is not explicit, but rather emerges through the interaction of the subject with nearby objects. In this work, single-cell data regarding the activation of primate dorso-medial stream neurons during gazing and reaching movements is studied, with the purpose of discovering meaningful pattern useful for modeling purposes. The outline of a model of the mechanisms which allow humans and other primates to build dynamical representations of their peripersonal space through active interaction with nearby objects is proposed, and a detailed description of how to employ the results of the data analysis in the model is offered. The application of the model to robotic systems will allow artificial agents to improve their skills in exploring the nearby space, and will at the same time constitute a way to validate modeling assumptions.
Chinellato E.; Grzyb BJ; Marzocchi N; Bosco A; Fattori P; del Pobil A
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/93522
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