Abstract
The purpose of this work is to outline a computational architecture for the intelligent processing of sensorimotor patterns. The focus is on the nature of the internal representations of the outside world which are necessary for planning and other goal-oriented functions. A model named N-SOBoS (new self-organizing body-schema), based on the SOBoS model [10] and on the dual Extended Topology Representing Network architecture is proposed, which integrates a number of concepts and methods partly explored in the field [15, 11, 12]. The novelty and the biological plausibility is related to the global architecture which allows to deal with sensorimotor patterns in a coordinate-free way, using population codes as internal representations and communication channels among different cortical maps.
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References
J. Decety and D.H. Ingvar. Brain structures partecipating in mental simulation of motor behavior: a neuropsychological interpretation. Acta Psychologica, 73:13–34, 1990.
J. Decuyper and D. Keymeulen. A reactive robot navigation system based on a fluid dynamics metaphor. In Hans-Paul Schwefel and Reinhard Maenner, editors, Parallel Problem Solving from Nature, pages 348–355. Springer, 1991.
F. Frisone and P.G. Morasso. Extending the TRN model in a biologically plausible way. In ICANN97-Int. Conf. on Artificial Neural Networks, pages 201–206, Lousanne, October 1997. Springer.
P. Gaudiano and S. S. Grossberg. Vector associative maps: unsupervised real-time error-based learning and control of movement trajectories. Neural Networks, 4:147–183, 1991.
E. I. Knudsen, S. du Lac, and S.D. Esterly. Computational maps in the brain. Annual Review of Neuroscience, 10:41–65, 1987.
M. Kuperstein and J. Rubinstein. Implementation of an adaptive neural controller for sensory-motor coordination. In R. Pfeifer, Z. Schreter, F. Fogelman-Soulie, and L. Steels, editors, Connectionism in Perspective, pages 49–61. Elsevier Science Publishers, Amsterdam, 1989.
T. Martinetz and K. Schulten. A’ Neural-Gas’ network learns topologies. In T. Kohonen, K. Makisara, O. Simula, and J. Kangas, editors, Artificial Neural Networks, Amsterdam, 1991. North-Holland.
T. Martinetz and K. Schulten. Topology Representing Networks. Neural Networks, 3:507–522, 1994.
P. Morasso and V. Sanguineti. Neurocomputing concepts in motor control. In J. Paillard, editor, Brain and Space, pages 404–432. University Press, Oxford, UK, 1991.
P. Morasso and V. Sanguineti. Self-organizing body-schema for motor planning. Journal of Motor Behavior, 26:131–148, 1993.
P. Morasso and V. Sanguineti. Kinematic invariances and body schema. Behavioral and Brain Sciences, 18:769–770, 1995.
P. Morasso and V. Sanguineti. How the brain can discover the existence of external egocentric space. Neurocomputing, 12:289–310, 1996.
F. A. Mussa Ivaldi, P. Morasso, and R. Zaccaria. Kinematic networks-A distributed model for representing and regularizing motor redundancy. Biological Cybernetics, 60:1–16, 1988.
H. Ritter, T. Martinetz, and K. Schulten. Topology conserving maps for learning visuo-motor coordination. Neural Networks, 2:159–168, 1989.
V. Sanguineti, T. Tsuji, and P. Morasso. A dynamical model for the generation of curved trajectories. In S. Gielen and B. Kappen, editors, International Conference on Artificial Neural Networks, pages 115–118, London, 1993. Springer.
R.N. Shepard and L.A. Cooper. Mental Images and their transformations. MIT Press, Cambridge, MA, 1982.
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Frisone, F., Morasso, P.G. (1999). The N-SOBoS model. In: Marinaro, M., Tagliaferri, R. (eds) Neural Nets WIRN Vietri-99. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0877-1_8
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DOI: https://doi.org/10.1007/978-1-4471-0877-1_8
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