High-order behaviour in learning gate networks with lateral inhibition
In this work we present a neural network model incorporating activity-dependent presynaptic facilitation with multidimensional inputs. The processing unit used is based on a slightly simplified version of the Learning Gate Model proposed by Ciaccia et al. (1992). The network topology integrates a we...
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Veröffentlicht in: | Biological cybernetics 1996-01, Vol.74 (1), p.73-83 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this work we present a neural network model incorporating activity-dependent presynaptic facilitation with multidimensional inputs. The processing unit used is based on a slightly simplified version of the Learning Gate Model proposed by Ciaccia et al. (1992). The network topology integrates a well-known biological neural circuit with a lateral inhibition connection subnet. By means of simulation experiments, we show that the proposed networks exhibit basic and high-order features of associative learning. In particular, overshadowing and blocking are reproduced in the presence of both noise-free and noisy inputs. The role of noise in the development of high-order learning capabilities is also discussed. |
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ISSN: | 0340-1200 1432-0770 |
DOI: | 10.1007/BF00199139 |