High-order behaviour in learning gate networks with lateral inhibition View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1996-01

AUTHORS

E. Blanzieri, F. Grandi, D. Maio

ABSTRACT

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. More... »

PAGES

73-83

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00199139

DOI

http://dx.doi.org/10.1007/bf00199139

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049659391

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/8573655


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