Modeling memory: what do we learn from attractor neural networks?

N Brunel; J P Nadal

doi:10.1016/s0764-4469(97)89830-7

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Modeling memory: what do we learn from attractor neural networks?

N Brunel·J P Nadal

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Abstract

In this paper we summarize some of the main contributions of models of recurrent neural networks with associative memory properties. We compare the behavior of these attractor neural networks with empirical data from both physiology and psychology. This type of network could be used in models with more complex functions.

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Humans Learning Memory Models, Neurological Models, Psychological Nerve Net Neuronal Plasticity Journal Article Review

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N Brunel, J P Nadal. Modeling memory: what do we learn from attractor neural networks?. https://doi.org/10.1016/s0764-4469(97)89830-7

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