One purpose of Computational Neuroscience is to try to understand by using models how at least some parts in the brain work or how cognitive phenomena occur and are organized in terms of neuronal activity. The Hopfield model of a neural network, rooted in Statistical Physics, put forward by J. Hopfield in the 1980s, was one of the first attempts to explain how associative memory could work. It was successful in guiding experiments, e.g., in the hippocampus and primate inferotemporal cortex. However, some higher level cognitive functions that the brain accomplishes require, to be approached quantitaively, by more advanced models beyond simple cued retrieval...

Latching dynamics in Potts neural networks / Kang, Chol Jun. - (2017 Dec 18).

Latching dynamics in Potts neural networks

Kang, Chol Jun
2017-12-18

Abstract

One purpose of Computational Neuroscience is to try to understand by using models how at least some parts in the brain work or how cognitive phenomena occur and are organized in terms of neuronal activity. The Hopfield model of a neural network, rooted in Statistical Physics, put forward by J. Hopfield in the 1980s, was one of the first attempts to explain how associative memory could work. It was successful in guiding experiments, e.g., in the hippocampus and primate inferotemporal cortex. However, some higher level cognitive functions that the brain accomplishes require, to be approached quantitaively, by more advanced models beyond simple cued retrieval...
Treves, Alessandro
Kang, Chol Jun
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11767/63331
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