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...
|Autori:||Kang, Chol Jun|
|Titolo:||Latching dynamics in Potts neural networks|
|Data di pubblicazione:||18-dic-2017|
|Appare nelle tipologie:||8.1 PhD thesis|