Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network-Reference-Cited by-同舟云学术

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Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network

Published:1998-01 Issue:1 Volume:9 Page:123-152
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Brunel Nicolas¹,Carusi Francesco²,Fusi Stefano²³

Affiliation:

1. LPS (Laboratory associated with CNRS, Paris 6 and Paris 7 Universities), Ecole Normale Supérieure, 24 rue Lhomond, 75231, Paris Cedex 05, France

2. INFN, Sezione dell'Università di Roma, ‘La Sapienza’, Pza Aldo Moro 2, 00185, Rome, Italy

3. Racah Institute of Physics, Hebrew University of Jerusalem

Publisher

Informa UK Limited

Subject

Neuroscience (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1088/0954-898X_9_1_007

Reference34 articles.

1. Modeling Brain Function

2. Learning internal representations in an attractor neural network with analogue neurons

3. Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex

4. Correlations of cortical Hebbian reverberations: theory versus experiment

5. Constraints on learning in dynamic synapses

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