Sciweavers

ICANN
2003
Springer

Optimal Hebbian Learning: A Probabilistic Point of View

13 years 8 months ago
Optimal Hebbian Learning: A Probabilistic Point of View
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabilistic optimality criterion. Our approach allows us to obtain quantitative results in terms of a learning window. This is done by maximising a given likelihood function with respect to the synaptic weights. The resulting weight adaptation is compared with experimental results.
Jean-Pascal Pfister, David Barber, Wulfram Gerstne
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where ICANN
Authors Jean-Pascal Pfister, David Barber, Wulfram Gerstner
Comments (0)