Can I read A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay on EtoBox?

A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay by Anatoli Gorchetchnikov; Massimiliano Versace; Michael E. Hasselmo is a Computer Science article available to read on EtoBox.

What is A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay about?

Temporal relationships between neuronal firing and plasticity have received significant attention in recent decades. Neurophysiological studies have shown the phenomenon of spike-timing-dependent plasticity (STDP). Various models were suggested to implement an STDP-like learning rule in artificial networks based on spiking neuronal representations. The rule presented here was developed under three constraints. First, it only depends on the information that is available at the synapse at the time of synaptic modification. Second, it naturally follows from neurophysiological and psychological research starting with Hebb's postulate [D. Hebb. (1949). The organization of behavior. Wiley, New York]. Third, it is simple, computationally cheap and its parameters are straightforward to determine. This rule is further extended by addition of four different types of gating derived from conventionally used types of gated decay in learning rules for continuous firing rate neural networks. The results show that the advantages of using these gatings are transferred to the new rule without sacrificing its dependency on spike-timing.

Who reads A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay?

Author

Anatoli Gorchetchnikov; Massimiliano Versace; Michael E. Hasselmo

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0893-6080)

Published

2005

Language

EN

Field

Computer Science (Physical Sciences)