Neural Modeling: Synaptic Plasticity

2005-12-25T07:17:47Z

Reviewing the code of the SPNet++ I realized that the implemented synaptic plasticity mechanism in the simulation is much simpler than I expected. It turned our that the code implements the nearest-neighbor spike model described in RELATING-STDP-TO-BCM article by Eugene M. Izhikevich and Niraj S. Desai. According to the authors of the article it may be sufficient to only consider two postsynaptic spikes -- the one that occurs before and the one that occurs after the presynaptic firing -- while determining whether a synapse should be potentiated or depressed based on recent spike activity. In addition to attempting to unify different forms of plasticity -- spike-timing-dependent plasticity (STDP) and a standard long-term potentiation and depression (LTP/LTD) -- into a single framework, this approach appears to be very computationally efficient.

update 2006/01/14: STDP-BASED-ON-LOCAL-INFORMATION paper presents an alternative rule, which is also described as computationally efficient, yet simple and reliable. This paper also provides five types of gating functions: no gating, presynaptic, postsynaptic, dual OR and dual AND gating.

There is also more information on different types of synaptic plasticity in the post on synaptic connectivity.

Zero Brane

Neural Modeling: Synaptic Plasticity