Two-Trace Model for Spike-Timing Dependent Plasticity

ECHEVESTE, RODRIGO; GROS, CLAUDIUS

Congreso; Osnabrück Computational Cognition Alliance Meeting (Occam) 2014; 2014

In the present work we propose a simple model formulating synaptic potentiation and depression in terms of two interacting traces, representing the fraction of open NMDA receptors and the Ca2+ concentration in the post-synaptic neuron, respectively. These two traces then determine the evolution of the synaptic weight. We first test that the standard STDP curve for low frequency trains of pairs of pre- and post-synaptic spikes is obtained and we then evaluate triplet effects. Finally, we train the synapse with Poissonian spike-trains and observe that a BCM-like rule for plasticity as a function of the pre-and post-synaptic firing rates is recovered. Having a low number of parameters and composed of only polynomial differential equations, the model is able nonetheless to reproduce key features of LTP and LTD. Moreover, since the parameters of the model are easily related to the dynamical properties of the synapse, the model constitutes a useful tool to study extended neural networks from a dynamical system?s point of view.