Modeling synaptic plasticity in conjuction with the timing of pre- and postsynaptic action potentials

Neural Comput. 2000 Feb;12(2):385-405. doi: 10.1162/089976600300015844.


We present a spiking neuron model that allows for an analytic calculation of the correlations between pre- and postsynaptic spikes. The neuron model is a generalization of the integrate-and-fire model and equipped with a probabilistic spike-triggering mechanism. We show that under certain biologically plausible conditions, pre- and postsynaptic spike trains can be described simultaneously as an inhomogeneous Poisson process. Inspired by experimental findings, we develop a model for synaptic long-term plasticity that relies on the relative timing of pre- and post-synaptic action potentials. Being given an input statistics, we compute the stationary synaptic weights that result from the temporal correlations between the pre- and postsynaptic spikes. By means of both analytic calculations and computer simulations, we show that such a mechanism of synaptic plasticity is able to strengthen those input synapses that convey precisely timed spikes at the expense of synapses that deliver spikes with a broad temporal distribution. This may be of vital importance for any kind of information processing based on spiking neurons and temporal coding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials*
  • Animals
  • Cerebral Cortex / physiology
  • Models, Neurological*
  • Neuronal Plasticity*
  • Neurons / physiology*
  • Presynaptic Terminals / physiology
  • Probability
  • Synapses / physiology*