Neural Computation 6: 14-18, 1994
Reasonable biophysical assumptions about synaptic transmission allow the equations for a simple kinetic synapse model to be solved analytically. This yields a mechanism that preserves the advantages of kinetic models while being as fast to compute as a single alpha -function. Moreover, this mechanism accounts implicitly for saturation and summation of multiple synaptic events, obviating the need for event queuing. The authors have presented a method by which synaptic conductances can be computed with low computational expense. The kinetic approach provides a natural means to describe the behavior of synapses in a way that handles the interaction of successive presynaptic events. Under the same assumption that transmitter concentration occurs as a pulse, more complex kinetic schemes can be treated. The 'kinetic synapse' can thus be generalized to give various conductance time courses with multiexponential rise and decay phases, without sacrificing the efficiency of the first-order model.
See also SYN.tar.Z and SYN.ZIP. This package shows how to implement biophysical models of synaptic interactions using NEURON. Both detailed and simplified models of synaptic currents and most useful types of postsynaptic receptors (AMPA, NMDA, GABA_A, GABA_B, neuromodulators) are described in a reference paper. We provide here the complement to simulate the same models using NEURON. The reference paper is a chapter in the book "Methods in Neuronal Modeling":
Destexhe, A., Mainen, Z.F. and Sejnowski,
Kinetic models of synaptic transmission.
In: Methods in Neuronal Modeling , 2nd Edition, Edited by Koch, C. and Segev, I., MIT Press, Cambridge, MA, 1997 (in press)
in which all details are given. More instructions are provided in a README file.