Computing the Optimally Fitted Spike Train for a Synapse

Description

Neural Computation 13, 2477–2494 (2001)Experimental data have shown that synapses are heterogeneous: differentsynapses respond with different sequences of amplitudes of postsynapticresponses to the same spike train. Neither the role of synaptic dynamicsitself nor the role of the heterogeneity of synaptic dynamics for computationsin neural circuits is well understood. We present in this articletwo computational methods that make it feasible to compute for a givensynapse with known synaptic parameters the spike train that is optimallyfitted to the synapse in a certain sense. With the help of these methods,one can compute, for example, the temporal pattern of a spike train (witha given number of spikes) that produces the largest sum of postsynapticresponses for a specific synapse. Several other applications are alsodiscussed. To our surprise, we find that most of these optimally fittedspike trains match common firing patterns of specific types of neuronsthat are discussed in the literature. Hence, our analysis provides a possiblefunctional explanation for the experimentally observed regularityin the combination of specific types of synapses with specific types ofneurons in neural circuits.