Linking non-binned spike train kernels to several existing spike train metrics.

This work presents two kernels which can be applied to sets of spike times.This allows the use of state-of-the-art classification techniques to spike trains.The presented kernels are closely related to several recent and often used spike train metrics.One of the main advantages is that it does not require the spike trains to be binned.A high temporal resolution is thus preserved which is needed when temporal coding is used.As a test of the classification possibilities a jittered spike train template classification problem is solved.