Bat echolocation modelling using spike kernels with Support Vector Regression

From the echoes of their vocalisations bats extract information about the positions of reflectors. To gain an understanding of how target position is translated into neural features, we model the bat’s peripheral auditory system up until the auditory nerve. This model assumes multiple threshold detecting neurons for each frequency channel where the inter-spike times are linked to the location of the reflector. To show that this coding process can be reversed we compute the kernel product of the spike trains using a non-binned spike kernel function. This approach allows doing regression on azimuth and elevation using Support Vector Machines.