Electrophysiological maps based on a Gaussian kernel have been proposed as a means to visualize response to stimulation in deep brain stimulation (DBS) surgeries. However, the Gaussian model does not represent the underlying physiological phenomenon produced by stimulation. We propose a new method to create physiological maps, which relies on spherical shell kernels. We compare our new maps to those created with Gaussian kernels and show that, on simulated data, this new approach produces more realistic maps. Experiments we have performed with real patient data show that our new maps correlate well with the underlying anatomy. Finally, we present preliminary results on an ongoing study assessing the value of these maps as pre-operative planning and intra-operative guidance tools.