Neurally-plausible radial basis kernels using distributed Fourier embeddings

ArXi:2605.08458v1 Announce Type: new Coherent, continuous spatial representations are critical for synthesizing physical and perceptual phenomena into a single representational space. Radial basis kernels provide a path forward for this type of distributed representation. In this work, we aim to characterize and analyze common radial basis kernels realizable in the neurally-plausible framework of spatial semantic pointers.