Neurally-plausible radial basis kernels using distributed Fourier embeddings

Tech Report, 2026

Jakeb Chouinard

Abstract

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. Further, we analyze previous radial basis kernel work based on grid cell-like representations and demonstrate that such representations are both capable of and optimal for realizing radial basis kernels.

Full text links

 PDF

 DOI

 arXiv

CTN Tech Report

Month
05
Institution
Centre for Theoretical Neuroscience
Address
Waterloo, ON
Issn
CTN-TR-20260508-001
Doi
https://doi.org/10.48550/arXiv.2605.08458
Arxiv
2605.08458

Cite

Plain text

BibTeX