Covariant spatio-temporal receptive fields for spiking neural networks.

ABSTRACT: Biological nervous systems constitute important sources of inspiration towards computers that are faster, cheaper, and more energy efficient. Neuromorphic disciplines view the brain as a coevolved system, simultaneously optimizing the hardware and the algorithms running on it. There are clear efficiency gains when bringing the computations into a physical substrate, but we presently lack theories to guide efficient implementations. Here, we present a principled computational model for neuromorphic systems in terms of spatio-temporal receptive fields, based on affine Gaussian kernels over space and leaky-integrator and leaky integrate-and-fire models over time. Our theory is provably covariant to spatial affine and temporal scaling transformations, with close similarities to visual processi

SUBMITTER: Pedersen JE 

PROVIDER: S-EPMC12413456 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature