Advancing models of the visual system using biologically plausible unsupervised spiking neural networks - Taylor, L (2023)
Spikes are thought to provide a fundamental unit of computation in the nervous system. The retina is known to use the relative timing of spikes to encode visual input, whereas primary visual cortex (V1) exhibits sparse and irregular spiking activity – but what do these different spiking patterns represent about sensory stimuli? To address this question, I set out to model the retina and V1 using a biologically-realistic spiking neural network (SNN), exploring the idea that temporal prediction underlies the sensory transformation of natural inputs.