KCL

Demystyfying the black box of human cortical visual processing with computational and mathematical approaches

Research into sensory systems such as vision sometimes involes completely separate studies by Experimental Psychologists and Cognitive/Systems Neuroscientists. Visual motion processing presents a typical case where key insights about phenomena obtained from human behaviour remain disjointed from animal or imaging work which directly probes the same question by looking at the brain. Here we discuss how the use of models in the experimental process can improve the depth of insights. I elaborate on three examples. First, we derive some rules governing the dynamics of perceptual shifts during ambiguous motion perception. Second, we probe the thin line between noise and useful signals in visual cortex. Third, we look at the dynamic representation of information and emerging perceptual consequences as observers estimate visual speed. I hope to try and make the case that the approach can be applied more broadly across experiments.