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Project

Decoding neural activity in the visual system: a pseudo-optimal and robust process?

Applications of ideal observer theory in perceptual systems have greatly advanced our understanding of visual processing. In many instances, the benchmarks provided by iedal observer theory have shown that our visual system processes information in ways that at least approximate ideal task performance. Recently, it has been suggested that even in processing low-contrast sinusoidal gratings, information from a pool of cortical cells tuned to a braod range of spatial-frequencies is combined by means of a simple, heuristic decision rule that resembles optimal combination. The main aim of this project is to explore this hypothesis further by testing to what degree detection and discrimination of simple stimuli is consistent with a model of our visual system in which simulated neural responses are decoded in a (pseudo-)optimal fashion. To this end, a combination of psychophysical experiments, neural network simulations and computational modelling will be used as tools. The second aim of the project is to explore whether a unified model-architecture (i.e., a biologically inspired front-end combined with (pseudo-)optimal decoding) manages to explain how we detect and discriminate both simple and more complex stimuli.
Date:1 Oct 2009 →  30 Sep 2012
Keywords:Discrimination, Detection, Population coding, Computational model, Psychophysics, Spation vision
Disciplines:Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing, Animal experimental and comparative psychology, Applied psychology, Human experimental psychology