Estimating multiple temporal mechanisms in human vision.
When studying human ability to perceive temporal changes in luminance it is customary to estimate either temporal impulse response shapes or temporal modulation transfer functions, the representation of the impulse response in the frequency domain. The advantages and limitations of previous methods are summarized. We then describe an approach based on use of an impulse response basis set that resolves some of those limitations. We next present psychophysical results for spatiotemporal signal detection in spatiotemporal noise, together with an economical model of performance. The model is based on accepted notions of psychophysical detection mechanisms and the filter basis set described in the first part of the paper. The best-fitting model requires only eight parameters, as opposed to the 198 parameters required to separately fit each psychometric function, and captures both qualitative and quantitative properties of the psychophysical data. Finally, the best-fitting model indicates that only two temporal filters are necessary to describe the performance of each of three subjects under the specific stimulus conditions employed here.
Fredericksen
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Cognitive Science Department, U.C. Irvine 92697, USA. eric@mach2.hipl.uci.edu
Hess
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D006801:Humans; D008027:Light; D016013:Likelihood Functions; D008433:Mathematics; D008959:Models, Neurological; D010364:Pattern Recognition, Visual / Q000502:physiology; D011601:Psychophysics; D013997:Time Factors; D014785:Vision, Ocular / Q000502:physiology*