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Kendrick Kay; Identifying the nonlinearities used in extrastriate cortex. Journal of Vision 2014;14(10):1474. doi: 10.1167/14.10.1474.
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© ARVO (1962-2015); The Authors (2016-present)
In this talk, I will discuss recent work in which I used fMRI measurements to develop models of how images are represented in human visual cortex. These models consist of specific linear and nonlinear computations and predict BOLD responses to a wide range of stimuli. The results highlight the importance of certain nonlinearities (e.g. compressive spatial summation, second-order contrast) in explaining responses in extrastriate areas. I will describe important choices made in the development of the approach regarding stimulus design, experimental design, and analysis. Furthermore, I will emphasize (and show through examples) that understanding representation requires a dual focus on abstraction and specificity. To grasp complex systems, it is necessary to develop computational concepts, language, and intuition that can be applied independently of data (abstraction). On the other hand, a model risks irrelevance unless it is carefully quantified, implemented, and systematically validated on experimental data (specificity).
Meeting abstract presented at VSS 2014
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