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Jose F. Barraza, Norberto M. Grzywacz; Speed adaptation as Kalman filtering. Journal of Vision 2006;6(6):558. doi: https://doi.org/10.1167/6.6.558.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose. If the purpose of adaptation is to fit sensory systems to different environments, it may be understood as an optimization process. What the optimum is depends on the statistics of these environments. Therefore, the system should update its parameters as the environment changes. A Kalman-filtering strategy performs those estimations optimally by combining current estimations of the environment with those from the past. We investigate whether the visual system uses this strategy for speed adaptation. Methods. We performed a matching speed experiment by using drifting sinusoidal gratings to evaluate the time course of speed adaptation. Simulations of these experiments were generated by an implementation of the model developed by Grzywacz and de Juan (Network: Comput. Neural Syst. 14:465–482, 2003). Results. Experimental results are in agreement with modeling predictions. When subjects adapt to a low speed and it suddenly increases, the time course of adaptation presents two phases, namely, a rapid decrease of perceived speed followed by a slower phase. In contrast, when speed changes from fast to slow, adaptation presents a single phase. However, this asymmetry disappears both experimentally and in simulations when the adapting stimulus is noisy. In both transitions, adaptation now occurs in a single phase. Conclusions. That speed adaptation follows a Kalman-strategy suggests that the brain is constantly optimizing its speed estimates. Grzywacz and de Juan reached a similar conclusion for contrast adaptation, suggesting that Kalman adaptation may be a general feature in the brain.
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