Abstract
Sensory systems adapt to environmental change. It has been argued that adaptation should have the effect of optimizing sensitivity to the new environment. Here we consider a framework in which this premise is made concrete using an economic normative theory of visual motion perception. In this framework, visual systems adapt to the environment by reallocating their limited neural resources. The allocation is optimal when uncertainties about different aspects of stimulation are balanced. This theory makes predictions about visual sensitivity as a function of environmental statistics. Adaptive optimization of the visual system should be manifested as a change in sensitivity for an observer and for the underlying motion-sensitive neurons. We review evidence supporting these predictions and examine effects of adaptation on the neuronal representation of visual motion.
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Notes
These uncertainties concern location and frequency content of stimuli, defined according to the information theory of Gabor6.
Change maps for all subjects appear in Fig S2 in Gepshtein et al.9.
This dimension could be space or time. For example, when x represents space, the larger number of lower level cells, from which the cell I receive information, corresponds to a larger receptive field size of I.
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Gepshtein, S., Albright, T.D. Adaptive Optimization of Visual Sensitivity. J Indian Inst Sci 97, 423–434 (2017). https://doi.org/10.1007/s41745-017-0056-y
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DOI: https://doi.org/10.1007/s41745-017-0056-y