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. 2015 Nov 1:1:547-567.
doi: 10.1146/annurev-vision-082114-035509. Epub 2015 Oct 22.

Visual Adaptation

Affiliations

Visual Adaptation

Michael A Webster. Annu Rev Vis Sci. .

Abstract

Sensory systems continuously mold themselves to the widely varying contexts in which they must operate. Studies of these adaptations have played a long and central role in vision science. In part this is because the specific adaptations remain a powerful tool for dissecting vision, by exposing the mechanisms that are adapting. That is, "if it adapts, it's there." Many insights about vision have come from using adaptation in this way, as a method. A second important trend has been the realization that the processes of adaptation are themselves essential to how vision works, and thus are likely to operate at all levels. That is, "if it's there, it adapts." This has focused interest on the mechanisms of adaptation as the target rather than the probe. Together both approaches have led to an emerging insight of adaptation as a fundamental and ubiquitous coding strategy impacting all aspects of how we see.

Keywords: color; form; neural coding; perceptual constancy; perceptual norms; plasticity.

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Figures

Figure 1
Figure 1
Examples of similar perceptual aftereffects across different stimulus domains. Left panel: adaptation to a mean color, blur, or faces produces roughly global shifts in the appearance of stimuli relative to a norm (e.g. gray, focused, undistorted), so that the adapting stimulus appears more neutral, with no aftereffect when adapting to the norm (n). This norm-based coding pattern and its adaptation can arise in mechanisms broadly tuned to the stimulus dimension, or if the stimulus itself is broad rather than punctate (e.g. representing a bias in the stimulus spectrum). Right panel: adaptation to color contrast, spatial frequency, or viewpoint instead biases the appearance of other stimuli away from the adapting level, with no change in the perceived level (e.g. size) of the adapt level itself, and produces similar aftereffects after adapting to any level across the dimension. This pattern implicates coding in multiple more narrowly-tuned channels.
Figure 2
Figure 2
Simulations of color adaptation to a change in environment or change in observer. Top left and middle: roughly the same scene in two seasons. Bottom left and middle: adapting to the color statistics in each season biases color appearance by toning down the dominant hues and increasing the salience of novel hues (e.g. increasing the perceived saturation of greens in the arid scene). Thus the same observer codes color differently in the two environments. Top right: the middle, arid scene viewed through the lens of an older observer. Bottom right: adapting to the spectral changes introduced by the lens removes most of the color bias. Thus the two different observers code color similarly when adapted to the same environment.

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