The multivariate adaptive design for efficient estimation of the time course of perceptual adaptation
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The multivariate adaptive design for efficient estimation of the time course of perceptual adaptation Ping Chen 1 & Steve Engel 2 & Chun Wang 3
# The Psychonomic Society, Inc. 2019
Abstract In experiments on behavioral adaptation, hundreds or even thousands of trials per subject are often required in order to accurately recover the many psychometric functions that characterize adaptation’s time course. More efficient methods for measuring perceptual changes over time would be beneficial to such efforts. In this article, we propose two methods to adaptively select the optimal stimuli sequentially in an experiment on adaptation: These are the minimum entropy (ME) method and the match probability (MP) method. The ME method minimizes the uncertainty about the joint posterior distribution of the function parameters at each trial and is mathematically equivalent to Zhao, Lesmes, and Lu’s (2019) method, which efficiently measures time courses of perceptual change by maximizing information gain. The MP method selects the next stimulus that makes the value of the psychometric function closest to .5—that is, where the probability of choosing either one of the two options for each stimulus is closest to .5. We extended Zhao et al.’s (2019) work by evaluating the ME method in a new domain (contrast adaptation) with two simulation studies that compared it to MP and two other methods (i.e., traditional staircase and random methods), and also explored the optimal block length. ME outperformed the other three methods in general, and using fewer longer blocks generally produced better parameter recovery than using more shorter blocks. Keywords Adaptive design . Minimum entropy . Perceptual adaptation . Time course . Tilt aftereffect
The properties of most biological systems, including human vision, change over time. Many such changes are functionally significant and take place on a reasonably rapid timescale— seconds to minutes—that enable them to be studied in the laboratory. Visual adaptation consists of a number of processes acting over this timescale to help the visual system optimize its performance within a given environment (e.g., Clifford & Rhodes, 2005). Examples include dark adaptation (e.g., Pugh, Nikonov, & Lamb, 1999), the development of color afterimages (e.g., Zaidi, Ennis, Cao, & Lee, 2012), and the wellstudied phenomenon of contrast adaptation (e.g., Clifford et al., 2007). In this latter form of adaptation, visual neurons reduce their responsiveness following exposure to their preferred stimuli, which are typically patterns of high and low luminance, characterized by their ratio, or contrast. Behavioral
* Chun Wang [email protected] 1
Beijing Normal University, Beijing, China
2
University of Minnesota, Minneapolis, MN, USA
3
University of Washington, Seattle, WA, USA
measures of perceptual sensitivity and bias show corresponding changes over time, as documented in a long history of psychophysical experiments. Whereas many experiments simply measure effects or aftereffects of adaptation, others focus on mea
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