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Nikos Gekas, Kyle C. McDermott, Pascal Mamassian; Disambiguating serial effects of multiple timescales. Journal of Vision 2019;19(6):24. doi: https://doi.org/10.1167/19.6.24.
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© ARVO (1962-2015); The Authors (2016-present)
What has been previously experienced can systematically affect human perception in the present. We designed a novel psychophysical experiment to measure the perceptual effects of adapting to dynamically changing stimulus statistics. Observers are presented with a series of oriented Gabor patches and are asked occasionally to judge the orientation of highly ambiguous test patches. We developed a computational model to quantify the influence of past stimuli presentations on the observers' perception of test stimuli over multiple timescales and to show that this influence is distinguishable from simple response biases. The experimental results reveal that perception is attracted toward the very recent past and simultaneously repulsed from stimuli presented at short to medium timescales and attracted to presentations further in the past. All effects differ significantly both on their relative strength and their respective duration. Our model provides a structured way of quantifying serial effects in psychophysical experiments, and it could help experimenters in identifying such effects in their data and distinguish them from less interesting response biases.
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