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József Arató, József Fiser; Information integration in sequential visual decision-making. Journal of Vision 2015;15(12):385. doi: 10.1167/15.12.385.
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© ARVO (1962-2015); The Authors (2016-present)
Although it is widely accepted that both summary statistics and salient patterns affect human decision making based on temporally varying visual input, the relative contributions and the exact nature of how these aspects determine human judgment are unclear and controversial, often discussed under the labels of priming, adaptation, or serial effects. To tease apart the role of the various factors influencing such decision making tasks, we conducted a series of 7 adult behavioral experiments. We asked subjects to perform a 2-AFC task of judging which of two possible visual shapes appeared on the screen in a randomly ordered sequence while we varied the long- and short-term probability of appearance, the level of Gaussian pixel noise added to the stimulus, and the ratio of repetitions vs. alternations. We found that the quality of the stimulus reliably and systematically influenced the strength of influence by each factor. However, instead of a simple interpolation between long-term probabilities and veridical choice, different pairings of short- and long-term appearance probabilities produced various characteristic under- and over-shootings in choice performances ruling out earlier models proposed for explaining human behavior. Independent control of base probabilities and repetition/alternation revealed that despite the two characteristics being correlated in general, repetition/alternation is a factor independently influencing human judgment. In addition, we found that human performance measured by correct answers and by reaction times (RT) yield opposing results under some conditions indicating that RT measures tap into motor rather than cognitive components of sequence coding. Our results can be captured by a model of human visual decision making that not only balances long- and short-term summary statistics of sequences, but in parallel also encodes salient features, such as repetitions, and in addition, relies on a generic assumption of non-discriminative flat prior of events in the environment.
Meeting abstract presented at VSS 2015
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