2020年1月10日（金）
16:00-17:00
会場： CiNet　1F　大会議室

講演タイトル：”Suboptimal visual averaging reveals compulsory, nonlinear mechanisms in human vision”

講師：
Takahiro Doi
Department of Psychology
University of Pennsylvania

担当: 藤田 一郎 (PI)

Abstract:
How humans integrate ambiguous and conflicting signals has been a focus of perception and decision-making research for decades. Identifying the source of sub-optimality can reveal the information integration strategy used by the nervous system to solve ecologically relevant tasks in natural environments. In this study, we examined visual spatial averaging, a fundamental process underlying the transformation of noisy local signals into a more stable global estimate. A novel paradigm was used to measure the degree of human sub-optimality against the ideal observer. In this talk, first I will establish that human visual averaging is suboptimal in both luminance and stereoscopic domains: the visual system does not faithfully compute the average of a spatially varied stimulus, especially when spatial variability is large. Then, I will present a series of experiments designed to identify the source of sub-optimality. Our results indicate two kinds of nonlinear mechanisms at work: one is related to the down-weighting of outlier samples and the other is the spatial interaction among nearby signals within a stimulus. These compulsory nonlinear mechanisms, while suboptimal in our laboratory task, may reflect an information integration strategy that improves performance in more natural contexts cluttered with object boundaries and illumination variation.