气候变化领域集成服务门户(CCPortal): Serial reproduction reveals the geometry of visuospatial representations

CCPortal

DOI	10.1073/PNAS.2012938118
	Serial reproduction reveals the geometry of visuospatial representations
	Langlois T.A.; Jacoby N.; Suchow J.W.; Griffiths T.L.
发表日期	2021
ISSN	00278424
卷号	118 期号:13
英文摘要	An essential function of the human visual system is to locate objects in space and navigate the environment. Due to limited resources, the visual system achieves this by combining imperfect sensory information with a belief state about locations in a scene, resulting in systematic distortions and biases. These biases can be captured by a Bayesian model in which internal beliefs are expressed in a prior probability distribution over locations in a scene. We introduce a paradigm that enables us to measure these priors by iterating a simple memory task where the response of one participant becomes the stimulus for the next. This approach reveals an unprecedented richness and level of detail in these priors, suggesting a different way to think about biases in spatial memory. A prior distribution on locations in a visual scene can reflect the selective allocation of coding resources to different visual regions during encoding ("efficient encoding"). This selective allocation predicts that locations in the scene will be encoded with variable precision, in contrast to previous work that has assumed fixed encoding precision regardless of location. We demonstrate that perceptual biases covary with variations in discrimination accuracy, a finding that is aligned with simulations of our efficient encoding model but not the traditional fixed encoding view. This work demonstrates the promise of using nonparametric data-driven approaches that combine crowdsourcing with the careful curation of information transmission within social networks to reveal the hidden structure of shared visual representations. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Bayesian statistics; Iterated learning; Spatial memory; Visual perception
语种	英语
scopus关键词	adult; article; crowdsourcing; geometry; human; learning; reproduction; simulation; social network; spatial memory; vision
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/180120
作者单位	Department of Psychology, University of California, Berkeley, CA 94704, United States; Department of Computer Science, Princeton University, Princeton, NJ 08542, United States; Computational Auditory Perception Research Group, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, 60322, Germany; The Center for Science and Society, Columbia University, New York, NY 10027, United States; School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, United States
推荐引用方式 GB/T 7714	Langlois T.A.,Jacoby N.,Suchow J.W.,et al. Serial reproduction reveals the geometry of visuospatial representations[J],2021,118(13).
APA	Langlois T.A.,Jacoby N.,Suchow J.W.,&Griffiths T.L..(2021).Serial reproduction reveals the geometry of visuospatial representations.Proceedings of the National Academy of Sciences of the United States of America,118(13).
MLA	Langlois T.A.,et al."Serial reproduction reveals the geometry of visuospatial representations".Proceedings of the National Academy of Sciences of the United States of America 118.13(2021).