Abstract
AbstractPerceptual decisions are better when they take uncertainty into account. Uncertainty arises not only from the properties of sensory input but also from cognitive sources, such as different levels of attention. However, it is unknown whether humans appropriately adjust for such cognitive sources of uncertainty during perceptual decision making. Here we show that human categorization and confidence decisions take into account uncertainty related to attention. We manipulated uncertainty in an orientation categorization task from trial to trial using only an attentional cue. The categorization task was designed to disambiguate decision rules that did or did not depend on attention. Using formal model comparison to evaluate decision behavior, we found that category and confidence decision boundaries shifted as a function of attention in an approximately Bayesian fashion. This means that the observer’s attentional state on each trial contributed probabilistically to the decision computation. This responsiveness of an observer’s decisions to attention-dependent uncertainty should improve perceptual decisions in natural vision, in which attention is unevenly distributed across a scene.
Publisher
Cold Spring Harbor Laboratory
Reference54 articles.
1. Knill, David C & Richards, W. Perception as Bayesian Inference (Cambridge University Press, 1996).
2. Trommershäuser, J. , Kording, K. & Landy, M. S. (eds.) Sensory Cue Integration (Oxford University Press, 2011).
3. Ma, W. J. & Jazayeri, M. Neural coding of uncertainty and probability. Annual Review of Neuroscience (2014).
4. Qamar, A. T. et al. Trial-to-trial, uncertainty-based adjustment of decision boundaries in visual categorization. Proceedings of the National Academy of Sciences (2013).
5. Adler, W. T. & Ma, W. J. Human confidence reports account for sensory uncertainty but in a non-Bayesian way. bioRxiv (2017). related:qMQe6XVts8AJ.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献