Point estimate observers: A new class of models for perceptual decision making.
- 1 March 2023
- journal article
- research article
- Published by American Psychological Association (APA) in Psychological Review
- Vol. 130 (2), 334-367
- https://doi.org/10.1037/rev0000402
Abstract
Bayesian optimal inference is often heralded as a principled, general framework for human perception. However, optimal inference requires integration over all possible world states, which quickly becomes intractable in complex real-world settings. Additionally, deviations from optimal inference have been observed in human decisions. A number of approximation methods have previously been suggested, such as sampling methods. In this study, we additionally propose point estimate observers, which evaluate only a single best estimate of the world state per response category. We compare the predicted behavior of these model observers to human decisions in five perceptual categorization tasks. Compared to the Bayesian observer, the point estimate observer loses decisively in one task, ties in two and wins in two tasks. Two sampling observers also improve upon the Bayesian observer, but in a different set of tasks. Thus, none of the existing general observer models appears to fit human perceptual decisions in all situations, but the point estimate observer is competitive with other observer models and may provide another stepping stone for future model development. (PsycInfo Database Record (c) 2023 APA, all rights reserved).Keywords
Funding Information
- German Research Foundation (SCHU 3351/1-1)
- Economic and Social Research Council
- St John’s College
- National Institutes of Health (R01EY020958; R01EY026927)
- NYU
This publication has 66 references indexed in Scilit:
- Probabilistic brains: knowns and unknownsNature Neuroscience, 2013
- Marginalization in Neural Circuits with Divisive NormalizationJournal of Neuroscience, 2011
- Optimal defocus estimation in individual natural imagesProceedings of the National Academy of Sciences of the United States of America, 2011
- Bayesian sampling in visual perceptionProceedings of the National Academy of Sciences of the United States of America, 2011
- Contributions of ideal observer theory to vision researchVision Research, 2011
- Spontaneous Cortical Activity Reveals Hallmarks of an Optimal Internal Model of the EnvironmentScience, 2011
- Uncertainty in category-based induction: When do people integrate across categories?Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
- Predictive coding under the free-energy principlePhilosophical Transactions B, 2009
- Probabilistic Population Codes for Bayesian Decision MakingNeuron, 2008
- Experience can change the 'light-from-above' priorNature Neuroscience, 2004