.png){kind=icon}
Return
Validating model-based Bayesian integration using prior-cost metamers
.png){kind=icon}
OA
AI
DOI：10.1073/pnas.2021531118.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
There are two competing views on how humans make decisions under uncertainty. Bayesian decision theory posits that humans optimize their behavior by establishing and integrating internal models of past sensory experiences (priors) and decision outcomes (cost functions). An alternative hypothesis posits that decisions are optimized through trial and error without explicit internal models for priors and cost functions. To distinguish between these possibilities, we introduce a paradigm that probes the sensitivity of humans to transitions between prior-cost pairs that demand the same optimal policy (metamers) but distinct internal models. We demonstrate the utility of our approach in two experiments that were classically explained by Bayesian theory. Our approach validates the Bayesian learning strategy in an interval timing task but not in a visuomotor rotation task. More generally, our work provides a domain-general approach for testing the circumstances under which humans explic-itly implement model-based Bayesian computations.
Keywords:
Bayesian integration
internal model
sensorimotor learning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
P
IF:
9.1
Papers:
10.8W
Citations:
73.5W
Organization
No organization information available
Cited Papers
Application of the small‐angle X‐ray scattering technique for the study of equilibrium enzyme‐substrate interactions of phenylalanyl‐tRNA synthetase from E. coli with tRNAPhe.png)
FEBS LettersOAAI
FEBS LettersIF0
OAAIShareSaveShareSaveShareSaveReverse osmosis molecular differentiation of organic liquids using carbon molecular sieve membranesScience
ScienceIF0
PREAI
ShareSaveShareSavePosterior parietal cortex represents sensory history and mediates its effects on behaviourNATUREOAAI
NATUREIF48.5
OAAIShareSave
View more