2021/04/19 by Lucy L. W. Owen, Owen, Lucy, Jonathan Browder +9 · 1 citation
Computer Science · Engineering · #Analog and Mixed-Signal Circuit Design #Control Systems and Identification #FOS: Biological sciences #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Methodology (stat.ME) #Neurons and Cognition (q-bio.NC)
paper · pdf · doi:10.48550/arxiv.2104.09549
openalex publication_date 2021/04/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
We introduce a new set of models and adaptive psychometric testing methods for multidimensional psychophysics. In contrast to traditional adaptive staircase methods like PEST and QUEST, the method is multi-dimensional and does not require a grid over contextual dimensions, retaining sub-exponential scaling in the number of stimulus dimensions. In contrast to more recent multi-dimensional adaptive methods, our underlying model does not require a parametric assumption about the interaction between intensity and the additional dimensions. In addition, we introduce a new active sampling policy that explicitly targets psychometric detection threshold estimation and does so substantially faster than policies that attempt to estimate the full psychometric function (though it still provides estimates of the function, albeit with lower accuracy). Finally, we introduce AEPsych, a user-friendly open-source package for nonparametric psychophysics that makes these technically-challenging methods accessible to the broader community.