Neuroadaptive Bayesian optimization and hypothesis testing
Cognitive neuroscientists are often interested in broad research questions, yet use overly
narrow experimental designs by considering only a small subset of possible experimental …
narrow experimental designs by considering only a small subset of possible experimental …
Adaptive design optimization as a promising tool for reliable and efficient computational fingerprinting
A key challenge in understanding mental (dys) functions is their etiological and functional
heterogeneity, and several multidimensional assessments have been proposed for their …
heterogeneity, and several multidimensional assessments have been proposed for their …
[HTML][HTML] Determining informative priors for cognitive models
MD Lee, W Vanpaemel - Psychonomic Bulletin & Review, 2018 - Springer
The development of cognitive models involves the creative scientific formalization of
assumptions, based on theory, observation, and other relevant information. In the Bayesian …
assumptions, based on theory, observation, and other relevant information. In the Bayesian …
[HTML][HTML] Rapid, precise, and reliable measurement of delay discounting using a Bayesian learning algorithm
Abstract Machine learning has the potential to facilitate the development of computational
methods that improve the measurement of cognitive and mental functioning. In three …
methods that improve the measurement of cognitive and mental functioning. In three …
[HTML][HTML] Assessing the detailed time course of perceptual sensitivity change in perceptual learning
The learning curve in perceptual learning is typically sampled in blocks of trials, which could
result in imprecise and possibly biased estimates, especially when learning is rapid …
result in imprecise and possibly biased estimates, especially when learning is rapid …
[HTML][HTML] Hierarchical Bayesian modeling of contrast sensitivity functions in a within-subject design
Recent development of the quick contrast sensitivity function (qCSF) method has made it
possible to obtain accurate, precise, and efficient contrast sensitivity function (CSF) …
possible to obtain accurate, precise, and efficient contrast sensitivity function (CSF) …
[HTML][HTML] ADOpy: a python package for adaptive design optimization
Experimental design is fundamental to research, but formal methods to identify good
designs are lacking. Advances in Bayesian statistics and machine learning offer algorithm …
designs are lacking. Advances in Bayesian statistics and machine learning offer algorithm …
[HTML][HTML] Collective endpoint of visual acuity and contrast sensitivity function from hierarchical Bayesian joint modeling
Clinical trials typically analyze multiple endpoints for signals of efficacy. To improve signal
detection for treatment effects using the high-dimensional data collected in trials, we …
detection for treatment effects using the high-dimensional data collected in trials, we …
Data-driven experimental design and model development using Gaussian process with active learning
Interest in computational modeling of cognition and behavior continues to grow. To be most
productive, modelers should be equipped with tools that ensure optimal efficiency in data …
productive, modelers should be equipped with tools that ensure optimal efficiency in data …
[HTML][HTML] Quantifying uncertainty of the estimated visual acuity behavioral function with hierarchical Bayesian modeling
Purpose: The goal of this study is to develop a hierarchical Bayesian model (HBM) to better
quantify uncertainty in visual acuity (VA) tests by incorporating the relationship between VA …
quantify uncertainty in visual acuity (VA) tests by incorporating the relationship between VA …