A hierarchical Bayesian approach to assess learning and guessing strategies in reinforcement learning
Publication date: December 2019Source: Journal of Mathematical Psychology, Volume 93Author(s): Jessica Vera Schaaf, Marieke Jepma, Ingmar Visser, Hilde Maria HuizengaAbstractIn two-armed bandit tasks participants learn which stimulus in a stimulus pair is associated with the highest value. In typical reinforcement learning studies, participants are presented with several pairs in a random order; frequently applied analyses assume each pair is learned in a similar way. When tasks become more difficult, however, participants may learn some stimulus pairs while they fail to learn other pairs, that is, they simply guess for a ...
Source: Journal of Mathematical Psychology - September 8, 2019 Category: Psychiatry & Psychology Source Type: research
Editorial Board
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - July 30, 2019 Category: Psychiatry & Psychology Source Type: research
State-trace analysis misinterpreted and misapplied: Reply to Stephens, Matzke, and Hayes (2019)
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): F. Gregory AshbyAbstractAfter using state-trace analysis to reanalyze results from 63 different categorization studies, Stephens, Matzke, and Hayes (2019) concluded that “the evidence for two distinct category learning systems is much more limited and inconsistent” (p. 14) than Ashby and Valentin (2017) had previously claimed. This reply shows that Stephens et al. (2019) misinterpreted and misapplied state-trace analysis. They report no evidence that favors a single learning system over multiple systems. They acknowledge that t...
Source: Journal of Mathematical Psychology - July 17, 2019 Category: Psychiatry & Psychology Source Type: research
The balance between vision and touch
Publication date: Available online 11 July 2019Source: Journal of Mathematical PsychologyAuthor(s): Devin M. BurnsAbstractAlthough research in augmented perception is booming, little is understood about the information processing characteristics that underlie the integration of these additional signals. In this experiment, Systems Factorial Technology was employed to examine the architecture, stopping rule, and workload capacity of participants when making use of vibration cues from a belt in combination with visual cues on a computer screen. In order to support the application of this vibration belt to improving balance i...
Source: Journal of Mathematical Psychology - July 13, 2019 Category: Psychiatry & Psychology Source Type: research
QTest 2.1: Quantitative testing of theories of binary choice using Bayesian inference
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): Christopher E. Zwilling, Daniel R. Cavagnaro, Michel Regenwetter, Shiau Hong Lim, Bryanna Fields, Yixin ZhangAbstractThis stand-alone tutorial gives an introduction to the QTest 2.1 public domain software package for the specification and statistical analysis of certain order-constrained probabilistic choice models. Like its predecessors, QTest 2.1 allows a user to specify a variety of probabilistic models of binary responses and to carry out state-of-the-art frequentist order-constrained hypothesis tests within a Graphical User I...
Source: Journal of Mathematical Psychology - July 6, 2019 Category: Psychiatry & Psychology Source Type: research
Audiovisual detection at different intensities and delays
We present closed-form solutions for the mean absorption times and absorption probabilities for a Wiener diffusion process with a drift towards a single barrier in the presence of a temporal deadline (A), and numerically improved solutions for the two-barrier model (B). The best description of the data was obtained from the deadline model and substantially outperformed the two-barrier approach. (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - July 2, 2019 Category: Psychiatry & Psychology Source Type: research
Linking the diffusion model and general recognition theory: Circular diffusion with bivariate-normally distributed drift rates
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): Philip L. SmithAbstractThe circular diffusion model is a model of continuous outcome decisions, which are modeled as evidence accumulation by a two-dimensional Wiener diffusion process on the interior of a disk whose bounding circle represents the decision criterion. When there is across-trial variability in the evidence entering the decision process, represented by variability in drift rates, the model predicts that inaccurate responses will be slower than accurate responses, in agreement with, and generalizing, the slow-error pro...
Source: Journal of Mathematical Psychology - June 26, 2019 Category: Psychiatry & Psychology Source Type: research
Editorial Board
Publication date: June 2019Source: Journal of Mathematical Psychology, Volume 90Author(s): (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - June 14, 2019 Category: Psychiatry & Psychology Source Type: research
A tutorial on Dirichlet process mixture modeling
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): Yuelin Li, Elizabeth Schofield, Mithat GönenAbstractBayesian nonparametric (BNP) models are becoming increasingly important in psychology, both as theoretical models of cognition and as analytic tools. However, existing tutorials tend to be at a level of abstraction largely impenetrable by non-technicians. This tutorial aims to help beginners understand key concepts by working through important but often omitted derivations carefully and explicitly, with a focus on linking the mathematics with a practical computation solution for ...
Source: Journal of Mathematical Psychology - May 22, 2019 Category: Psychiatry & Psychology Source Type: research
Information processing architectures within stimulus perception and across the visual fields: An extension of the Systems Factorial Technology to nested architectures
Publication date: Available online 14 May 2019Source: Journal of Mathematical PsychologyAuthor(s): Robin D. Thomas, Gaojie Fan, Heather GambleAbstractSystems Factorial Technology (SFT) is a framework that was developed in order to study how people combine and utilize information from different sources during cognitive processing. By using a series of non-parametric analyses including the mean interaction contrast (MIC) and survivor interaction contrast (SIC), SFT can distinguish between types of information processing architectures (mainly parallel and serial) as well as stopping rules (mainly exhaustive and self-terminati...
Source: Journal of Mathematical Psychology - May 16, 2019 Category: Psychiatry & Psychology Source Type: research
Hierarchical Bayesian mixture models of processing architectures and stopping rules
Publication date: Available online 10 May 2019Source: Journal of Mathematical PsychologyAuthor(s): Gabriel Tillman, Nathan J. EvansAbstractSystems Factorial Technology is a methodology that allows researchers to identify properties of cognitive processing systems, such as the system’s architecture and the decisional stopping rule. It assumes that the cognitive system will use the same architecture and decisional stopping rule on every trial of an experiment. Through simulation, we aim to explore the predictions of models that allow for a mixture of architectures and decisional stopping rules across trials. Our simulation...
Source: Journal of Mathematical Psychology - May 11, 2019 Category: Psychiatry & Psychology Source Type: research
True contextuality in a psychophysical experiment
Publication date: August 2019Source: Journal of Mathematical Psychology, Volume 91Author(s): Víctor H. Cervantes, Ehtibar N. DzhafarovAbstractRecent crowdsourcing experiments have shown that true contextuality of the kind found in quantum mechanics can also be present in human behavior. In these experiments simple human choices were aggregated over large numbers of respondents, with each respondent dealing with a single context (set of questions asked). In this paper we present experimental evidence of contextuality in individual human behavior, in a psychophysical experiment with repeated presentations of visual stimuli ...
Source: Journal of Mathematical Psychology - May 11, 2019 Category: Psychiatry & Psychology Source Type: research
A general approach to prior transformation
We present a general method for setting prior distributions in Bayesian models where parameters of interest are re-parametrized via a functional relationship. We generalize the results of Heck and Wagenmakers (2016) by considering the case where the dimension of the auxiliary parameter space does not equal that of the primary parameter space. We present numerical methods for carrying out prior specification for statistical models that do not admit closed-form solutions. Taken together, these results provide researchers a more complete set of tools for setting prior distributions that could be applied to many cognitive and ...
Source: Journal of Mathematical Psychology - May 5, 2019 Category: Psychiatry & Psychology Source Type: research
Biases in estimating the balance between model-free and model-based learning systems due to model misspecification
In this study, we examined the possible biases in model parameter estimation due to model misspecification of a computational model. In particular, we focused on two features related to choice behavior, the existence of which was implied by the actual choice data but has not been assumed in the widely used computational models. One feature is the forgetting process, which assumes a change in unchosen option values. The other feature is gradual perseveration, which assumes that actions are positively autocorrelated with multiple preceding actions. We simulated cases in which these features relate to the choice process, but ...
Source: Journal of Mathematical Psychology - April 29, 2019 Category: Psychiatry & Psychology Source Type: research
A nonparametric technique for analysis of state-trace functions
Publication date: Available online 18 April 2019Source: Journal of Mathematical PsychologyAuthor(s): Aaron S. Benjamin, Michael L. Griffin, Jeffrey A. DouglasAbstractState-trace analysis provides a direct and transparent way of evaluating a question that is central to many studies of cognitive function: do one or two latent processes underlie performance on a particular task? This evaluation is made using a state-trace plot, which is a bivariate plot of two dependent variables over a dimensional variable that provides the basis for the hypothesized dissociation, and a trace variable, which enables the examination over a ...
Source: Journal of Mathematical Psychology - April 20, 2019 Category: Psychiatry & Psychology Source Type: research
