The following is a summary of “Hierarchical Bayesian perceptual template modeling of mechanisms of spatial attention in central and peripheral cuing,” published in the February 2023 issue of Ophthalmology by Lu, et al.
For a study, the external noise paradigm and perceptual template model (PTM) were used by researchers to analyze observer properties and mechanisms of observer state changes in various research domains, with a focus on individual-level analysis.
They developed a new hierarchical Bayesian perceptual template model (HBPTM) to model the trial-by-trial data from all individuals and conditions in a published spatial cuing study within a single structure. The performance of the HBPTM was compared to that of a Bayesian Inference Procedure (BIP), which separately infers the posterior distributions of the model parameters for each individual subject without the hierarchical structure. The HBPTM enabled the computation of the joint posterior distribution of the hyperparameters and parameters at the population, observer, and experiment levels, allowing for statistical inferences at all these levels. The study also included a large simulation study that varied the number of observers and trials in each condition, demonstrating the advantage of the HBPTM over the BIP across all the simulated datasets.
In the spatial cuing study, the HBPTM showed that the effect of cue validity on reaction times depended on individual observer properties, such as spatial attention allocation and perceptual sensitivity. They also found that the cuing effect was larger in experiments with larger cue-target distances and shorter stimulus durations.
Overall, the HBPTM and its extensions can be applied to model data from the external noise paradigm in various domains and enable predictions of human performance at both the population and individual levels.