Modeling inter-trial dynamics in visual search: developing a hierarchical predictive-coding framework of response decisions in a variety of search tasks

• Applicant: Professor Dr. Hermann J. Müller
• Subject Area: General, Cognitive and Mathematical Psychology
• Term: from 2015 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 263727500

The aim of the project is to develop a principled, quantitative framework describing dynamic weighting processes in visual search. In particular, we plan to model different types of inter-trial effects, foremost: the effects of repetitions vs. switches of the target-defining (features and) dimensions in singleton-target search scenarios. These effects have been well characterized qualitatively over the past decades and led to the notion of 'dimension weighting' (which has now become an accepted component of saliency-based accounts of visual search, including J. M. Wolfe's Guided Search model). Although inter-trial dynamics is sometimes still seen as only a 'minor' source of search RT variation, it actually accounts for a large portion of response time (RT) variability even in the most simple, supposedly purely stimulus-driven singleton feature 'pop-out' search (e.g., Found & Müller, 1996), and an even larger portion in singleton conjunction search (e.g., Weidner et al., 2002) - and is arguably more influential than top-down, template-based) influences on search performance (e.g., Kristjánsson et al., 2002). However, while clearly important and well characterized, we are still lacking a principled, computational account of the dynamics of weighting. Here, we propose to develop such an account by combining a new, Bayesian-type perceptual decision and weight updating model with a generative model of RT distributions. In more detail, as singleton feature search is driven largely by target saliency, we propose to use the LATER ('Linear Approach to Threshold with Ergodic Rate') model for modeling the RT distributions. On top of this, we will develop a perceptual model accounting for the influences of prior knowledge on target detection, (feature- and dimension-based) inter-trial effects, as well as dimension-weighting mechanisms. In addition, we will revisit the notion of coactive processing of redundant pop-out signals and examine its relation to inter-trial effects. In a second project phase, we plan to generalize our perceptual-response framework to a singleton search paradigm not limited to the pop-out search, as well as looking for brain correlates of the weighting dynamics.

• DFG Programme: Research Units
• Subproject of: FOR 2293: Active Perception
• Co-Investigator: Professor Dr. Zhuanghua Shi