Inter-trial effects in priming of pop-out: Comparison of computational updating models

Allenmark, Fredrik; Gökçe, Ahu; Geyer, Thomas; Zinchenko, Artyom; Müller, Hermann J.; Shi, Zhuanghua · 2021 · OpenAlex-citations

DOI: 10.1371/journal.pcbi.1009332

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Summary

This study investigates the computational mechanisms underlying inter-trial priming effects in visual search, specifically within the "priming of pop-out" (PoP) paradigm. While previous research established that repeating target features, positions, or responses speeds up reaction times, the specific cognitive processes driving these long-lasting effects remained unclear. The authors aimed to determine whether these effects arise from changes in evidence accumulation rates (processing efficiency) or decision biases, and to characterize how the cognitive system updates internal predictive models based on stimulus history. The researchers applied a modeling framework combining evidence accumulation (EA) models—specifically the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model—with various computational updating rules. They analyzed response time data from a previously published PoP study involving sparse search displays where target and distractor colors swapped randomly across trials. The experimental design allowed for the examination of three distinct inter-trial effects: repetitions of the target-defining color, the target position, and the response-critical feature (a notch orientation). The authors performed a systematic comparison of over 1,000 model combinations to identify which EA parameter (drift rate or starting point) and which updating rule best accounted for the observed n-back temporal profiles of these priming effects. The results demonstrated that the modeling framework accurately predicted the temporal profiles of inter-trial effects. Crucially, the study found that different mechanisms underlie different types of priming. Target color- and position-based inter-trial effects were best explained by the redistribution of a limited-capacity attentional weight resource, which determines the evidence accumulation rate. This suggests that prior exposure to specific features or locations enhances the efficiency of sensory processing. In contrast, response-based inter-trial effects were best explained by a bias in the starting point of the evidence accumulation process, favoring the response associated with the previous trial. This response bias was found to be largely tied to the position of the target, indicating that stimulus-response bindings are spatially specific. These findings elucidate how the cognitive system optimizes task performance by continually tracking and updating separate internal models for stimulus and response parameters. The study confirms that feature and position priming operate through efficient attentional weighting, while response priming operates through decision biases linked to spatial context. This distinction clarifies the nature of the memory traces responsible for inter-trial effects, demonstrating that the brain maintains distinct, dynamically updated predictive models for perceptual processing and motor response selection.

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• visual search