Inter-trial effects in visual pop-out search: Factorial comparison of Bayesian updating models.

Zhuanghua Shi,Fredrik Allenmark,Hermann J. Müller

doi:10.1371/journal.pcbi.1006328

Abstract

Many previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton (‘pop-out’) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit ‘top-down’ modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.

Highlights

In everyday life, we are continuously engaged in selecting visual information to achieve our action goals, as the amount of information we receive at any time exceeds the available processing capacity
When a perceptual task is performed repeatedly, performance becomes faster and more accurate when there is little or no change of critical stimulus attributes across consecutive trials. This phenomenon has been explored in previous studies on visual ‘pop-out’ search, showing that participants can find and respond to a unique target object among distractors faster when properties of the target are repeated across trials
A systematic comparison of how well different combinations of models explain the data revealed the best model to assume that perceptual decisions are biased based on the response-critical stimulus property on recent trials, while repetition of the visual dimension in which the target differs from the distractors increases the speed of stimulus processing

Summary

Introduction

We are continuously engaged in selecting visual information to achieve our action goals, as the amount of information we receive at any time exceeds the available processing capacity. A prime piece of evidence in this context is visual search for so-called singleton targets, that is, targets defined by being unique relative to the background of non-target (or distractor) items, whether they differ from the background by one unique feature (simple feature singletons) or a unique conjunction of features (conjunction singletons): singleton search is expedited (or slowed) when critical properties of the stimuli repeat (or change) across trials Such inter-trial effects have been found for repetitions/ switches of, for example, the target-defining color [2,3], size [4], position [5], and, more generally, the target-defining feature dimension [6,7]. The latter has been referred to as the dimension repetition/switch effect, that is: responding to a target repeated from the same dimension (e.g., color) is expedited even when the precise target feature is different across trials (e.g., changing from blue on one trial to red on the ), whereas a target switch from one dimension to another (e.g., from orientation to color) causes a reaction time cost (‘dimension repetition effect’, DRE) [8,9,10]

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Discussion

Conclusion