Dataset Information

Modeling the effect of selection history on pop-out visual search.

ABSTRACT: While attentional effects in visual selection tasks have traditionally been assigned "top-down" or "bottom-up" origins, more recently it has been proposed that there are three major factors affecting visual selection: (1) physical salience, (2) current goals and (3) selection history. Here, we look further into selection history by investigating Priming of Pop-out (POP) and the Distractor Preview Effect (DPE), two inter-trial effects that demonstrate the influence of recent history on visual search performance. Using the Ratcliff diffusion model, we model observed saccadic selections from an oddball search experiment that included a mix of both POP and DPE conditions. We find that the Ratcliff diffusion model can effectively model the manner in which selection history affects current attentional control in visual inter-trial effects. The model evidence shows that bias regarding the current trial's most likely target color is the most critical parameter underlying the effect of selection history. Our results are consistent with the view that the 3-item color-oddball task used for POP and DPE experiments is best understood as an attentional decision making task.

SUBMITTER: Tseng YC

PROVIDER: S-EPMC3940711 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Modeling the effect of selection history on pop-out visual search.

Tseng Yuan-Chi YC Glaser Joshua I JI Caddigan Eamon E Lleras Alejandro A

PloS one 20140303 3

While attentional effects in visual selection tasks have traditionally been assigned "top-down" or "bottom-up" origins, more recently it has been proposed that there are three major factors affecting visual selection: (1) physical salience, (2) current goals and (3) selection history. Here, we look further into selection history by investigating Priming of Pop-out (POP) and the Distractor Preview Effect (DPE), two inter-trial effects that demonstrate the influence of recent history on visual sea ...[more]

PMID: 24595032

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Project description: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.

Project description:The label-feedback hypothesis states that language can modulate visual processing. In particular, hearing or reading aloud target names (labels) speeds up performance in visual search tasks by facilitating target detection and such advantage is often measured against a condition where the target name is shown visually (i.e. via the same modality as the search task). The current study conceptually complements and expands previous investigations. The effect of a multimodal label presentation (i.e., an audio+visual, AV, priming label) in a visual search task is compared to that of a multimodal (i.e. white noise+visual, NV, label) and two unimodal (i.e. audio, A, label or visual, V, label) control conditions. The name of a category (i.e. a label at the superordinate level) is used as a cue, instead of the more commonly used target name (a basic level label), with targets belonging to one of three categories: garments, improper weapons, and proper weapons. These categories vary for their structure, improper weapons being an ad hoc category (i.e. context-dependent), unlike proper weapons and garments. The preregistered analysis shows an overall facilitation of visual search performance in the AV condition compared to the NV condition, confirming that the label-feedback effect may not be explained away by the effects of multimodal stimulation only and that it extends to superordinate labels. Moreover, exploratory analyses show that such facilitation is driven by the garments and proper weapons categories, rather than improper weapons. Thus, the superordinate label-feedback effect is modulated by the structural properties of a category. These findings are consistent with the idea that the AV condition prompts an "up-regulation" of the label, a requirement for enhancing the label's beneficial effects, but not when the label refers to an ad hoc category. They also highlight the peculiar status of the category of improper weapons and set it apart from that of proper weapons.

Dataset Information

Modeling the effect of selection history on pop-out visual search.

Publications

Modeling the effect of selection history on pop-out visual search.

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