ArticleAttention, perception & psychophysics2026
Estimating stimulus-processing time via position slopes in visual search.
Article in Attention, perception & psychophysics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Existing approaches to measure the time needed to process a single stimulus have confounded the measure with other time-consuming processes, such as initiation of the response, and neglect the massively parallel processing abilities of the visual system. Conversely, traditional set-size manipulations in visual search yield flawed estimates of stimulus-processing time, mainly because the number of actually processed stimuli is typically unknown. We have recently developed the systematic-search paradigm, a visual-search paradigm that overcomes this limitation and potentially provides a valid measure of stimulus-processing time. Its core idea is to bring the order of search under experimental control, so that the number of processed stimuli is determined by the position of the target on the current trial. We then extract the slope of the linear function relating target position (and therefore the number of processed stimuli) to response times. With this approach, all extraneous processing times are relegated to the intercept of the function. The present study provides a further validation of this slope-measure by showing that it reflects the complexity of the visual stimuli (Exp. 1), but is robust against changes in the complexity of the response (Exp. 2). All raw data, analysis code, preregistrations, and research materials are available online ( https://osf.io/42mxh/ ). OPEN PRACTICES STATEMENT: In both experiments, we report how we determined our sample size, all data exclusions (if any), all manipulations, and all measures in the study. The experiments' designs and analyses were preregistered. All trial-level raw data, analysis code, preregistrations and research materials are available online ( https://osf.io/42mxh/ ). Direct links to the preregistrations are https://osf.io/tbk8s/ (Exp. 1) and https://osf.io/va98q/ (Exp. 2).
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