Heinrich René Liesefeld

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).

In everyday life, we often generalize previously learned associations between our actions and their outcomes to novel, but similar situations. The present study aimed to conceptually and directly replicate results reported by Esser et al. (Psychological Research, 87(7), 2249–2258 2023), who reported that action–effect (A–E) learning generalizes to categorically similar stimuli. Yet, the overall picture in the published literature is not overwhelming with regard to such generalization, and hence a replication seems to be of particular importance. We present three experiments. In our conceptual replications (Experiment 1 and 2), we did not find evidence for A–E compatibility effects for either learned or similar stimuli. In the direct replication (Experiment 3), we observed evidence for successful A–E learning, but still failed to replicate generalization to similar stimuli. A critical difference between Experiments 1 and 2 and Experiment 3, however, is that stimulus-stimulus (S-S) learning was not possible in the former two experiments, but in the latter one (as was already acknowledged by Esser et al.). In sum, our results (1) suggest a critical role of S-S learning in this particular design (2) and question whether A–E learning truly generalizes to similar stimuli.

The target article “Illusions of Understanding in the Sciences” by Shiffrin et al. ( Computational Brain & Behavior , 2026) demonstrates how scientists tend to misinterpret correlations by declaring one of the variables as the cause of the other. In our commentary, we discuss that even under controlled experiments it is typically not possible to conclusively identify causal relationships beyond a superficial level.

In many experimental-psychological studies, either the speed or the accuracy of responses could be the primary dependent variable of interest. Often, there is no straightforward choice and this decision is particularly difficult if there are signs of variation in speed–accuracy tradeoff across conditions and/or participants. An apparently well-validated solution to this conundrum is the inverse efficiency score (IES). The general application of IES has never actually been endorsed in the cited sources and recent validation studies show that it does not serve well any of the major purposes to which it has been applied. Its popularity may even have hampered progress on the important methodological issue of how to best combine speed and accuracy measures. The present article traces the history of IES via a literature review and with the aid of contemporary witnesses. This exercise reveals a flaw in the academic culture that could be improved by increasing the value of either checking the original sources or instead being honest about the reliance on second-hand information. The story of IES also exemplifies how ignoring fundamental methodological problems makes practitioners resort to the most accessible solutions, often relying on a simplified appeal to authority and little else.

The slope of the function relating response times to the number of stimuli in a visual-search display is commonly considered a measure of search speed and is extensively used to test theories of visual cognition. Unfortunately, this important measure is confounded in multiple ways so that many classical findings in the literature must be called into question. As a way out of this predicament, we here develop a new technique to measure search speed (data collected in 2022 and 2023): Instead of manipulating the number of stimuli that need to be searched via a set-size manipulation, we achieve the intended purpose by placing the search target at different spatial positions with respect to an a-priori-known search order. Reliably inducing such a search order is the main achievement of the present study, but we also report several additional data patterns that might turn out instrumental for future research on visual attention.