Distractor suppression leads to reduced flanker interference

Abstract

Recent studies using the additional singleton paradigm have shown that regularities in distractor locations can cause biases in the spatial priority map, such that attentional capture by salient singletons is reduced for locations that are likely to contain distractors. It has been suggested that this type of suppression is proactive (i.e., occurring before display onset). The current study replicated the original findings using an online version of the task. To further assess the suppression of high-probability locations, we employed a congruence manipulation similar to the traditional flanker effect, where distractors could be either congruent or incongruent with the response to the target. Experiment 1 shows that through statistical learning distractor suppression reduces the interference from incongruent distractors, as participants made less errors in high-probability versus low-probability conditions. In Experiment 2, participants were forced to search for a specific target feature (the so-called feature-search mode), which is assumed to allow participants to ignore distractors in a top-down manner. Yet even when this “top-down” search mode was employed, there was still a congruence effect when the distractor singleton was presented at the low-probability but not at the high-probability location. The absence, but not reversal, of a congruence effect at the high-probability location also further indicates that this distractor suppression mechanism is proactive. The results indicate that regardless of the search mode used, there is suppression of the high-probability location indicating that this location competes less for attention within the spatial priority map than all other locations.

Independence of implicitly guided attention from goal-driven oculomotor control

“…Experiment 1 was conducted using an online platform ( Pavlovia.org ) during a period when in-person testing was halted due to COVID-19. The online platform was validated by a recent publication that revealed LPL in online testing (Ivanov & Theeuwes, 2021 ). In addition, we conducted a pilot experiment to validate online testing.…”

Target templates and the time course of distractor location learning

“…These findings indicate that the high-probability location was suppressed relative to the other display locations, attenuating the salience signal of stimuli presented at that location (Ferrante et al, 2018;Ivanov & Theeuwes, 2021;Wang & Theeuwes, 2018b, 2018a. Presumably, the weights within the spatial priority map, based on which attention is deployed, were adjusted so that the high-probability location was assigned a low priority to prevent distractor capture (Ferrante et al, 2018;Ivanov & Theeuwes, 2021;Wang & Theeuwes, 2018a, 2018b. Further research demonstrated that distractor location learning is modulated not only by learning of spatial, but also of nonspatial distractor regularities (Failing et al, 2019;van Moorselaar et al, 2020).…”

“…Second, when the target was presented at the high-probability location of the distractor, target selection was impaired (but see Allenmark et al, 2019;van Moorselaar et al, 2021). These findings indicate that the high-probability location was suppressed relative to the other display locations, attenuating the salience signal of stimuli presented at that location (Ferrante et al, 2018;Ivanov & Theeuwes, 2021;Wang & Theeuwes, 2018b, 2018a. Presumably, the weights within the spatial priority map, based on which attention is deployed, were adjusted so that the high-probability location was assigned a low priority to prevent distractor capture (Ferrante et al, 2018;Ivanov & Theeuwes, 2021;Wang & Theeuwes, 2018a, 2018b.…”

“…Only a few studies have examined the effects of the target template (i.e., search for a feature-specific target vs. shape singleton) on distractor location learning (Ivanov & Theeuwes, 2021;Wang & Theeuwes, 2018c). Wang and Theeuwes (2018) hypothesized that in feature search mode (Bacon & Egeth, 1994), distractors can be ignored by top-down processes, eliminating the need for distractor location learning.…”

Another Warning about Median Reaction Time --- Version of 19 Jan 2022

“…In addition, trial frequencies have often been varied across conditions to explore a variety of cognitive processes by investigating their interactions with probability (e.g., Broadbent & Gregory, 1965;Den Heyer, Briand, & Dannenbring, 1983;Miller & Pachella, 1973;Sanders, 1970;Theios, Smith, Haviland, Traupmann, & Moy, 1973). Currently, trial frequencies are commonly varied in studies of spatial and temporal statistical learning (e.g., Flowers, Palitsky, Sullivan, & Peterson, 2021;Gibson, Pauszek, Trost, & Wenger, 2021;Liesefeld & Müller, 2021;Vadillo, Giménez-Fernández, Beesley, Shanks, & Luque, 2021), the modulation of attentional control processes by environmental contingencies (e.g., Cochrane, Simmering, & Green, 2021;Huang, Theeuwes, & Donk, 2021;Kang & Chiu, 2021), action-outcome contingency learning (e.g., Gao & Gozli, 2021), adaptation to the frequency of congruent versus incongruent information (e.g., Bausenhart, Ulrich, & Miller, 2021;Ivanov & Theeuwes, 2021;Thomson, Simone, & Watter, 2021), and between-task resource sharing (e.g., Miller & Tang, 2021), to name just a few areas. Unfortunately, median bias is still sometimes overlooked and may contaminate published comparisons of conditions with different POWER OF MEDIAN RTS 8 trial frequencies (e.g., Bulger, Shinn-Cunningham, & Noyce, 2021).…”