Probability cueing of singleton-distractor regions in visual search: the locus of spatial distractor suppression is determined by colour swapping

Allenmark, Fredrik; Zhang, Bei; Liesefeld, Heinrich René; Shi, Zhuanghua; Müller, Hermann J.

doi:10.1080/13506285.2019.1666953

Cited by 37 publications

(65 citation statements)

References 55 publications

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“…We first conducted a behavioral experiment to examine how distractor expectations at the feature and spatial level may interact in reducing distractor interference. We specifically predicted that suppression at high probability distractor locations would become specific to distractors (i.e., not affect target processing) when distractors are assigned unique and fixed spatial frequencies, as has been shown previously using shapes and colors (Allenmark et al, 2019;Zhang et al, 2019). To this end, observers (N = 18) performed a visual search task in which the distractor and the target either had the same spatial frequency and only differed in orientation (referred to as Distractor predictable Target predictable (DpTp) identical condition), or differed both in spatial frequency and orientation.…”

Section: Experiments 1 -Is Spatial Suppression Modulated By Feature Expectations?mentioning

confidence: 97%

“…Indeed, in this study, it was also found that even targets occurring at the likely distractor location were inhibited, as reflected by slower response times. Behavioral studies have also shown, however, that when targets and distractors are assigned unique and fixed features, the suppression at high probability distractor locations becomes specific to distractors (Allenmark, Zhang, Liesefeld, Shi, & Müller, 2019;Zhang, Allenmark, Liesefeld, Shi, & Muller, 2019), indicative of feature-based inhibition. Together, these findings suggest that the locus of distractor learning in the processing hierarchy is flexible and depends on the extent to which expectations are location-and/or featurespecific.…”

Section: Introductionmentioning

confidence: 99%

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Neural mechanisms underlying expectation-dependent inhibition of distracting information

Moorselaar

Lampers

Cordesius

et al. 2020

eLife

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Predictions based on learned statistical regularities in the visual world have been shown to facilitate attention and goal-directed behavior by sharpening the sensory representation of goal-relevant stimuli in advance. Yet, how the brain learns to ignore predictable goal-irrelevant or distracting information is unclear. Here, we used EEG and a visual search task in which the predictability of a distractor’s location and/or spatial frequency was manipulated to determine how spatial and feature distractor expectations are neurally implemented and reduce distractor interference. We find that expected distractor features could not only be decoded pre-stimulus, but their representation differed from the representation of that same feature when part of the target. Spatial distractor expectations did not induce changes in preparatory neural activity, but a strongly reduced Pd, an ERP index of inhibition. These results demonstrate that neural effects of statistical learning critically depend on the task relevance and dimension (spatial, feature) of predictions.

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Section: Experiments 1 -Is Spatial Suppression Modulated By Feature Expectations?mentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Neural mechanisms underlying expectation-dependent inhibition of distracting information

Moorselaar

Lampers

Cordesius

et al. 2020

eLife

View full text Add to dashboard Cite

show abstract

“…As discussed above, (bottom-up) target saliency is influenced by target/nontarget feature contrast, display density, and the target's distance to fixation. The effectiveness of top-down control via dimension weighting depends on factors such as availability of cognitive resources and predictability of and experience with various properties of the search display (e.g., Allenmark, Wang, Liesefeld, Shi, & Müller, 2019). Finally, priority guidance is most beneficial if the display contains many items.…”

Section: Resolving Current Controversiesmentioning

confidence: 99%

A theoretical attempt to revive the serial/parallel-search dichotomy

Liesefeld

Müller

2019

Atten Percept Psychophys

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A core distinction in Anne Treisman's feature-integration theory (FIT) is in that between parallel and serial search. We outline this dichotomy and selectively review the reasons why it has largely been abandoned in the visual-search community-namely, its theoretical dispensability, failure to find reliable yardsticks for differentiating parallel and serial search, and falsification of core predictions. We then go on to introduce a new theoretical framework that, we argue, clears up some of the theoretical confusion by merging FIT with various competing theories. This framework's core feature is the distinction between and characterization of two fundamentally different search modes: one in which attention is guided to a single item via a priority map (priority guidance), and one in which clumps of multiple items are scanned in parallel in a spatially systematic order (clump scanning). Finally, we will elaborate how this new theoretical framework can resolve current controversies in the literature and how it relates to other existing theories. We (somewhat optimistically) believe that the outcome of this theoretical exercise is a unification of theories of visual search that can explain, or at least is consistent with, all phenomena reported in the visual-search literature that have previously been accounted for by various conflicting theories.

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“…This effect is attributable primarily to a proactive suppression of frequent distractor locations: oculomotor capture is less likely when distractors occur at frequent (vs. rare) locations (Di Caro et al 2019;Wang et al 2019a;Sauter et al 2020); and for frequent locations, an anticipatory suppressionrelated event-related component (P D ) is observed (Wang et al 2019b). However, how suppression of likely distractor locations is implemented is influenced by how distractors are defined relative to the target (Sauter et al 2018;Allenmark et al 2019;Failing et al 2019;Zhang et al 2019;Liesefeld and Müller 2020): if target and distractor are defined in the same dimension (e.g., target and distractor are both orientation-defined), suppression appears to work at a supra-dimensional level of 'attentionalpriority' computation, impacting both distractor and target signals -as compared to a level of dimension-specific 'feature-contrast' computation when they are defined in a different dimension (orientation-defined target, colour-defined distractor), in which case suppression typically impacts only distractor signals.…”

Section: Introductionmentioning

confidence: 99%

Statistical learning of frequent distractor locations in visual search involves regional signal suppression in early visual cortex

Zhang

Weidner

Allenmark

et al. 2021

Preprint

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Observers can learn the locations where salient distractors appear frequently to reduce potential interference - an effect attributed to better suppression of distractors at frequent locations. But how distractor suppression is implemented in the visual cortex and frontoparietal attention networks remains unclear. We used fMRI and a regional distractor-location learning paradigm (Sauter et al. 2018, 2020) with two types of distractors defined in either the same (orientation) or a different (colour) dimension to the target to investigate this issue. fMRI results showed that BOLD signals in early visual cortex were significantly reduced for distractors (as well as targets) occurring at the frequent versus rare locations, mirroring behavioural patterns. This reduction was more robust with same-dimension distractors. Crucially, behavioural interference was correlated with distractor-evoked visual activity only for same- (but not different-) dimension distractors. Moreover, with different- (but not same-) dimension distractors, a colour-processing area within the fusiform gyrus was activated more when a colour distractor was present versus absent and with a distractor occurring at a rare versus frequent location. These results support statistical learning of frequent distractor locations involving regional suppression in the early visual cortex and point to differential neural mechanisms of distractor handling with different- versus same-dimension distractors.

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Probability cueing of singleton-distractor regions in visual search: the locus of spatial distractor suppression is determined by colour swapping

Cited by 37 publications

References 55 publications

Neural mechanisms underlying expectation-dependent inhibition of distracting information

Neural mechanisms underlying expectation-dependent inhibition of distracting information

A theoretical attempt to revive the serial/parallel-search dichotomy

Statistical learning of frequent distractor locations in visual search involves regional signal suppression in early visual cortex

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