Literature DB >> 29476331

How to inhibit a distractor location? Statistical learning versus active, top-down suppression.

Benchi Wang1, Jan Theeuwes2.   

Abstract

Recently, Wang and Theeuwes (Journal of Experimental Psychology: Human Perception and Performance, 44(1), 13-17, 2018a) demonstrated the role of lingering selection biases in an additional singleton search task in which the distractor singleton appeared much more often in one location than in all other locations. For this location, there was less capture and selection efficiency was reduced. It was argued that statistical learning induces plasticity within the spatial priority map such that particular locations that are high likely to contain a distractor are suppressed relative to all other locations. The current study replicated these findings regarding statistical learning (Experiment 1) and investigated whether similar effects can be obtained by cueing the distractor location in a top-down way on a trial-by-trial basis. The results show that top-down cueing of the distractor location with long (1,500 ms; Experiment 2) and short stimulus-onset symmetries (SOAs) (600 ms; Experiment 3) does not result in suppression: The amount of capture nor the efficiency of selection was affected by the cue. If anything, we found an attentional benefit (instead of the suppression) for the short SOA. We argue that through statistical learning, weights within the attentional priority map are changed such that one location containing a salient distractor is suppressed relative to all other locations. Our cueing experiments show that this effect cannot be accomplished by active, top-down suppression. Consequences for recent theories of distractor suppression are discussed.

Entities:  

Keywords:  Attentional capture; Cueing; Statistical learning; Suppression; Top-down

Mesh:

Year:  2018        PMID: 29476331     DOI: 10.3758/s13414-018-1493-z

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.199


  36 in total

1.  Learning What Is Irrelevant or Relevant: Expectations Facilitate Distractor Inhibition and Target Facilitation through Distinct Neural Mechanisms.

Authors:  Dirk van Moorselaar; Heleen A Slagter
Journal:  J Neurosci       Date:  2019-07-03       Impact factor: 6.167

Review 2.  Inhibition as a potential resolution to the attentional capture debate.

Authors:  Nicholas Gaspelin; Steven J Luck
Journal:  Curr Opin Psychol       Date:  2018-10-29

3.  Passive exposure attenuates distraction during visual search.

Authors:  Bo-Yeong Won; Joy J Geng
Journal:  J Exp Psychol Gen       Date:  2020-04-06

4.  Oculomotor Inhibition of Salient Distractors: Voluntary Inhibition Cannot Override Selection History.

Authors:  Nicholas Gaspelin; John M Gaspar; Steven J Luck
Journal:  Vis cogn       Date:  2019-04-09

5.  Probing the Neural Mechanisms for Distractor Filtering and Their History-Contingent Modulation by Means of TMS.

Authors:  Carlotta Lega; Oscar Ferrante; Francesco Marini; Elisa Santandrea; Luigi Cattaneo; Leonardo Chelazzi
Journal:  J Neurosci       Date:  2019-08-06       Impact factor: 6.167

6.  Specificity and persistence of statistical learning in distractor suppression.

Authors:  Mark K Britton; Brian A Anderson
Journal:  J Exp Psychol Hum Percept Perform       Date:  2019-12-30       Impact factor: 3.332

7.  Evidence for second-order singleton suppression based on probabilistic expectations.

Authors:  Bo-Yeong Won; Mary Kosoyan; Joy J Geng
Journal:  J Exp Psychol Hum Percept Perform       Date:  2019-01       Impact factor: 3.332

8.  Strategic Distractor Suppression Improves Selective Control in Human Vision.

Authors:  Wieske van Zoest; Christoph Huber-Huber; Matthew D Weaver; Clayton Hickey
Journal:  J Neurosci       Date:  2021-07-08       Impact factor: 6.167

9.  Distractor probabilities modulate flanker task performance.

Authors:  Eli Bulger; Barbara G Shinn-Cunningham; Abigail L Noyce
Journal:  Atten Percept Psychophys       Date:  2020-11-01       Impact factor: 2.199

10.  Combined influence of valence and statistical learning on the control of attention: Evidence for independent sources of bias.

Authors:  Haena Kim; Brian A Anderson
Journal:  Cognition       Date:  2020-12-25
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