Literature DB >> 30588570

Biasing Allocations of Attention via Selective Weighting of Saliency Signals: Behavioral and Neuroimaging Evidence for the Dimension-Weighting Account.

Heinrich René Liesefeld1,2, Anna M Liesefeld3, Stefan Pollmann4, Hermann J Müller3,5.   

Abstract

Objects that stand out from the environment tend to be of behavioral relevance, and the visual system is tuned to preferably process these salient objects by allocating focused attention. However, attention is not just passively (bottom-up) driven by stimulus features, but previous experiences and task goals exert strong biases toward attending or actively ignoring salient objects. The core and eponymous assumption of the dimension-weighting account (DWA) is that these top-down biases are not as flexible as one would like them to be; rather, they are subject to dimensional constraints. In particular, DWA assumes that people can often not search for objects that have a particular feature but only for objects that stand out from the environment (i.e., that are salient) in a particular feature dimension. We review behavioral and neuroimaging evidence for such dimensional constraints in three areas: search history, voluntary target enhancement, and distractor handling. The first two have been the focus of research on DWA since its inception and the latter the subject of our more recent research. Additionally, we discuss various challenges to the DWA and its relation to other prominent theories on top-down influences in visual search.

Entities:  

Keywords:  Dimension weighting; Priority map; Review; Task history; Visual search

Year:  2019        PMID: 30588570     DOI: 10.1007/7854_2018_75

Source DB:  PubMed          Journal:  Curr Top Behav Neurosci        ISSN: 1866-3370


  6 in total

1.  Flexible weighting of target features based on distractor context.

Authors:  Jeongmi Lee; Joy J Geng
Journal:  Atten Percept Psychophys       Date:  2020-02       Impact factor: 2.199

Review 2.  Guided Search 6.0: An updated model of visual search.

Authors:  Jeremy M Wolfe
Journal:  Psychon Bull Rev       Date:  2021-02-05

3.  Feature-Based Attentional Weighting and Re-weighting in the Absence of Visual Awareness.

Authors:  Lasse Güldener; Antonia Jüllig; David Soto; Stefan Pollmann
Journal:  Front Hum Neurosci       Date:  2021-01-29       Impact factor: 3.169

4.  Statistical regularities cause attentional suppression with target-matching distractors.

Authors:  Dirk Kerzel; Stanislas Huynh Cong
Journal:  Atten Percept Psychophys       Date:  2020-11-29       Impact factor: 2.199

5.  Statistical learning in visual search reflects distractor rarity, not only attentional suppression.

Authors:  Dirk Kerzel; Chiara Balbiani; Sarah Rosa; Stanislas Huynh Cong
Journal:  Psychon Bull Rev       Date:  2022-04-20

6.  Statistical learning of target selection and distractor suppression shape attentional priority according to different timeframes.

Authors:  Valeria Di Caro; Chiara Della Libera
Journal:  Sci Rep       Date:  2021-07-02       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.