Literature DB >> 28185227

Target-present guessing as a function of target prevalence and accumulated information in visual search.

Chad Peltier1, Mark W Becker2.   

Abstract

Target prevalence influences visual search behavior. At low target prevalence, miss rates are high and false alarms are low, while the opposite is true at high prevalence. Several models of search aim to describe search behavior, one of which has been specifically intended to model search at varying prevalence levels. The multiple decision model (Wolfe & Van Wert, Current Biology, 20(2), 121--124, 2010) posits that all searches that end before the observer detects a target result in a target-absent response. However, researchers have found very high false alarms in high-prevalence searches, suggesting that prevalence rates may be used as a source of information to make "educated guesses" after search termination. Here, we further examine the ability for prevalence level and knowledge gained during visual search to influence guessing rates. We manipulate target prevalence and the amount of information that an observer accumulates about a search display prior to making a response to test if these sources of evidence are used to inform target present guess rates. We find that observers use both information about target prevalence rates and information about the proportion of the array inspected prior to making a response allowing them to make an informed and statistically driven guess about the target's presence.

Entities:  

Keywords:  Attention; Low target prevalence; Models of visual search; Visual search

Mesh:

Year:  2017        PMID: 28185227     DOI: 10.3758/s13414-017-1297-6

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


  2 in total

1.  Visual display for surgical targeting: concepts and usability study.

Authors:  Milovan Regodić; Zoltán Bárdosi; Georgi Diakov; Malik Galijašević; Christian F Freyschlag; Wolfgang Freysinger
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-04-08       Impact factor: 2.924

2.  Eye movement feedback fails to improve visual search performance.

Authors:  Chad Peltier; Mark W Becker
Journal:  Cogn Res Princ Implic       Date:  2017-11-22
  2 in total

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