Literature DB >> 19895828

Reaction time distributions constrain models of visual search.

Jeremy M Wolfe1, Evan M Palmer, Todd S Horowitz.   

Abstract

Many experiments have investigated visual search for simple stimuli like colored bars or alphanumeric characters. When eye movements are not a limiting factor, these tasks tend to produce roughly linear functions relating reaction time (RT) to the number of items in the display (set size). The slopes of the RTxset size functions for different searches fall on a continuum from highly efficient (slopes near zero) to inefficient (slopes>25-30ms/item). Many theories of search can produce the correct pattern of mean RTs. Producing the correct RT distributions is more difficult. In order to guide future modeling, we have collected a very large data set (about 112,000 trials) on three tasks: an efficient color feature search, an inefficient search for a 2 among 5s, and an intermediate colorxorientation conjunction search. The RT distributions have interesting properties. For example, target absent distributions overlap target present more than would be expected if the decision to end search were based on a simple elapsed time threshold. Other qualitative properties of the RT distributions falsify some classes of model. For example, normalized RT distributions do not change shape as set size changes as a standard self-terminating model predicts that they should. Copyright 2009 Elsevier Ltd. All rights reserved.

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Mesh:

Year:  2009        PMID: 19895828      PMCID: PMC2891283          DOI: 10.1016/j.visres.2009.11.002

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  33 in total

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Authors:  B McElree; M Carrasco
Journal:  J Exp Psychol Hum Percept Perform       Date:  1999-12       Impact factor: 3.332

Review 2.  Visual search and attention: a signal detection theory approach.

Authors:  P Verghese
Journal:  Neuron       Date:  2001-08-30       Impact factor: 17.173

3.  Termination of a visual search with large display size effects.

Authors:  Denis Cousineau; Richard M Shiffrin
Journal:  Spat Vis       Date:  2004

4.  A computational theory of visual attention.

Authors:  C Bundesen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1998-08-29       Impact factor: 6.237

5.  Just say no: how are visual searches terminated when there is no target present?

Authors:  M M Chun; J M Wolfe
Journal:  Cogn Psychol       Date:  1996-02       Impact factor: 3.468

6.  A test of the deadline model for speed-accuracy tradeoffs.

Authors:  E Ruthruff
Journal:  Percept Psychophys       Date:  1996-01

7.  Eye movements during parallel-serial visual search.

Authors:  G J Zelinsky; D L Sheinberg
Journal:  J Exp Psychol Hum Percept Perform       Date:  1997-02       Impact factor: 3.332

8.  Conjunctive search for one and two identical targets.

Authors:  R Ward; J L McClelland
Journal:  J Exp Psychol Hum Percept Perform       Date:  1989-11       Impact factor: 3.332

9.  A two-stage model of visual search.

Authors:  J E Hoffman
Journal:  Percept Psychophys       Date:  1979-04

10.  A neural theory of attentive visual search: interactions of boundary, surface, spatial, and object representations.

Authors:  S Grossberg; E Mingolla; W D Ross
Journal:  Psychol Rev       Date:  1994-07       Impact factor: 8.934

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  33 in total

Review 1.  Serial vs. parallel models of attention in visual search: accounting for benchmark RT-distributions.

Authors:  Rani Moran; Michael Zehetleitner; Heinrich René Liesefeld; Hermann J Müller; Marius Usher
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2.  What are the shapes of response time distributions in visual search?

Authors:  Evan M Palmer; Todd S Horowitz; Antonio Torralba; Jeremy M Wolfe
Journal:  J Exp Psychol Hum Percept Perform       Date:  2011-02       Impact factor: 3.332

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5.  The effects of increasing target prevalence on information processing during visual search.

Authors:  Hayward J Godwin; Tamaryn Menneer; Kyle R Cave; Michael Thaibsyah; Nick Donnelly
Journal:  Psychon Bull Rev       Date:  2015-04

6.  Decision-related pupil dilation reflects upcoming choice and individual bias.

Authors:  Jan Willem de Gee; Tomas Knapen; Tobias H Donner
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-21       Impact factor: 11.205

7.  Guidance and selection history in hybrid foraging visual search.

Authors:  Jeremy M Wolfe; Matthew S Cain; Avigael M Aizenman
Journal:  Atten Percept Psychophys       Date:  2019-04       Impact factor: 2.199

8.  Age doesn't matter much: hybrid visual and memory search is preserved in older adults.

Authors:  Iris Wiegand; Jeremy M Wolfe
Journal:  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn       Date:  2019-05-03

9.  When is it time to move to the next map? Optimal foraging in guided visual search.

Authors:  Krista A Ehinger; Jeremy M Wolfe
Journal:  Atten Percept Psychophys       Date:  2016-10       Impact factor: 2.199

10.  Macrocircuits: decision networks.

Authors:  Jeffrey D Schall
Journal:  Curr Opin Neurobiol       Date:  2012-12-13       Impact factor: 6.627

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