IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0149217.html
   My bibliography  Save this article

Modelling Visual Change Detection and Identification under Free Viewing Conditions

Author

Listed:
  • Ken McAnally
  • Russell Martin

Abstract

We examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study differed from most previous studies in that observers were allowed to inspect the initial display for 3s, simulating the long inspection times typical of natural viewing, and their eye movements were not constrained. For the majority of observers, combined change detection and identification performance was best modelled by a SDT-based process that assumed that memory resources were distributed across all eight items in our displays. Some observers required a parameter to allow for sometimes making random guesses at the identities of changes they had missed. However, the performance of a small proportion of observers was best explained by a HTT-based model that allowed for lapses of attention.

Suggested Citation

  • Ken McAnally & Russell Martin, 2016. "Modelling Visual Change Detection and Identification under Free Viewing Conditions," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-16, February.
    • Handle: RePEc:plo:pone00:0149217
    DOI: 10.1371/journal.pone.0149217
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149217
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0149217&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0149217?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Steven J. Luck & Edward K. Vogel, 1997. "The capacity of visual working memory for features and conjunctions," Nature, Nature, vol. 390(6657), pages 279-281, November.
    2. Weiwei Zhang & Steven J. Luck, 2008. "Discrete fixed-resolution representations in visual working memory," Nature, Nature, vol. 453(7192), pages 233-235, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fion Choi Hung Lee & Siu Shing Man & Alan Hoi Shou Chan, 2019. "Effects of magnification modes and location cues on visual inspection performance," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuri A. Markov & Natalia A. Tiurina & Igor S. Utochkin, 2018. "Different features are stored independently in visual working memory but mediated by object-based representations," HSE Working papers WP BRP 101/PSY/2018, National Research University Higher School of Economics.
    2. Yuri A. Markov & Igor S. Utochkin, 2017. "The Effect of Object Distinctiveness on Object-Location Binding in Visual Working Memory," HSE Working papers WP BRP 79/PSY/2017, National Research University Higher School of Economics.
    3. J David Timm & Frank Papenmeier, 2019. "Reorganization of spatial configurations in visual working memory: A matter of set size?," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-16, November.
    4. Shaiyan Keshvari & Ronald van den Berg & Wei Ji Ma, 2013. "No Evidence for an Item Limit in Change Detection," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-9, February.
    5. Jack Phu & Michael Kalloniatis & Sieu K Khuu, 2016. "The Effect of Attentional Cueing and Spatial Uncertainty in Visual Field Testing," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-18, March.
    6. Haggar Cohen-Dallal & Isaac Fradkin & Yoni Pertzov, 2018. "Are stronger memories forgotten more slowly? No evidence that memory strength influences the rate of forgetting," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    7. Loic Matthey & Paul M Bays & Peter Dayan, 2015. "A Probabilistic Palimpsest Model of Visual Short-term Memory," PLOS Computational Biology, Public Library of Science, vol. 11(1), pages 1-34, January.
    8. Mohammad Zia Ul Haq Katshu & Giovanni d'Avossa, 2014. "Fine-Grained, Local Maps and Coarse, Global Representations Support Human Spatial Working Memory," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-13, September.
    9. Igor S. Utochkin & Vladislav A. Khvostov & Yulia M. Stakina, 2017. "Ensemble-Based Segmentation in the Perception of Multiple Feature Conjunctions," HSE Working papers WP BRP 78/PSY/2017, National Research University Higher School of Economics.
    10. Jastrzębski, Jan & Ciechanowska, Iwona & Chuderski, Adam, 2018. "The strong link between fluid intelligence and working memory cannot be explained away by strategy use," Intelligence, Elsevier, vol. 66(C), pages 44-53.
    11. Aki Kondo & Jun Saiki, 2012. "Feature-Specific Encoding Flexibility in Visual Working Memory," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-8, December.
    12. Hongwei Tan & Sebastiaan van Dijken, 2023. "Dynamic machine vision with retinomorphic photomemristor-reservoir computing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    13. Robert W. Faff & Sebastian Kernbach, 2021. "A visualisation approach for pitching research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5177-5197, December.
    14. Tullo, Domenico & Faubert, Jocelyn & Bertone, Armando, 2018. "The characterization of attention resource capacity and its relationship with fluid reasoning intelligence: A multiple object tracking study," Intelligence, Elsevier, vol. 69(C), pages 158-168.
    15. Jifan Zhou & Jun Yin & Tong Chen & Xiaowei Ding & Zaifeng Gao & Mowei Shen, 2011. "Visual Working Memory Capacity Does Not Modulate the Feature-Based Information Filtering in Visual Working Memory," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-10, September.
    16. Nathaniel J. S. Ashby & Stephan Dickert & Andreas Glockner, 2012. "Focusing on what you own: Biased information uptake due to ownership," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(3), pages 254-267, May.
    17. Lior Fink & Daniele Papismedov, 2023. "On the Same Page? What Users Benefit from a Desktop View on Mobile Devices," Information Systems Research, INFORMS, vol. 34(2), pages 423-441, June.
    18. Li, Qian & Huang, Zhuowei (Joy) & Christianson, Kiel, 2016. "Visual attention toward tourism photographs with text: An eye-tracking study," Tourism Management, Elsevier, vol. 54(C), pages 243-258.
    19. Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure," Management Science, INFORMS, vol. 66(11), pages 5075-5093, November.
    20. S. Cerreia-Vioglio & F. Maccheroni & M. Marinacci & A. Rustichini, 2017. "Multinomial logit processes and preference discovery: inside and outside the black box," Working Papers 615, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0149217. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.