IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0041136.html
   My bibliography  Save this article

Selective Attention Increases Choice Certainty in Human Decision Making

Author

Listed:
  • Leopold Zizlsperger
  • Thomas Sauvigny
  • Thomas Haarmeier

Abstract

Choice certainty is a probabilistic estimate of past performance and expected outcome. In perceptual decisions the degree of confidence correlates closely with choice accuracy and reaction times, suggesting an intimate relationship to objective performance. Here we show that spatial and feature-based attention increase human subjects' certainty more than accuracy in visual motion discrimination tasks. Our findings demonstrate for the first time a dissociation of choice accuracy and certainty with a significantly stronger influence of voluntary top-down attention on subjective performance measures than on objective performance. These results reveal a so far unknown mechanism of the selection process implemented by attention and suggest a unique biological valence of choice certainty beyond a faithful reflection of the decision process.

Suggested Citation

  • Leopold Zizlsperger & Thomas Sauvigny & Thomas Haarmeier, 2012. "Selective Attention Increases Choice Certainty in Human Decision Making," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
  • Handle: RePEc:plo:pone00:0041136
    DOI: 10.1371/journal.pone.0041136
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0041136
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0041136&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0041136?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. Stefano Baldassi & Nicola Megna & David C Burr, 2006. "Visual Clutter Causes High-Magnitude Errors," PLOS Biology, Public Library of Science, vol. 4(3), pages 1-1, February.
    2. Max Berniker & Martin Voss & Konrad Kording, 2010. "Learning Priors for Bayesian Computations in the Nervous System," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-9, September.
    3. Yaffa Yeshurun & Marisa Carrasco, 1998. "Attention improves or impairs visual performance by enhancing spatial resolution," Nature, Nature, vol. 396(6706), pages 72-75, November.
    4. Adam Kepecs & Naoshige Uchida & Hatim A. Zariwala & Zachary F. Mainen, 2008. "Neural correlates, computation and behavioural impact of decision confidence," Nature, Nature, vol. 455(7210), pages 227-231, September.
    5. Konrad P. Körding & Daniel M. Wolpert, 2004. "Bayesian integration in sensorimotor learning," Nature, Nature, vol. 427(6971), pages 244-247, January.
    Full references (including those not matched with items on IDEAS)

    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. Adam N Sanborn & Ulrik R Beierholm, 2016. "Fast and Accurate Learning When Making Discrete Numerical Estimates," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-28, April.
    2. Jannes Jegminat & Maya A Jastrzębowska & Matthew V Pachai & Michael H Herzog & Jean-Pascal Pfister, 2020. "Bayesian regression explains how human participants handle parameter uncertainty," PLOS Computational Biology, Public Library of Science, vol. 16(5), pages 1-23, May.
    3. Luigi Acerbi & Sethu Vijayakumar & Daniel M Wolpert, 2014. "On the Origins of Suboptimality in Human Probabilistic Inference," PLOS Computational Biology, Public Library of Science, vol. 10(6), pages 1-23, June.
    4. Martin Graziano & Mariano Sigman, 2009. "The Spatial and Temporal Construction of Confidence in the Visual Scene," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-10, March.
    5. Luigi Acerbi & Sethu Vijayakumar & Daniel M Wolpert, 2017. "Target Uncertainty Mediates Sensorimotor Error Correction," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-21, January.
    6. William T Adler & Wei Ji Ma, 2018. "Comparing Bayesian and non-Bayesian accounts of human confidence reports," PLOS Computational Biology, Public Library of Science, vol. 14(11), pages 1-34, November.
    7. Luigi Acerbi & Daniel M Wolpert & Sethu Vijayakumar, 2012. "Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-19, November.
    8. Shih-Wei Wu & Maria F Dal Martello & Laurence T Maloney, 2009. "Sub-Optimal Allocation of Time in Sequential Movements," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-13, December.
    9. Micha Heilbron & Florent Meyniel, 2019. "Confidence resets reveal hierarchical adaptive learning in humans," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-24, April.
    10. Manuel Rausch & Michael Zehetleitner, 2019. "The folded X-pattern is not necessarily a statistical signature of decision confidence," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-18, October.
    11. Geonhui Lee & Woong Choi & Hanjin Jo & Wookhyun Park & Jaehyo Kim, 2020. "Analysis of motor control strategy for frontal and sagittal planes of circular tracking movements using visual feedback noise from velocity change and depth information," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    12. Wen-Hao Zhang & Si Wu & Krešimir Josić & Brent Doiron, 2023. "Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    13. Seth W. Egger & Stephen G. Lisberger, 2022. "Neural structure of a sensory decoder for motor control," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    14. Laurence Aitchison & Dan Bang & Bahador Bahrami & Peter E Latham, 2015. "Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-23, October.
    15. Ronald H Stevens & Trysha L Galloway, 2022. "Can machine learning be used to forecast the future uncertainty of military teams?," The Journal of Defense Modeling and Simulation, , vol. 19(2), pages 145-158, April.
    16. Wan-Yu Shih & Hsiang-Yu Yu & Cheng-Chia Lee & Chien-Chen Chou & Chien Chen & Paul W. Glimcher & Shih-Wei Wu, 2023. "Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-24, December.
    17. Andrea Insabato & Mario Pannunzi & Gustavo Deco, 2017. "Multiple Choice Neurodynamical Model of the Uncertain Option Task," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-29, January.
    18. Tim Genewein & Eduard Hez & Zeynab Razzaghpanah & Daniel A Braun, 2015. "Structure Learning in Bayesian Sensorimotor Integration," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-27, August.
    19. Ofri Raviv & Merav Ahissar & Yonatan Loewenstein, 2012. "How Recent History Affects Perception: The Normative Approach and Its Heuristic Approximation," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-10, October.
    20. Brocas, Isabelle & Carrillo, Juan D., 2012. "From perception to action: An economic model of brain processes," Games and Economic Behavior, Elsevier, vol. 75(1), pages 81-103.

    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:pone00:0041136. 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.