September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Tuned normalization in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior
Author Affiliations & Notes
  • Brian Maniscalco
    Department of Bioengineering, University of California Riverside
  • Brian Odegaard
    Department of Psychology, University of California Los Angeles
  • Piercesare Grimaldi
    Departments of Psychiatry and Biobehavioral Sciences, University of California Los Angeles
  • Seong Hah Cho
    Department of Psychology, University of Hong Kong
  • Michele A. Basso
    Departments of Psychiatry and Biobehavioral Sciences, University of California Los Angeles
    Department of Neurobiology, University of California Los Angeles
    Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles
    Brain Research Institute, University of California Los Angeles
  • Hakwan Lau
    Department of Psychology, University of California Los Angeles
    Department of Psychology, University of Hong Kong
    Brain Research Institute, University of California Los Angeles
    State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong
  • Megan A.K. Peters
    Department of Bioengineering, University of California Riverside
    Department of Psychology, University of California Los Angeles
    Interdepartmental Graduate Program in Neuroscience, University of California, Riverside
    Department of Psychology, University of California, Riverside
Journal of Vision September 2019, Vol.19, 289b. doi:https://doi.org/10.1167/19.10.289b
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Brian Maniscalco, Brian Odegaard, Piercesare Grimaldi, Seong Hah Cho, Michele A. Basso, Hakwan Lau, Megan A.K. Peters; Tuned normalization in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior. Journal of Vision 2019;19(10):289b. doi: https://doi.org/10.1167/19.10.289b.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Current dominant views hold that perceptual confidence – e.g., in visual perceptual decisions – reflects the probability that the relevant decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being correct can be dissociated. An alternative hypothesis suggests that confidence instead reflects the magnitude of evidence in favor of a perceptual decision while being relatively insensitive to the evidence opposing the decision. We considered how this alternative hypothesis might be biologically instantiated by developing a simple leaky competing accumulator neural network model incorporating a known property of sensory neurons: tuned normalization. The key idea of the model is that each accumulator neuron’s normalization ‘tuning’ dictates its contribution to perceptual decisions versus confidence judgments. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature, where confidence and decision accuracy in visual tasks were shown to dissociate -- and that the differential contribution a neuron makes to decisions versus confidence judgments based on its normalization tuning is vital to capturing some of these effects. One critical prediction of the model is that systematic variability in normalization tuning exists not only in sensory cortices but also in the decision-making circuitry. We tested and validated this prediction in macaque superior colliculus (SC; a region implicated in decision-making). The confirmation of this novel prediction provides direct support for our model. We will also present pilot data from an exploratory fMRI paradigm investigating this Tuned Normalization model’s predictions in humans. These findings suggest that the brain has developed and implements this alternative, heuristic theory of perceptual confidence computation by capitalizing on the diversity of neural resources available

Acknowledgement: This work was partially supported by the National Institutes of Health (R01NS08862801 to HL R01EY13692 to MAB). 
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×