1
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Priors in perception: Top-down modulation, Bayesian perceptual learning rate, and prediction error minimization.

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          I discuss top-down modulation of perception in terms of a variable Bayesian learning rate, revealing a wide range of prior hierarchical expectations that can modulate perception. I then switch to the prediction error minimization framework and seek to conceive cognitive penetration specifically as prediction error minimization deviations from a variable Bayesian learning rate. This approach retains cognitive penetration as a category somewhat distinct from other top-down effects, and carves a reasonable route between penetrability and impenetrability. It prevents rampant, relativistic cognitive penetration of perception and yet is consistent with the continuity of cognition and perception.

          Related collections

          Author and article information

          Journal
          Conscious Cogn
          Consciousness and cognition
          Elsevier BV
          1090-2376
          1053-8100
          January 2017
          : 47
          Affiliations
          [1 ] Philosophy & Cognition Lab, Philosophy Department, Monash University, Melbourne, VIC 3800, Australia. Electronic address: Jakob.Hohwy@monash.edu.
          Article
          S1053-8100(16)30277-X
          10.1016/j.concog.2016.09.004
          27663763

          Comments

          Comment on this article