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  1. Putting perception into action with inverse optimal control for continuous psychophysics

    This article has 2 authors:
    1. Dominik Straub
    2. Constantin A Rothkopf
    This article has been curated by 1 group:
    • Curated by eLife

      Evaluation Summary:

      The paper presents a Bayesian model framework for estimating individual perceptual uncertainty from continuous tracking data, taking into account motor variability, action cost, and possible misestimation of the generative dynamics. While the contribution is mostly technical, the analyses are well done and clearly explained. The paper provides therefore a didactic resource for students wishing to implement similar models on continuous action data.

      (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

    Reviewed by eLife

    This article has 5 evaluationsAppears in 3 listsLatest version Latest activity