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Tracking human skill learning with a hierarchical Bayesian sequence model

Noémi Éltető, Dezső Nemeth, Karolina Janacsek, Peter Dayan
doi: https://doi.org/10.1101/2022.01.27.477977

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doi 
https://doi.org/10.1101/2022.01.27.477977
History 
  • January 27, 2022.
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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Author Information

  1. Noémi Éltető1,*,
  2. Dezső Nemeth2,3,4,
  3. Karolina Janacsek5,3 and
  4. Peter Dayan1,6
  1. 1Max Planck Institute for Biological Cybernetics, Tübingen, Germany
  2. 2Lyon Neuroscience Research Center, Université de Lyon, Lyon, France
  3. 3Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
  4. 4Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
  5. 5Centre for Thinking and Learning, Institute for Lifecourse Development, Universtiy of Greenwich, London, United Kingdom
  6. 6University of Tübingen, Tübingen, Germany
  1. ↵*noemi.elteto{at}tuebingen.mpg.de
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Posted January 27, 2022.
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Tracking human skill learning with a hierarchical Bayesian sequence model
Noémi Éltető, Dezső Nemeth, Karolina Janacsek, Peter Dayan
bioRxiv 2022.01.27.477977; doi: https://doi.org/10.1101/2022.01.27.477977
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