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Publications of year 2020
Articles in journals
  1. Parvaneh Adibpour, Jessica Lebenberg, Claire Kabdebon, Ghislaine Dehaene-Lambertz, and Jessica Dubois. Anatomo-functional correlates of auditory development in infancy. Developmental Cognitive Neuroscience, pp 100752, 2020. [PDF] [bibtex-entry]


  2. Claire HC Chang, Stanislas Dehaene, Denise H Wu, Wen-Jui Kuo, and Christophe Pallier. Cortical encoding of linguistic constituent with and without morphosyntactic cues. Cortex, 2020. [PDF] [bibtex-entry]


  3. Lorenzo Ciccione and Stanislas Dehaene. Grouping mechanisms in numerosity perception. 2020. [WWW] [PDF] [bibtex-entry]


  4. Dror Dotan and Stanislas Dehaene. Parallel and serial processes in number-to-quantity conversion. Cognition, 2020. [bibtex-entry]


  5. Daria La Rocca, Philippe Ciuciu, Denis-Alexander Engemann, and Virginie Van Wassenhove. Emergence of $\beta$ and $\gamma$ networks following multisensory training. NeuroImage, 206:116313, 2020. [PDF] [bibtex-entry]


  6. Diana López-Barroso, Michel Thiebaut de Schotten, José Morais, Régine Kolinsky, Lucia W Braga, Alexandre Guerreiro-Tauil, Stanislas Dehaene, and Laurent Cohen. Impact of literacy on the functional connectivity of vision and language related networks. NeuroImage, pp 116722, 2020. [WWW] [bibtex-entry]


  7. Maxime Maheu, Florent Meyniel, and Stanislas Dehaene. Rational arbitration between statistics and rules in human sequence learning. bioRxiv, 2020. [WWW] [PDF]
    Abstract: Detecting and learning temporal regularities is essential to accurately predict the future. Past research indicates that humans are sensitive to two types of sequential regularities: deterministic rules, which afford sure predictions, and statistical biases, which govern the probabilities of individual items and their transitions. How does the human brain arbitrate between those two types? We used finger tracking to continuously monitor the online build-up of evidence, confidence, false alarms and changes-of-mind during sequence learning. All these aspects of behaviour conformed tightly to a hierarchical Bayesian inference model with distinct hypothesis spaces for statistics and rules, yet linked by a single probabilistic currency. Alternative models based either on a single statistical mechanism or on two non-commensurable systems were rejected. Our results indicate that a hierarchical Bayesian inference mechanism, capable of operating over several distinct hypothesis spaces, underlies the human capability to learn both statistics and rules.
    [bibtex-entry]


  8. George A Mashour, Pieter Roelfsema, Jean-Pierre Changeux, and Stanislas Dehaene. Conscious Processing and the Global Neuronal Workspace Hypothesis. Neuron, 105(5):776--798, 2020. [WWW] [PDF] [bibtex-entry]


  9. Theofanis I. Panagiotaropoulos, Abhilash Dwarakanath, and Vishal Kapoor. Prefrontal Cortex and Consciousness: Beware of the Signals. Trends in Cognitive Science, March 2020. [WWW] [PDF] [bibtex-entry]


  10. Theofanis I. Panagiotaropoulos, Liping Wang, and Stanislas Dehaene. Hierarchical architecture of conscious processing and subjective experience. Cognitive Neuropsychology, 0(0):1-4, 2020.
    Note: PMID: 32423303. [WWW] [PDF] [bibtex-entry]


  11. Cassandra Potier Watkins, Julien Caporal, Clément Merville, Sid Kouider, and Stanislas Dehaene. Accelerating reading acquisition and boosting comprehension with a cognitive science-based tablet training. Journal of Computers in Education, pp 1--30, 2020. [PDF] [bibtex-entry]



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Note that this is not the exhaustive list of publications, but only a selection. Contact the individual authors for complete lists of references.




Last modified: Mon Jul 6 15:30:41 2020
Author: gs985873.


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