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Ari E Kahn

Showing results (1-10 of 33) with videos related to

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Communications Psychology|February 5, 2025
Publisher Correction: Humans rationally balance detailed and temporally abstract world modelsAri E Kahn, Nathaniel D Daw
Communications Psychology|January 4, 2025
Humans rationally balance detailed and temporally abstract world modelsAri E Kahn, Nathaniel D Daw
Plos Computational Biology|November 17, 2025
Trial-by-trial learning of successor representations in human behaviorAri E Kahn, Dani S Bassett, Nathaniel D Daw
Biorxiv : the Preprint Server for Biology|July 16, 2025
Trial-by-trial learning of successor representations in human behaviorAri E Kahn, Dani S Bassett, Nathaniel D Daw
Nature Communications|May 10, 2020
Abstract representations of events arise from mental errors in learning and memoryChristopher W Lynn, Ari E Kahn, Nathaniel Nyema, et al.
Nature Human Behaviour|April 17, 2019
Network constraints on learnability of probabilistic motor sequencesAri E Kahn, Elisabeth A Karuza, Jean M Vettel, et al.
Developmental Science|June 3, 2026
Developmental Change in Structure Learning Reflects a Shift From Recency-Based to Relational PredictionKate Nussenbaum, Ari E Kahn, Alice Zhang, et al.
Cognition|October 11, 2025
Children leverage predictive representations for flexible, value-guided choiceAlice Zhang, Ari E Kahn, Nathaniel D Daw, et al.
Scientific Reports|October 8, 2017
Process reveals structure: How a network is traversed mediates expectations about its architectureElisabeth A Karuza, Ari E Kahn, Sharon L Thompson-Schill, et al.
Neuroimage|January 10, 2020
Functional brain network architecture supporting the learning of social networks in humansSteven H Tompson, Ari E Kahn, Emily B Falk, et al.
Pageof 4

Showing results (1-10 of 33) with videos related to

Sort By:
Pageof 4
Communications Psychology|February 5, 2025
Publisher Correction: Humans rationally balance detailed and temporally abstract world modelsAri E Kahn, Nathaniel D Daw
Communications Psychology|January 4, 2025
Humans rationally balance detailed and temporally abstract world modelsAri E Kahn, Nathaniel D Daw
Plos Computational Biology|November 17, 2025
Trial-by-trial learning of successor representations in human behaviorAri E Kahn, Dani S Bassett, Nathaniel D Daw
Biorxiv : the Preprint Server for Biology|July 16, 2025
Trial-by-trial learning of successor representations in human behaviorAri E Kahn, Dani S Bassett, Nathaniel D Daw
Nature Communications|May 10, 2020
Abstract representations of events arise from mental errors in learning and memoryChristopher W Lynn, Ari E Kahn, Nathaniel Nyema, et al.
Nature Human Behaviour|April 17, 2019
Network constraints on learnability of probabilistic motor sequencesAri E Kahn, Elisabeth A Karuza, Jean M Vettel, et al.
Developmental Science|June 3, 2026
Developmental Change in Structure Learning Reflects a Shift From Recency-Based to Relational PredictionKate Nussenbaum, Ari E Kahn, Alice Zhang, et al.
Cognition|October 11, 2025
Children leverage predictive representations for flexible, value-guided choiceAlice Zhang, Ari E Kahn, Nathaniel D Daw, et al.
Scientific Reports|October 8, 2017
Process reveals structure: How a network is traversed mediates expectations about its architectureElisabeth A Karuza, Ari E Kahn, Sharon L Thompson-Schill, et al.
Neuroimage|January 10, 2020
Functional brain network architecture supporting the learning of social networks in humansSteven H Tompson, Ari E Kahn, Emily B Falk, et al.
Pageof 4