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Kinematic priming of action predictions

The ability to anticipate what others will do next is crucial for navigating social, interactive environments. Here, we develop an experimental and analytical framework to measure the implicit readout of prospective intention information from movement kinematics. Using a primed action categorization...

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Detalles Bibliográficos
Autores principales: Scaliti, Eugenio, Pullar, Kiri, Borghini, Giulia, Cavallo, Andrea, Panzeri, Stefano, Becchio, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cell Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357321/
https://www.ncbi.nlm.nih.gov/pubmed/37339628
http://dx.doi.org/10.1016/j.cub.2023.05.055
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author Scaliti, Eugenio
Pullar, Kiri
Borghini, Giulia
Cavallo, Andrea
Panzeri, Stefano
Becchio, Cristina
author_facet Scaliti, Eugenio
Pullar, Kiri
Borghini, Giulia
Cavallo, Andrea
Panzeri, Stefano
Becchio, Cristina
author_sort Scaliti, Eugenio
collection PubMed
description The ability to anticipate what others will do next is crucial for navigating social, interactive environments. Here, we develop an experimental and analytical framework to measure the implicit readout of prospective intention information from movement kinematics. Using a primed action categorization task, we first demonstrate implicit access to intention information by establishing a novel form of priming, which we term kinematic priming: subtle differences in movement kinematics prime action prediction. Next, using data collected from the same participants in a forced-choice intention discrimination task 1 h later, we quantify single-trial intention readout—the amount of intention information read by individual perceivers in individual kinematic primes—and assess whether it can be used to predict the amount of kinematic priming. We demonstrate that the amount of kinematic priming, as indexed by both response times (RTs) and initial fixations to a given probe, is directly proportional to the amount of intention information read by the individual perceiver at the single-trial level. These results demonstrate that human perceivers have rapid, implicit access to intention information encoded in movement kinematics and highlight the potential of our approach to reveal the computations that permit the readout of this information with single-subject, single-trial resolution.
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spelling pubmed-103573212023-07-21 Kinematic priming of action predictions Scaliti, Eugenio Pullar, Kiri Borghini, Giulia Cavallo, Andrea Panzeri, Stefano Becchio, Cristina Curr Biol Article The ability to anticipate what others will do next is crucial for navigating social, interactive environments. Here, we develop an experimental and analytical framework to measure the implicit readout of prospective intention information from movement kinematics. Using a primed action categorization task, we first demonstrate implicit access to intention information by establishing a novel form of priming, which we term kinematic priming: subtle differences in movement kinematics prime action prediction. Next, using data collected from the same participants in a forced-choice intention discrimination task 1 h later, we quantify single-trial intention readout—the amount of intention information read by individual perceivers in individual kinematic primes—and assess whether it can be used to predict the amount of kinematic priming. We demonstrate that the amount of kinematic priming, as indexed by both response times (RTs) and initial fixations to a given probe, is directly proportional to the amount of intention information read by the individual perceiver at the single-trial level. These results demonstrate that human perceivers have rapid, implicit access to intention information encoded in movement kinematics and highlight the potential of our approach to reveal the computations that permit the readout of this information with single-subject, single-trial resolution. Cell Press 2023-07-10 /pmc/articles/PMC10357321/ /pubmed/37339628 http://dx.doi.org/10.1016/j.cub.2023.05.055 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Scaliti, Eugenio
Pullar, Kiri
Borghini, Giulia
Cavallo, Andrea
Panzeri, Stefano
Becchio, Cristina
Kinematic priming of action predictions
title Kinematic priming of action predictions
title_full Kinematic priming of action predictions
title_fullStr Kinematic priming of action predictions
title_full_unstemmed Kinematic priming of action predictions
title_short Kinematic priming of action predictions
title_sort kinematic priming of action predictions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357321/
https://www.ncbi.nlm.nih.gov/pubmed/37339628
http://dx.doi.org/10.1016/j.cub.2023.05.055
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