Cargando…

Movement kinematics drive chain selection toward intention detection

The ability to understand intentions based on another’s movements is crucial for human interaction. This ability has been ascribed to the so-called motor chaining mechanism: anytime a motor chain is activated (e.g., grasp-to-drink), the observer attributes to the agent the corresponding intention (i...

Descripción completa

Detalles Bibliográficos
Autores principales: Soriano, Marco, Cavallo, Andrea, D’Ausilio, Alessandro, Becchio, Cristina, Fadiga, Luciano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187161/
https://www.ncbi.nlm.nih.gov/pubmed/30242132
http://dx.doi.org/10.1073/pnas.1809825115
_version_ 1783362973281026048
author Soriano, Marco
Cavallo, Andrea
D’Ausilio, Alessandro
Becchio, Cristina
Fadiga, Luciano
author_facet Soriano, Marco
Cavallo, Andrea
D’Ausilio, Alessandro
Becchio, Cristina
Fadiga, Luciano
author_sort Soriano, Marco
collection PubMed
description The ability to understand intentions based on another’s movements is crucial for human interaction. This ability has been ascribed to the so-called motor chaining mechanism: anytime a motor chain is activated (e.g., grasp-to-drink), the observer attributes to the agent the corresponding intention (i.e., to drink) from the first motor act (i.e., the grasp). However, the mechanisms by which a specific chain is selected in the observer remain poorly understood. In the current study, we investigate the possibility that in the absence of discriminative contextual cues, slight kinematic variations in the observed grasp inform mapping to the most probable chain. Chaining of motor acts predicts that, in a sequential grasping task (e.g., grasp-to-drink), electromyographic (EMG) components that are required for the final act [e.g., the mouth-opening mylohyoid (MH) muscle] show anticipatory activation. To test this prediction, we used MH EMG, transcranial magnetic stimulation (TMS; MH motor-evoked potentials), and predictive models of movement kinematics to measure the level and timing of MH activation during the execution (Experiment 1) and the observation (Experiment 2) of reach-to-grasp actions. We found that MH-related corticobulbar excitability during grasping observation varied as a function of the goal (to drink or to pour) and the kinematics of the observed grasp. These results show that subtle changes in movement kinematics drive the selection of the most probable motor chain, allowing the observer to link an observed act to the agent’s intention.
format Online
Article
Text
id pubmed-6187161
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher National Academy of Sciences
record_format MEDLINE/PubMed
spelling pubmed-61871612018-10-15 Movement kinematics drive chain selection toward intention detection Soriano, Marco Cavallo, Andrea D’Ausilio, Alessandro Becchio, Cristina Fadiga, Luciano Proc Natl Acad Sci U S A Biological Sciences The ability to understand intentions based on another’s movements is crucial for human interaction. This ability has been ascribed to the so-called motor chaining mechanism: anytime a motor chain is activated (e.g., grasp-to-drink), the observer attributes to the agent the corresponding intention (i.e., to drink) from the first motor act (i.e., the grasp). However, the mechanisms by which a specific chain is selected in the observer remain poorly understood. In the current study, we investigate the possibility that in the absence of discriminative contextual cues, slight kinematic variations in the observed grasp inform mapping to the most probable chain. Chaining of motor acts predicts that, in a sequential grasping task (e.g., grasp-to-drink), electromyographic (EMG) components that are required for the final act [e.g., the mouth-opening mylohyoid (MH) muscle] show anticipatory activation. To test this prediction, we used MH EMG, transcranial magnetic stimulation (TMS; MH motor-evoked potentials), and predictive models of movement kinematics to measure the level and timing of MH activation during the execution (Experiment 1) and the observation (Experiment 2) of reach-to-grasp actions. We found that MH-related corticobulbar excitability during grasping observation varied as a function of the goal (to drink or to pour) and the kinematics of the observed grasp. These results show that subtle changes in movement kinematics drive the selection of the most probable motor chain, allowing the observer to link an observed act to the agent’s intention. National Academy of Sciences 2018-10-09 2018-09-21 /pmc/articles/PMC6187161/ /pubmed/30242132 http://dx.doi.org/10.1073/pnas.1809825115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Soriano, Marco
Cavallo, Andrea
D’Ausilio, Alessandro
Becchio, Cristina
Fadiga, Luciano
Movement kinematics drive chain selection toward intention detection
title Movement kinematics drive chain selection toward intention detection
title_full Movement kinematics drive chain selection toward intention detection
title_fullStr Movement kinematics drive chain selection toward intention detection
title_full_unstemmed Movement kinematics drive chain selection toward intention detection
title_short Movement kinematics drive chain selection toward intention detection
title_sort movement kinematics drive chain selection toward intention detection
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187161/
https://www.ncbi.nlm.nih.gov/pubmed/30242132
http://dx.doi.org/10.1073/pnas.1809825115
work_keys_str_mv AT sorianomarco movementkinematicsdrivechainselectiontowardintentiondetection
AT cavalloandrea movementkinematicsdrivechainselectiontowardintentiondetection
AT dausilioalessandro movementkinematicsdrivechainselectiontowardintentiondetection
AT becchiocristina movementkinematicsdrivechainselectiontowardintentiondetection
AT fadigaluciano movementkinematicsdrivechainselectiontowardintentiondetection