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Early warning signals in motion inference

The ability to infer intention lies at the basis of many social interactions played out via motor actions. We consider a simple paradigm of this ability in humans using data from experiments simulating an antagonistic game between an Attacker and a Blocker. Evidence shows early inference of an Attac...

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Autores principales: Hart, Yuval, Vaziri-Pashkam, Maryam, Mahadevan, L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259514/
https://www.ncbi.nlm.nih.gov/pubmed/32469884
http://dx.doi.org/10.1371/journal.pcbi.1007821
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author Hart, Yuval
Vaziri-Pashkam, Maryam
Mahadevan, L.
author_facet Hart, Yuval
Vaziri-Pashkam, Maryam
Mahadevan, L.
author_sort Hart, Yuval
collection PubMed
description The ability to infer intention lies at the basis of many social interactions played out via motor actions. We consider a simple paradigm of this ability in humans using data from experiments simulating an antagonistic game between an Attacker and a Blocker. Evidence shows early inference of an Attacker move by as much as 100ms but the nature of the informational cues signaling the impending move remains unknown. We show that the transition to action has the hallmark of a critical transition that is accompanied by early warning signals. These early warning signals occur as much as 130 ms before motion ensues—showing a sharp rise in motion autocorrelation at lag-1 and a sharp rise in the autocorrelation decay time. The early warning signals further correlate strongly with Blocker response times. We analyze the variance of the motion near the point of transition and find that it diverges in a manner consistent with the dynamics of a fold-transition. To test if humans can recognize and act upon these early warning signals, we simulate the dynamics of fold-transition events and ask people to recognize the onset of directional motion: participants react faster to fold-transition dynamics than to its uncorrelated counterpart. Together, our findings suggest that people can recognize the intent and onset of motion by inferring its early warning signals.
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spelling pubmed-72595142020-06-08 Early warning signals in motion inference Hart, Yuval Vaziri-Pashkam, Maryam Mahadevan, L. PLoS Comput Biol Research Article The ability to infer intention lies at the basis of many social interactions played out via motor actions. We consider a simple paradigm of this ability in humans using data from experiments simulating an antagonistic game between an Attacker and a Blocker. Evidence shows early inference of an Attacker move by as much as 100ms but the nature of the informational cues signaling the impending move remains unknown. We show that the transition to action has the hallmark of a critical transition that is accompanied by early warning signals. These early warning signals occur as much as 130 ms before motion ensues—showing a sharp rise in motion autocorrelation at lag-1 and a sharp rise in the autocorrelation decay time. The early warning signals further correlate strongly with Blocker response times. We analyze the variance of the motion near the point of transition and find that it diverges in a manner consistent with the dynamics of a fold-transition. To test if humans can recognize and act upon these early warning signals, we simulate the dynamics of fold-transition events and ask people to recognize the onset of directional motion: participants react faster to fold-transition dynamics than to its uncorrelated counterpart. Together, our findings suggest that people can recognize the intent and onset of motion by inferring its early warning signals. Public Library of Science 2020-05-29 /pmc/articles/PMC7259514/ /pubmed/32469884 http://dx.doi.org/10.1371/journal.pcbi.1007821 Text en © 2020 Hart et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hart, Yuval
Vaziri-Pashkam, Maryam
Mahadevan, L.
Early warning signals in motion inference
title Early warning signals in motion inference
title_full Early warning signals in motion inference
title_fullStr Early warning signals in motion inference
title_full_unstemmed Early warning signals in motion inference
title_short Early warning signals in motion inference
title_sort early warning signals in motion inference
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259514/
https://www.ncbi.nlm.nih.gov/pubmed/32469884
http://dx.doi.org/10.1371/journal.pcbi.1007821
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