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Emalie G. McMahon, Charles Y. Zheng, Francisco Pereira, Ray Gonzalez, Leslie G. Ungerleider, Maryam Vaziri-Pashkam; Subtle predictive movements reveal actions regardless of social context. Journal of Vision 2019;19(7):16. doi: https://doi.org/10.1167/19.7.16.
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© ARVO (1962-2015); The Authors (2016-present)
Humans have a remarkable ability to predict the actions of others. To address what information enables this prediction and how the information is modulated by social context, we used videos collected during an interactive reaching game. Two participants (an “initiator” and a “responder”) sat on either side of a plexiglass screen on which two targets were affixed. The initiator was directed to tap one of the two targets, and the responder had to either beat the initiator to the target (competition) or arrive at the same time (cooperation). In a psychophysics experiment, new observers predicted the direction of the initiators' reach from brief clips, which were clipped relative to when the initiator began reaching. A machine learning classifier performed the same task. Both humans and the classifier were able to determine the direction of movement before the finger lift-off in both social conditions. Further, using an information mapping technique, the relevant information was found to be distributed throughout the body of the initiator in both social conditions. Our results indicate that we reveal our intentions during cooperation, in which communicating the future course of actions is beneficial, and also during competition despite the social motivation to reveal less information.
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