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The influence of visual training on predicting complex action sequences

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Cross,  Emily S.
Department Psychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Max Planck Research Group Body and Self, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Social and Cultural Psychology, Radboud University, Nijmegen, the Netherlands;
School of Psychology, Wales Institute for Cognitive Neuroscience, Bangor University, United Kingdom;
Institute of Cognitive Neuroscience, University College London, United Kingdom;

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Stadler,  Waltraud
Department Psychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
School of Psychology, Wales Institute for Cognitive Neuroscience, Bangor University, United Kingdom;
Institute of Cognitive Neuroscience, University College London, United Kingdom;

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Parkinson,  Jim
Department Psychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Movement Science Unit, Department of Sport and Health Science, TU Munich, Germany;
Institute of Cognitive Neuroscience, University College London, United Kingdom;

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Schütz-Bosbach,  Simone
Max Planck Research Group Body and Self, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Institute of Cognitive Neuroscience, University College London, United Kingdom;

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Prinz,  Wolfgang
Department Psychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Institute of Cognitive Neuroscience, University College London, United Kingdom;

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Citation

Cross, E. S., Stadler, W., Parkinson, J., Schütz-Bosbach, S., & Prinz, W. (2013). The influence of visual training on predicting complex action sequences. Human Brain Mapping, 34(2), 467-486. doi:10.1002/hbm.21450.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0012-0F9D-F
Abstract
Linking observed and executable actions appears to be achieved by an action observation network (AON), comprising parietal, premotor, and occipitotemporal cortical regions of the human brain. AON engagement during action observation is thought to aid in effortless, efficient prediction of ongoing movements to support action understanding. Here, we investigate how the AON responds when observing and predicting actions we cannot readily reproduce before and after visual training. During pre- and posttraining neuroimaging sessions, participants watched gymnasts and wind-up toys moving behind an occluder and pressed a button when they expected each agent to reappear. Between scanning sessions, participants visually trained to predict when a subset of stimuli would reappear. Posttraining scanning revealed activation of inferior parietal, superior temporal, and cerebellar cortices when predicting occluded actions compared to perceiving them. Greater activity emerged when predicting untrained compared to trained sequences in occipitotemporal cortices and to a lesser degree, premotor cortices. The occipitotemporal responses when predicting untrained agents showed further specialization, with greater responses within body-processing regions when predicting gymnasts' movements and in object-selective cortex when predicting toys' movements. The results suggest that (1) select portions of the AON are recruited to predict the complex movements not easily mapped onto the observer's body and (2) greater recruitment of these AON regions supports prediction of less familiar sequences. We suggest that the findings inform both the premotor model of action prediction and the predictive coding account of AON function.