Abstract
Our experience of the world seems to divide naturally into discrete, temporally extended events, yet the mechanisms underlying the learning and identification of events are poorly understood. Research on event perception has focused on transient elevations in predictive uncertainty or surprise as the primary signal driving event segmentation. We present human behavioral and functional magnetic resonance imaging (fMRI) evidence in favor of a different account, in which event representations coalesce around clusters or 'communities' of mutually predicting stimuli. Through parsing behavior, fMRI adaptation and multivoxel pattern analysis, we demonstrate the emergence of event representations in a domain containing such community structure, but in which transition probabilities (the basis of uncertainty and surprise) are uniform. We present a computational account of how the relevant representations might arise, proposing a direct connection between event learning and the learning of semantic categories.
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Acknowledgements
We thank M. Arcaro, J. McGuire, K. Norman, F. Pereira and M. Todd for helpful discussions. This project was made possible through the support of a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. This work was also supported by US National Science Foundation Graduate Research Fellowship DGE-0646086 to A.C.S., US National Institutes of Health grant R01-EY021755 to N.B.T.-B., and US National Science Foundation grant IIS-1207833 and a James S. McDonnell Foundation grant to M.M.B.
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A.C.S., T.T.R. and M.M.B. designed the experiments. A.C.S. and N.I.C. collected and analyzed the data. N.B.T.-B. provided guidance on data acquisition and analysis. A.C.S., T.T.R., M.M.B. and N.B.T.-B. wrote the paper. All of the authors discussed the results and commented on the manuscript.
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Schapiro, A., Rogers, T., Cordova, N. et al. Neural representations of events arise from temporal community structure. Nat Neurosci 16, 486–492 (2013). https://doi.org/10.1038/nn.3331
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DOI: https://doi.org/10.1038/nn.3331
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