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Neural representations of events arise from temporal community structure
Open accessAbstract
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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Citations
Cites
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Elman, J. L. (1990) · Cognitive Science · doi:10.1207/s15516709cog1402_1 · Cited by 11,212
Landauer, T. K., & Dumais, S. T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.211 · Cited by 6,282
Family resemblances: Studies in the internal structure of categories
Rosch, E., & Mervis, C. B. (1975) · Cognitive Psychology · doi:10.1016/0010-0285(75)90024-9 · Cited by 5,933
Statistical learning by 8-month-old infants
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996) · Science · doi:10.1126/science.274.5294.1926 · Cited by 5,659
Maps of random walks on complex networks reveal community structure
Rosvall, M., & Bergstrom, C. T. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706851105 · Cited by 4,583
Context theory of classification learning
Medin, D. L., & Schaffer, M. M. (1978) · Psychological Review · doi:10.1037/0033-295x.85.3.207 · Cited by 3,061
Repetition and the brain: neural models of stimulus-specific effects
Grill-Spector, K., Henson, R., & Martin, A. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.11.006 · Cited by 2,256
Addis, D. R., Wong, A. T., & Schacter, D. L. (2007) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2006.10.016 · Cited by 1,949
Functional anatomy of a common semantic system for words and pictures
Vandenberghe, R. R., Price, C. J., Wise, R., Josephs, O., & Frackowiak, R. S. J. (1996) · Nature · doi:10.1038/383254a0 · Cited by 1,172
Rogers, T. T., & McClelland, J. L. (2004) · The MIT Press eBooks · doi:10.7551/mitpress/6161.001.0001 · Cited by 1,161
Self-citationTopics in semantic representation
Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007) · Psychological Review · doi:10.1037/0033-295x.114.2.211 · Cited by 1,122
Semantic Cognition: A Parallel Distributed Processing Approach
Rogers, T. T., & McClelland, J. L. (2004) · Cited by 891
Self-citationThe parallel distributed processing approach to semantic cognition
McClelland, J. L., & Rogers, T. T. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1076 · Cited by 832
Self-citationStatistical learning of higher-order temporal structure from visual shape sequences.
Fiser, J., & Aslin, R. (2002) · Journal of Experimental Psychology. Learning, Memory and Cognition · doi:10.1037//0278-7393.28.3.458 · Cited by 641
Attribution and the unit of perception of ongoing behavior
Newtson, D. (1973) · Journal of Personality and Social Psychology · doi:10.1037/h0035584 · Cited by 632
Learning the structure of event sequences.
Cleeremans, A., & McClelland, J. L. (1991) · Journal of Experimental Psychology General · doi:10.1037//0096-3445.120.3.235 · Cited by 584
Human brain activity time-locked to perceptual event boundaries
Zacks, J. M., Braver, T. S., Sheridan, M. A., Donaldson, D. I., Snyder, A. Z., Ollinger, J. M., Buckner, R. L., & Raichle, M. E. (2001) · Nature Neuroscience · doi:10.1038/88486 · Cited by 572
Neuroimaging studies of semantic memory: inferring “how” from “where”
Thompson‐Schill, S. L. (2002) · Neuropsychologia · doi:10.1016/s0028-3932(02)00161-6 · Cited by 556
Evidence of Mirror Neurons in Human Inferior Frontal Gyrus
Kilner, J. M., Neal, A., Weiskopf, N., Friston, K. J., & Frith, C. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.2668-09.2009 · Cited by 537
Learning the structure of event sequences.
Cleeremans, A., & McClelland, J. L. (1991) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.120.3.235 · Cited by 516
Statistical learning of higher-order temporal structure from visual shape sequences.
Fiser, J., & Aslin, R. Ν. (2002) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.28.3.458 · Cited by 505
Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities
Schapiro, A. C., Kustner, L. V., & Turk-Browne, N. B. (2012) · Current Biology · doi:10.1016/j.cub.2012.06.056 · Cited by 430
Self-citationWho did what to whom? The neural basis of argument hierarchies during language comprehension
Bornkessel‐Schlesewsky, I., Zysset, S., Friederici, A. D., von Cramon, D. Y., & Schlesewsky, M. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.01.032 · Cited by 426
PARSER: A Model for Word Segmentation
Perruchet, P., & Vinter, A. (1998) · Journal of Memory and Language · doi:10.1006/jmla.1998.2576 · Cited by 389
Botvinick, M., & Plaut, D. C. (2004) · Psychological Review · doi:10.1037/0033-295x.111.2.395 · Cited by 374
Self-citationDissociating the role of the medial and lateral anterior prefrontal cortex in human planning
Koechlin, É., Corrado, G., Pietrini, P., & Grafman, J. H. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.130177397 · Cited by 335
Ueno, T., Saito, S., Rogers, T. T., & Ralph, M. A. L. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.013 · Cited by 326
Self-citationTheories of artificial grammar learning.
Pothos, E. M. (2007) · Psychological Bulletin · doi:10.1037/0033-2909.133.2.227 · Cited by 318
What constitutes an episode in episodic memory?
Ezzyat, Y., & Davachi, L. (2011) · Psychological Science · doi:10.1177/0956797610393742 · Cited by 298
Selecting Among Competing Alternatives: Selection and Retrieval in the Left Inferior Frontal Gyrus
Moss, H. E., Abdallah, S., Fletcher, P., Bright, P., Pilgrim, L., Acres, K., & Tyler, L. K. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhi049 · Cited by 244
Segmenting dynamic human action via statistical structure
Baldwin, D. A., Andersson, A., Saffran, J. R., & Meyer, M. A. (2007) · Cognition · doi:10.1016/j.cognition.2007.07.005 · Cited by 208
Sridharan, D., Levitin, D. J., Chafe, C., Berger, J., & Menon, V. (2007) · Neuron · doi:10.1016/j.neuron.2007.07.003 · Cited by 202
Prediction error associated with the perceptual segmentation of naturalistic events
Zacks, J. M., Kurby, C. A., Eisenberg, M. L., & Haroutunian, N. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00078 · Cited by 202
Bar, M., Aminoff, E., Mason, M. F., & Fenske, M. (2007) · Hippocampus · doi:10.1002/hipo.20287 · Cited by 193
A computational model of event segmentation from perceptual prediction
Reynolds, J. R., Zacks, J. M., & Braver, T. S. (2007) · Cognitive Science · doi:10.1080/15326900701399913 · Cited by 172
Dissociating Neural Mechanisms of Temporal Sequencing and Processing Phonemes
Gelfand, J. R., & Bookheimer, S. Y. (2003) · Neuron · doi:10.1016/s0896-6273(03)00285-x · Cited by 163
Homae, F. (2002) · NeuroImage · doi:10.1006/nimg.2002.1138 · Cited by 153
Making Sense of Human Behavior: Action Parsing and Intentional Inference
Baird, J. A., & Baldwin, D. A. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/3838.003.0014 · Cited by 143
Activation of human motion processing areas during event perception
Speer, N. K., Swallow, K. M., & Zacks, J. M. (2003) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.3.4.335 · Cited by 143
Artificial syntactic violations activate Broca's region
Petersson, K. M., Forkstam, C., & Ingvar, M. (2004) · Cognitive Science · doi:10.1207/s15516709cog2803_4 · Cited by 142
Information mapping with pattern classifiers: A comparative study
Pereira, F., & Botvinick, M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.026 · Cited by 140
Self-citationRepetition‐induced changes in BOLD response reflect accumulation of neural activity
James, T. W., & Gauthier, L. (2005) · Human Brain Mapping · doi:10.1002/hbm.20165 · Cited by 135
Babies and Brains: Habituation in Infant Cognition and Functional Neuroimaging
Chun, M. M. (2008) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.016.2008 · Cited by 130
Visual Quality Determines the Direction of Neural Repetition Effects
Turk‐Browne, N. B., Yi, D.-J., Leber, A. B., & Chun, M. M. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj159 · Cited by 89
Self-citationAvrahami, J., & Kareev, Y. (1994) · Cognition · doi:10.1016/0010-0277(94)90050-7 · Cited by 72
Dissociable roles of human inferior frontal gyrus during action execution and observation
Press, C., Weiskopf, N., & Kilner, J. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.118 · Cited by 63
Constructing Semantic Representations From a Gradually Changing Representation of Temporal Context
Howard, M. W., Shankar, K. H., & Jagadisan, U. K. K. (2010) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2010.01112.x · Cited by 59
The formation of structurally relevant units in artificial grammar learning
Perruchet, P., Annie Vinter, A., Pacteau, C., & Gallego, J. (2002) · The Quarterly Journal of Experimental Psychology Section A · doi:10.1080/02724980143000451 · Cited by 42
Psychological Structure and Neural Correlates of Event Knowledge
Wood, J. N., Knutson, K. M., & Grafman, J. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhh215 · Cited by 38
Implicit learning of fifth- and sixth-order sequential probabilities
Remillard, G. (2010) · Memory & Cognition · doi:10.3758/mc.38.7.905 · Cited by 26
The frontopolar cortex mediates event knowledge complexity: a parametric functional MRI study
Krüeger, F., Spampinato, M. V., Barbey, A. K., Huey, E. D., Morland, T., & Grafman, J. H. (2009) · Neuroreport · doi:10.1097/wnr.0b013e32832e7ea5 · Cited by 22
Flagged first, then by citations
Cited by
Sorted by citations
Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks
(2018) · doi:10.5194/hess-22-6005-2018 · Cited by 2,114
What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior
Behrens, T. E. J., Muller, T. H., Whittington, J. C. R., Mark, S., Baram, A. B., Stachenfeld, K. L., & Kurth-Nelson, Z. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.002 · Cited by 1,055
Discovering Event Structure in Continuous Narrative Perception and Memory
Baldassano, C., Chen, J., Zadbood, A., Pillow, J. W., Hasson, U., & Norman, K. A. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.041 · Cited by 952
The hippocampus as a predictive map
Stachenfeld, K. L., Botvinick, M. M., & Gershman, S. J. (2017) · Nature Neuroscience · doi:10.1038/nn.4650 · Cited by 1,000
Self-citationSchapiro, A. C., Turk‐Browne, N. B., Botvinick, M., & Norman, K. A. (2016) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0049 · Cited by 530
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Metadata
- Authors
- Schapiro, A. C., Rogers, T. T., Cordova, N. I., Turk-Browne, N. B., & Botvinick, M. M.
- Affiliations
- Princeton University (US)
- University of Wisconsin–Madison (US)
- Corresponding author
- Schapiro, Anna C
- Venue
- Nature Neuroscience
- Published
- 2013-02-17
- Volume
- 16
- Issue
- 4
- Pages
- 486-492
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC3749823
- OpenAlex
- W2016723506
- Cited by
- 556
- References
- 54
- Citations by year
- 2026: 32 · 2025: 41 · 2024: 63 · 2023: 53 · 2022: 50 · 2021: 103 · 2020: 54 · 2019: 53 · 2018: 35 · 2017: 19 · 2016: 10 · 2015: 20 · 2014: 19 · 2013: 4
- FWCI
- 9.69
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Eye Institute (R01EY021755)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- event perception, event segmentation, forecast uncertainty, surprise, neural adaptation, multi-voxel pattern analysis, transition probabilities
- MeSH terms
- Adolescent, Adult, Brain, Female, Humans, Learning, Magnetic Resonance Imaging, Male, Photic Stimulation, Psychomotor Performance, Time Factors, Neural Networks, Computer, Computational Biology, Young Adult
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