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Grounding predictive coding models in empirical neuroscience research

Published online by Cambridge University Press:  10 May 2013

Tobias Egner
Affiliation:
Department of Psychology & Neuroscience, and Center for Cognitive Neuroscience, Duke University, Durham, NC 27708. [email protected]://sites.google.com/site/egnerlab/
Christopher Summerfield
Affiliation:
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom. [email protected]://sites.google.com/site/summerfieldlab/home

Abstract

Clark makes a convincing case for the merits of conceptualizing brains as hierarchical prediction machines. This perspective has the potential to provide an elegant and powerful general theory of brain function, but it will ultimately stand or fall with evidence from basic neuroscience research. Here, we characterize the status quo of that evidence and highlight important avenues for future investigations.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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References

Alink, A., Schwiedrzik, C. M., Kohler, A., Singer, W. & Muckli, L. (2010) Stimulus predictability reduces responses in primary visual cortex. Journal of Neuroscience 30:2960–66.CrossRefGoogle ScholarPubMed
den Ouden, H. E. M., Daunizeau, J., Roiser, J., Friston, K. J. & Stephan, K. E. (2010) Striatal prediction error modulates cortical coupling. Journal of Neuroscience 30:3210–19.CrossRefGoogle ScholarPubMed
den Ouden, H. E. M, Friston, K. J., Daw, N. D., McIntosh, A. R. & Stephan, K. E. (2009) A dual role for prediction error in associative learning. Cerebral Cortex 19:1175–85.Google Scholar
Egner, T., Monti, J. M. & Summerfield, C. (2010) Expectation and surprise determine neural population responses in the ventral visual stream. Journal of Neuroscience 30(49):16601–608.Google Scholar
Eliades, S. J. & Wang, X. (2008) Neural substrates of vocalization feedback monitoring in primate auditory cortex. Nature 453:1102–106.CrossRefGoogle ScholarPubMed
Feldman, H. & Friston, K. J. (2010) Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience 4:215. doi:10.3389/fnmuh.2010.00215.Google Scholar
Friston, K. (2005) A theory of cortical responses. Philosophical Transactions of the Royal Society of London B: Biological Sciences 360(1456):815–36.Google Scholar
Friston, K. (2008) Hierarchical models in the brain. PLoS Computational Biology 4:e1000211.Google Scholar
Friston, K. J. (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11(2):127–38.Google Scholar
Hawkins, J. & Blakeslee, S. (2004) On intelligence. Owl Books/Times Books.Google Scholar
Helmholtz, H. von (1876) Handbuch der physiologischen Optik. Leopold Voss.Google Scholar
Hubel, D. H. & Wiesel, T. N. (1965) Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology 28:229–89.Google Scholar
Jiang, J., Schmajuk, N. & Egner, T. (2012) Explaining neural signals in human visual cortex with an associative learning model. Behavioral Neuroscience 126(4):575–81.Google Scholar
Keller, G. B., Bonhoeffer, T. & Hubener, M. (2012) Sensorimotor mismatch signals in primary visual cortex of the behaving mouse. Neuron 74:809–15.Google Scholar
Kok, P., Rahnev, D., Jehee, J. F., Lau, H. C. & de Lange, F. P. (2011) Attention reverses the effect of prediction in silencing sensory signals. Cerebral Cortex 22:2197–206.Google Scholar
Meyer, T. & Olson, C. R. (2011) Statistical learning of visual transitions in monkey inferotemporal cortex. Proceedings of the National Academy of Sciences USA 108:19401–406.CrossRefGoogle ScholarPubMed
Mumford, D. (1992) On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biological Cybernetics 66(3):241–51.CrossRefGoogle ScholarPubMed
Murray, S. O., Kersten, D., Olshausen, B. A., Schrater, P. & Woods, D. L. (2002) Shape perception reduces activity in human primary visual cortex. Proceedings of the National Academy of Sciences USA 99(23):15164–69.Google Scholar
Pearce, J. M. & Hall, G. (1980) A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli. Psychological Review 87:532–52.Google Scholar
Rao, R. P. N. & Ballard, D. H. (1999) Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience 2(1):7987.CrossRefGoogle ScholarPubMed
Riesenhuber, M. & Poggio, T (2000) Models of object recognition. Nature Neuroscience 3(Suppl.):1199–204.Google Scholar
Summerfield, C. & Egner, T (2009) Expectation (and attention) in visual cognition. Trends in Cognition Science 13:403409.Google Scholar
Summerfield, C., Egner, T., Greene, M., Koechlin, E., Mangels, J. & Hirsch, J (2006) Predictive codes for forthcoming perception in the frontal cortex. Science 314:1311–14.Google Scholar
Summerfield, C. & Koechlin, E. (2008) A neural representation of prior information during perceptual inference. Neuron 59:336–47.Google Scholar
Summerfield, C., Trittschuh, E. H., Monti, J. M., Mesulam, M. M. & Egner, T. (2008) Neural repetition suppression reflects fulfilled perceptual expectations. Nature Neuroscience 11(9):10041006.CrossRefGoogle ScholarPubMed
Summerfield, C., Wyart, V., Johnen, V. M. & De Gardelle, V (2011) Human scalp electroencephalography reveals that repetition suppression varied with expectation. Frontiers in Human Neuroscience 5:67. (Online publication). doi:10.3389/fnhum.2011.00067.CrossRefGoogle ScholarPubMed
Todorovic, A., van Ede, F., Maris, E. & de Lange, F. P. (2011) Prior expectation mediates neural adaptation to repeated sounds in the auditory cortex: An MEG study. Journal of Neuroscience 31:9118–23.Google Scholar
Wacongne, C., Changeux, J. P. & Dehaene, S. (2012) A neuronal model of predictive coding accounting for the mismatch negativity. Journal of Neuroscience 32:3665–78.Google Scholar
Wyart, V., Nobre, A. C. & Summerfield, C. (2012) Dissociable prior influences of signal probability and relevance on visual contrast sensitivity. Proceedings of the National Academy of Sciences USA 109:3593–98.Google Scholar