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Sparse coding and challenges for Bayesian models of the brain

  • Thomas Trappenberg (a1) and Paul Hollensen (a1)

Abstract

While the target article provides a glowing account for the excitement in the field, we stress that hierarchical predictive learning in the brain requires sparseness of the representation. We also question the relation between Bayesian cognitive processes and hierarchical generative models as discussed by the target article.

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References

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Barlow, H. B. (1961) Possible principles underlying the transformations of sensory messages. In: Sensory communication, ed. Rosenblith, W., pp. 217–34. (Chapter 13). MIT Press.
Földiák, P. (1990) Forming sparse representations by local anti-Hebbian learning. Biological Cybernetics 64:165–70.
Friston, K. J. (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11(2):127–38.
Hollensen, P. & Trappenberg, T. (2011) Learning sparse representations through learned inhibition. Poster presented at the COSYNE (Computational and Systems Neuroscience Conference) Annual Meeting, Salt Lake City, Utah, February 24, 2011.
Jaeger, H. (2011) Neural hierarchies: Singin' the blues. Oral presentation at Osnabrück Computational Cognition Alliance Meeting (OCCAM 2011), University of Osnabrück, Germany, June 22–24, 2011. Available at: http://video.virtuos.uni-osnabrueck.de:8080/engage/ui/watch.html?id=10bc55e8-8d98-40d3-bb11-17780b70c052&play=true.
Lee, H., Ekanadham, C. & Ng, A. (2008) Sparse deep belief net model for visual area V2. In: Advances in Neural Information Processing Systems 20 (NIPS'07), ed. Platt, J., Koller, D., Singer, Y. & Roweis, S., pp. 873–80. MIT Press.
Olshausen, B. A. & Field, D. J. (1996) Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381(6583):607609.
Rust, N. C., Schwartz, O., Movshon, J. A. & Simoncelli, E. P. (2005) Spatiotemporal elements of Macaque V1 receptive fields. Neuron 46:945–56.
Saxe, A., Bhand, M., Mudur, R., Suresh, B. & Ng, A. (2011) Modeling cortical representational plasticity with unsupervised feature learning. Poster presented at COSYNE 2011, Salt Lake City, Utah, February 24–27, 2011. Available at: http://www.stanford.edu/~asaxe/papers.
Vinje, W. E. & Gallant, J. L. (2000) Sparse coding and decorrelation in primary visual cortex during natural vision. Science 287:1273–76.
Waydo, S., Kraskov, A., Quiroga, R. Q., Fried, I. & Koch, C. (2006) Sparse representation in the human medial temporal lobe. Journal of Neuroscience 26:10232–34.

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