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Neuronal inference must be local, selective, and coordinated

Published online by Cambridge University Press:  10 May 2013

William A. Phillips*
Affiliation:
Psychology Department, University of Stirling, FK9 4LA Stirling, Scotland, United Kingdom, and Frankfurt Institute of Advanced Studies, 60438 Frankfurt am Main, Germany. [email protected]://www.psychology.stir.ac.uk/staff/staff-profiles/honorary-staff/bill-phillips

Abstract

Life is preserved and enhanced by coordinated selectivity in local neural circuits. Narrow receptive-field selectivity is necessary to avoid the curse-of-dimensionality, but local activities can be made coherent and relevant by guiding learning and processing using broad coordinating contextual gain-controlling interactions. Better understanding of the functions and mechanisms of those interactions is therefore crucial to the issues Clark examines.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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References

Doherty, M. J., Campbell, N. M., Tsuji, H. & Phillips, W. A. (2010) The Ebbinghaus illusion deceives adults but not young children. Developmental Science 13:714–21. doi:10.1111/j.1467-7687.2009.00931.x.CrossRefGoogle Scholar
Doherty, M. J., Tsuji, H. & Phillips, W. A. (2008) The context-sensitivity of visual size perception varies across cultures. Perception 37:1426–33.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
Fiorillo, C. D. (2012) Beyond Bayes: On the need for a unified and Jaynesian definition of probability and information within neuroscience. Information 3(2):175203. doi:10.3390/info3020175.Google Scholar
Friston, K. J. (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11(2):127–38.Google Scholar
Jaynes, E. T. (2003) Probability theory: The logic of science. Cambridge University Press.Google Scholar
Kay, J., Floreano, D. & Phillips, W. A. (1998) Contextually guided unsupervised learning using local multivariate binary processors. Neural Networks 11:117–40.Google Scholar
Kay, J. & Phillips, W. A. (2010) Coherent Infomax as a computational goal for neural systems. Bulletin of Mathematical Biology 73:344–72. doi: 10.1007/s11538-010-9564-x.CrossRefGoogle ScholarPubMed
Körding, K. P. & König, P. (2000) Learning with two sites of synaptic integration. Network: Computation in Neural Systems 11:115.Google ScholarPubMed
Phillips, W. A. (2012) Self-organized complexity and coherent Infomax from the viewpoint of Jaynes's probability theory. Information 3(1):115. doi:10.3390/info3010001.Google Scholar
Phillips, W. A., Chapman, K. L. S. & Berry, P. D. (2004) Size perception is less context-sensitive in males. Perception 33:7986.Google Scholar
Phillips, W. A., Kay, J. & Smyth, D. (1995) The discovery of structure by multistream networks of local processors with contextual guidance. Network: Computation in Neural Systems 6:225–46.Google Scholar
Phillips, W. A. & Silverstein, S. M. (2003) Convergence of biological and psychological perspectives on cognitive coordination in schizophrenia. Behavioral and Brain Sciences 26:6582; discussion 82–137.Google Scholar
Phillips, W. A. & Singer, W. (1997) In search of common foundations for cortical computation. Behavioral and Brain Sciences 20:657722.Google Scholar
Phillips, W. A., von der Malsburg, C. & Singer, W. (2010) Dynamic coordination in brain and mind. In: Strüngmann Forum Report, vol. 5: Dynamic coordination in the brain: From neurons to mind, ed. von der Malsburg, C., Phillips, W. A. & Singer, W., Chapter 1, pp. 124. MIT Press.Google Scholar
Spratling, M. W. (2008a) Predictive coding as a model of biased competition in visual attention. Vision Research 48(12):1391–408.Google Scholar
von der Malsburg, C., Phillips, W. A. & Singer, W., eds. (2010) Strungmann Forum Report, Vol. 5. Dynamic coordination in the brain: From neurons to mind. MIT Press.Google Scholar