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Semantic cognition: Distributed, but then attractive

Published online by Cambridge University Press:  11 December 2008

Emilio Kropff  and
Alessandro Treves
Emilio Kropff
Affiliation:
Cognitive Neuroscience sector, SISSA – International School for Advanced Studies, 34014 Trieste, Italy; emilio.kropff@ntnu.nohttp://folk.ntnu.no/kropff/
Alessandro Treves
Affiliation:
Kavli Institute for Systems Neuroscience and Centre for the Biology of Memory, MTFS, NO-7489 Trondheim, Norway. ale@sissa.ithttp://people.sissa.it/~ale/
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Abstract

The parallel distributed processing (PDP) perspective brings forward the important point that all semantic phenomena are based on analog underlying mechanisms, involving the weighted summation of multiple inputs by individual neurons. It falls short of indicating, however, how the essentially discrete nature of semantic processing may emerge at the cognitive level. Bridging this gap probably requires attractor networks.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 31 , Issue 6 , December 2008 , pp. 718 - 719
Copyright
Copyright © Cambridge University Press 2008

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References

Akrami, A., Liu, Y., Treves, A. & Jagadeesh, B. (2006) Dynamics of neural response in inferotemporal cortex during categorical processing of natural images. Society for Neuroscience Abstracts 504.9.Google Scholar
Braitenberg, V. & Schüz, A. (1991) Anatomy of the cortex: Statistics and geometry. Springer-Verlag.CrossRefGoogle Scholar
Hopfield, J. J. (1982) Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences USA 79:2554–58.CrossRefGoogle ScholarPubMed
Kropff, E. (forthcoming) Full solution for the storage of correlated memories in an autoassociative memory. In: Proceedings of the International Meeting on “Closing the Gap Between Neurophysiology and Behaviour: A Computational Modelling Approach,” Birmingham, U.K., May 2007. Available at: http://arxiv.org/abs/0707.3066.Google Scholar
Kropff, E. & Treves, A. (2007) Uninformative memories will prevail: The storage of correlated representations and its consequences. Human Frontier Science Program Journal 1(4):249–62.Google ScholarPubMed
Marr, D. (1971) Simple memory: A theory for archicortex. Philosophical Transactions of the Royal Society of London, B 262:23–81.Google ScholarPubMed
McRae, K., Cree, G., Seidenberg, M. & McNorgan, C. (2005) Semantic feature production norms for a large set of living and nonliving things. Behavior Research Methods, Instruments, and Computers 37(4):547–59.CrossRefGoogle ScholarPubMed
Rogers, T. T. & McClelland, J. L. (2004) Semantic cognition: A parallel distributed processing approach. MIT Press.CrossRefGoogle Scholar
Treves, A. (2005) Frontal latching networks: A possible neural basis for infinite recursion. Cognitive Neuropsychology 22:276–91.CrossRefGoogle ScholarPubMed
Warrington, E. & Shallice, T. (1984) Category specific semantic impairments. Brain 107(3):829–54.CrossRefGoogle ScholarPubMed
Wills, T. J., Lever, C., Cacucci, F., Burgess, N. & O'Keefe, J. (2005) Attractor dynamics in the hippocampal representation of the local environment. Science 308:873–76.CrossRefGoogle ScholarPubMed