By Proft F., Geerlings P.
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Extra info for Conceptual and Computational DFT in the Study of Aromaticity
Of Neuroscience 13:19161931. Calvin, W. (1995). Cortical columns, modules, and hebbian cell assembles, in M. ), The handbook of brain theory and neural networks, MIT Press, Cambridge, MA, pp. 269-272. Cherniak, C. (1995). Neural component placement, Trends in Neuroscience 18: 522-527. Conway, J. H. & Sloane, N. (1993). Sphere packings, lattices and groups, 2 edn, Springer-Verlag, New York, NY. Durbin, R. & Mitchison, G. (1990). A dimension reduction framework for understanding cortical maps, Nature 343: 644-647.
Huma, n arm trajectory formation. Brain 105" 331-348. 4Acknowledgments. This work was partly supported by EU projects SPEECH-MAPS, MIAMI, MOVAID, by a MURST 40~ project and an ISS project. 32 V. Sanguineti, P. Morasso and F. Frisone Amari, S. (1977). Dynamics of pattern formation in lateral-inhibition type neural fields, Biological Cybernetics 27: 77-87. Benaim, M. & Tomasini, L. (1991). Competitive and Self-Organizing algorithms based on the minimization of an information criterion, in T. Kohonen, K.
Field computation is then a computational process that operates on an entire field in parallel. Often we treat the field as varying continuously in time, although this is not necessary. It is sometimes objected that distributions of quantity in the brain are not in fact continuous, since neurons and even synapses are discrete. However, this objection is irrelevant. For the purposes of field computation, it is necessary only that the number of units be sufficiently large t h a t it may be treated as a continuum, specifically, that continuous mathematics can be applied.
Conceptual and Computational DFT in the Study of Aromaticity by Proft F., Geerlings P.