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Download Computation and Neural Systems by Anthony J. Bell (auth.), Frank H. Eeckman, James M. Bower PDF

By Anthony J. Bell (auth.), Frank H. Eeckman, James M. Bower (eds.)

Computational neuroscience is healthier outlined by way of its concentrate on realizing the anxious structures as a computational gadget instead of by way of a specific experimental method. Accordinlgy, whereas the vast majority of the papers during this booklet describe research and modeling efforts, different papers describe the result of new organic experiments explicitly positioned within the context of computational concerns. The distribution of topics in Computation and Neural Systems displays the present kingdom of the sector. as well as the medical effects provided right here, quite a few papers additionally describe the continued technical advancements which are serious for the continuing progress of computational neuroscience.
Computation and Neural Systems comprises papers offered on the First Annual Computation and Neural platforms assembly held in San Francisco, CA, July 26--29, 1992.

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Motorneurons of different geometry and the size principle. Biological Cybernetics, 25:163-176, 1977. [4] J. Wray. Theory and application of artificial neural networks. PhD thesis, University of Newcastle-upon-Tyne, 1992. [5] J. Wray and G. G. R. Green. Analysis of networks that have learnt control problems. In Proceedings of the International Conference Control '91, Herriot- Watt, UK, pages 261-265. Institution of Electrical Engineers, 1991. 4 UNSUPERVISED HEBBIAN LEARNING AND THE SHAPE OF THE NEURON ACTIVATION FUNCTION Jonathan L.

1988) Nature, 336:379-381. , J. Rinzel and M. Rogawski (1991) J. , 66:839-850. 7 AN ENTROPY MEASURE FOR REVEALING DETERMINISTIC STRUCTURE IN SPIKE TRAIN DATA Garrett T. Kenyon David C. O. O. Box 5218, Denton, TX. , deterministic) structure, which is a necessary (but not a sufficient) condition for significant information to be encoded in the precise temporal spike sequence. 1. INTRODUCTION Statistical measures, such as the peristimulus time histogram (PSTH), have been successfully employed throughout the nervous system in order to analyze spike activity, both for characterizing receptive fields and for studying the information processing capabilities of neurons.

Responses of 8 neurons in the primary visual cortex of an anaesthetised cat were recorded using standard extracellular techniques as described by Blakemore and Price[3]. Stimuli consisted of high contrast, drifting sinewave gratings with parameters that elicited some response from most cells. All parameters except for orientation were kept constant during the experiment. The analysis shows that uncertainty about the stimulus orientation decreases quickly with the number of cells included in the calculation (Figure 1,2).

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