Computational Neuroscience, from Multiple Levels to Multi-level
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This paper introduces the special issue of Journal of Physiology-Paris (Volume 104, Issues 1-2, Pages 1-106, January-March 2010) Computational Neuroscience, from Multiple Levels to Multi-level Edited by Emmanuel Daucé and Laurent Perrinet.
- Computational neuroscience, from multiple levels to multi-level Pages 1-4 Emmanuel Daucé, Laurent Perrinet
- Overview of facts and issues about neural coding by spikes Pages 5-18 Bruno Cessac, Hélène Paugam-Moisy, Thierry Viéville
- An Adaptive Resonance Theory account of the implicit learning of orthographic word forms Pages 19-26 H. Glotin, P. Warnier, F. Dandurand, S. Dufau, B. Lété, C. Touzet, J.C. Ziegler, J. Grainger
- Modelling honeybee visual guidance in a 3-D environment Pages 27-39 G. Portelli, J. Serres, F. Ruffier, N. Franceschini
- Voltage-sensitive dye imaging: Technique review and models Pages 40-50 S. Chemla, F. Chavane
- Phase space analysis of networks based on biologically realistic parameters Pages 51-60 Nicole Voges, Laurent Perrinet
- Interactions of motion and form in visual cortex – A neural model Pages 61-70 Cornelia Beck, Heiko Neumann
- A model of neural mechanisms in monocular transparent motion perception Pages 71-83 Florian Raudies, Heiko Neumann
- A unified and quantitative network model for spatial attention in area V4 Pages 84-90 Etienne Hugues, Jorge V. José
- Spike timing-dependent plasticity is affected by the interplay of intrinsic and network oscillations Pages 91-98 Fabiano Baroni, Pablo Varona
- Exploring modulation of action potential firing by artificial graft of fast GABAergic autaptic afferences in hypophyseal neuroendocrine melanotrope cells Pages 99-106 Sofiane Boussa, Jennifer Pasquier, François Leboulenger, Alain Faure, Frank Le Foll
- Emmanuel Daucé, Laurent Perrinet. Computational Neuroscience, from Multiple Levels to Multi-level, URL . Journal of Physiology (Paris), 104(1--2):1--4, 2010 abstractDespite the long and fruitful history of neuroscience, a global, multi-level description of cardinal brain functions is still far from reach. Using analytical or numerical approaches, \emphComputational Neuroscience aims at the emergence of such common principles by using concepts from Dynamical Systems and Information Theory. The aim of this Special Issue of the Journal of Physiology (Paris) is to reflect the latest advances in this field which has been presented during the NeuroComp08 conference that took place in October 2008 in Marseille (France). By highlighting a selection of works presented at the conference, we wish to illustrate the intrinsic diversity of this field of research but also the need of an unification effort that is becoming more and more necessary to understand the brain in its full complexity, from multiple levels of description to a multi-level understanding..
All material (c) L. Perrinet. Please check the copyright notice.