Daucé Emmanuel, Perrinet Laurent
ISM/CNRS, Marseille, France.
J Physiol Paris. 2010 Jan-Mar;104(1-2):1-4. doi: 10.1016/j.jphysparis.2009.11.001. Epub 2009 Nov 10.
Despite 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, Computational 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.
尽管神经科学有着悠久且成果丰硕的历史，但对大脑主要功能进行全面、多层次的描述仍遥不可及。计算神经科学运用动力学系统和信息论的概念，通过分析或数值方法，致力于揭示此类通用原理。《生理学杂志》（巴黎）本期特刊的目的是反映该领域的最新进展，这些进展来自于2008年10月在法国马赛举行的NeuroComp08会议。通过重点介绍会议上展示的一系列研究成果，我们希望既能展现该研究领域内在的多样性，又能说明为从多层次描述到多层次理解来全面认识大脑，统一研究工作的必要性日益凸显。
