Computational Neural Science on the Connection Machine: Adaptative Map Algorithms for Real World Problems

计算神经科学的一个重要目标是， 研究信息处理大脑， 数字信息处理的计算策略，就是 缩小高密度神经元和突触之间的差距 在大脑中发现的低密度和今天的计算 模型 在这方面，连接机器，一个巨大的平行 每个处理器具有大存储容量的计算机， 理想的研究工具 研究人员将利用这台新机器 缩小当前大脑模型和现实之间的差距。 这项工作将是高度计算性的，但它将带来 将来自不同学科的概念和技术结合在一起， 神经生物学、计算机科学和计算物理学。

One important aim of Computational Neural Science which studies information processing brains and adopts neural parallel computational strategies to digital information processing, is to narrow the gap between the high density of neurons and synapses found in brains and the low density in today's computational models. In this respect the Connection Machine, a massive parallel computer with a large storage capacity per processor, provides an ideal research tool. The researchers will exploit this new machine to narrow the gap between current models of the brain and reality. This work will be highly computational in nature, but it will bring together concepts and techniques from disparate disciplines, names Neurobiology, Computer Science, and Computational Physics.