用秀丽隐杆线虫探索神经原理,秀丽隐杆线虫的神经模拟代表

A. Blau, F. Callaly, Seamus Cawley, Aedan Coffey, A. Mauro, Gorka Epelde, L. Ferrara, F. Krewer, C. Liberale, Pedro Machado, G. Maclair, T. McGinnity, F. Morgan, A. Mujika, A. Petrushin, Gautier Robin, J. Wade
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引用次数: 5

摘要

生物神经系统是强大的、健壮的、高度自适应的计算实体,在感觉-运动整合的几乎所有方面都优于传统计算机。尽管信息技术取得了巨大的进步,但在看似简单的定向和导航任务中,人工计算系统和大脑之间存在着巨大的性能差异。事实上,没有任何系统可以忠实地复制秀丽隐杆线虫丰富的行为技能。秀丽隐杆线虫是自然界中最简单的神经系统之一,由302个神经元和约8000个连接组成。elegans项目旨在提供这一缺失的环节。本文概述了主要的平台组件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring Neural Principles with Si elegans, a Neuromimetic Representation of the Nematode Caenorhabditis elegans
Biological neural systems are powerful, robust and highly adaptive computational entities that outperformconventional computers in almost all aspects of sensory-motor integration. Despite dramatic progress ininformation technology, there is a big performance discrepancy between artificial computational systemsand brains in seemingly simple orientation and navigation tasks. In fact, no system exists that can faithfullyreproduce the rich behavioural repertoire of the tiny worm Caenorhabditis elegans which features one of thesimplest nervous systems in nature made of 302 neurons and about 8000 connections. The Si elegans projectaims at providing this missing link. This article is sketching out the main platform components.
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