整个大脑能比它的“部分”简单吗？
Can the whole brain be simpler than its "parts"?
摘要：
这是一系列相关论文中的第一篇，这些论文讨论了一种动态可重构的通用学习神经计算机的问题，这种计算机可以作为整个人类大脑的计算模型。整个系列的标题是“零脑计划”。我的大脑是一个动态可重构的通用学习神经计算机。“（欲了解更多信息，请访问网站www.brain0.com。）这篇介绍性论文涉及一般方法论。它的主要目标是解释为什么神经建模和认知建模都非常重视整个大脑作为复杂计算系统的基本要求。作者认为，它可以更容易地开发一个适当的计算模型为整个“未编程”（未经训练）的人脑比找到适当的正式表示的一些非平凡的部分大脑的性能。(In同样的方式，例如，描述一个复杂的分析函数的行为比描述其实部和/或虚部的行为更容易。困扰着纯粹现象学（“无脑”）认知理论的“维度灾难”是一种自然的惩罚，因为它试图在维度不够高的状态空间中表示大脑性能的不够大的部分。一个“部分”建模者遇到了“第二十二条军规”。“试图通过人为地降低其维度来简化认知问题，会使问题变得更加困难。
英文摘要：
This is the first in a series of connected papers discussing the problem of a dynamically reconfigurable universal learning neurocomputer that could serve as a computational model for the whole human brain. The whole series is entitled "The Brain Zero Project. My Brain as a Dynamically Reconfigurable Universal Learning Neurocomputer." (For more information visit the website www.brain0.com.) This introductory paper is concerned with general methodology. Its main goal is to explain why it is critically important for both neural modeling and cognitive modeling to pay much attention to the basic requirements of the whole brain as a complex computing system. The author argues that it can be easier to develop an adequate computational model for the whole "unprogrammed" (untrained) human brain than to find adequate formal representations of some nontrivial parts of brain's performance. (In the same way as, for example, it is easier to describe the behavior of a complex analytical function than the behavior of its real and/or imaginary part.) The "curse of dimensionality" that plagues purely phenomenological ("brainless") cognitive theories is a natural penalty for an attempt to represent insufficiently large parts of brain's performance in a state space of insufficiently high dimensionality. A "partial" modeler encounters "Catch 22." An attempt to simplify a cognitive problem by artificially reducing its dimensionality makes the problem more difficult.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
