脑模型的新想法2
New Ideas for Brain Modelling 2
摘要：
本文描述了一种相对简单的方法，允许大脑模型通过嵌套结构自组织其概念模式。对于一个模拟，时间减少是有帮助的，它将能够显示模式如何形成，然后按顺序发射，作为搜索或思维过程的一部分。它使用一个非常简单的方程来说明抑制剂如何关闭某些区域，让其他区域成为突出的区域，从而定义当前的大脑状态。这允许对大脑内部看似混乱的结构进行少量控制。它之所以有吸引力，是因为它仍然主要是机械的，因此可以作为一个自动过程或模型添加。本文还介绍了如何嵌套模式结构可以用作一个基本的计数机制。另一个数学结论为保持记忆或概念模式提供了基础。自我组织可以通过自动化过程来自我定位。这可能允许以更均匀的方式添加新的神经元，并有助于保持概念的完整性。这个过程也可能有助于以后找到记忆结构。这个扩展版本进一步整合了现有的认知模型，并提供了一些新的结论。
英文摘要：
This paper describes a relatively simple way of allowing a brain model to self-organise its concept patterns through nested structures. For a simulation, time reduction is helpful and it would be able to show how patterns may form and then fire in sequence, as part of a search or thought process. It uses a very simple equation to show how the inhibitors in particular, can switch off certain areas, to allow other areas to become the prominent ones and thereby define the current brain state. This allows for a small amount of control over what appears to be a chaotic structure inside of the brain. It is attractive because it is still mostly mechanical and therefore can be added as an automatic process, or the modelling of that. The paper also describes how the nested pattern structure can be used as a basic counting mechanism. Another mathematical conclusion provides a basis for maintaining memory or concept patterns. The self-organisation can space itself through automatic processes. This might allow new neurons to be added in a more even manner and could help to maintain the concept integrity. The process might also help with finding memory structures afterwards. This extended version integrates further with the existing cognitive model and provides some new conclusions.
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。
