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New Ideas for Brain Modelling 2

机译:脑建模的新思想2

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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.
机译:本文描述了一种允许脑模型通过嵌套结构自组织其概念模式的相对简单的方法。对于模拟,减少时间有用,并且能够以搜索或思想过程的一部分,展示模式可以形成模式,然后按顺序释放。它使用一个非常简单的方程来展示抑制剂的特定方式,可以关闭某些区域,以允许其他区域成为突出的区域,从而定义当前的脑状态。这允许对大脑内部的混乱结构似乎少量的控制。它很有吸引力,因为它仍然主要是机械,因此可以添加为自动过程,或者建模。本文还描述了如何将嵌套模式结构用作基本计数机制。另一个数学结论为维护存储器或概念模式提供了基础。自动组织可以通过自动流程来空间。这可能允许以更均匀的方式添加新神经元,并有助于维护概念完整性。此过程还可以帮助找到内存结构之后。该扩展版本与现有的认知模型相结合,并提供了一些新的结论。

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