Self-repairing Hardware Paradigms based on Astrocyte-neuron Models

人类的大脑具有非凡的自我修复能力，例如在中风或受伤后。这种自我修复源于一系列分布和细粒度的机制，这些机制协同作用，确保神经元（大脑的基本组成部分）在尽可能接近正常状态的情况下继续发挥作用。相比之下，现代电子系统设计通常依赖于单个控制器或处理器，其自我修复能力非常有限。我们迫切需要超越目前的方法，从生物学中寻找灵感，为电子系统设计提供信息。最近的研究强调，星形胶质细胞（一种胶质细胞）和大脑神经元之间的相互作用提供了一种分布式细胞水平的修复能力，其中阻碍或停止神经元放电的故障可以通过重新调整大脑神经元之间连接的局部权重来修复。该项目旨在利用这些最新发现，从这些结果中获得灵感，设计新一代“以天文为中心”的算法，开发新一代自我修复算法。为了实现这一目标，我们将在我们的电子系统中包括代表神经元和星形胶质细胞的组件，并以这样一种方式模拟它们之间的相互作用，以捕捉生物系统中所见的分布式修复能力。

The human brain is remarkable in its ability to self-repair, for example following stroke or injury. Such self-repair results from a range of distributed and fine-grained mechanisms which act in tandem to ensure that the neurones (the basic building blocks in the brain) continue to function in as close to a normal state as possible.In contrast modern electronic systems design typically relies on a single controller or processor, which has very limited self-repair capabilities. There is a pressing need to progress beyond current approaches and look for inspiration from biology to inform electronic systems design.Recent studies have highlighted that interactions between astrocytes (a type of glial cell) and neurones in the brain provide a distributed cellular level repair capability where faults that impede or stop neuronal firing can be repaired by a re-adjustment of the local weights of connections between neurones in the brain.This project aims to exploit these recent findings and develop a new generation of self-repairing algorithms by taking inspiration from these results to design a new generation of "astro-centric" algorithms. To achieve this we will include components representing both neurones and astrocytes in our electronic systems and model the interactions between these in such a way as to capture the distributed repair capabilities seen in the biological system.