Internal control of brain networks via sparse feedback
Internal control of brain networks via sparse feedback
复制标题
通过稀疏反馈对大脑网络进行内部控制
DOI：
10.1002/aic.18061
复制
发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
Daoutidis, Prodromos
中科院分区：
文献类型：
--
作者：
Mitrai, Ilias;Jones, Victoria O.;Dewantoro, Harman;Stamoulis, Catherine;Daoutidis, Prodromos
人类大脑是一个复杂的系统，其功能取决于神经元之间的相互作用和它们在组织尺度上的集合。这些相互作用受到解剖学和能量约束的限制，并促进信息处理和整合以响应认知需求。在这项工作中，我们认为大脑是一个闭环动力系统下的稀疏反馈控制。该控制器设计同时考虑了控制性能和反馈（通信）代价。作为原理的证明，我们将这个框架应用于结构和功能的大脑网络。在高反馈成本下，只有少量高度连接的网络节点被控制，这表明大脑区域的一小部分可能在神经回路的控制中发挥核心作用，通过性能和通信成本之间的权衡。
The human brain is a complex system whose function depends on interactions between neurons and their ensembles across scales of organization. These interactions are restricted by anatomical and energetic constraints, and facilitate information processing and integration in response to cognitive demands. In this work, we considered the brain as a closed loop dynamic system under sparse feedback control. This controller design considered simultaneously control performance and feedback (communication) cost. As proof of principle, we applied this framework to structural and functional brain networks. Under high feedback cost only a small number of highly connected network nodes were controlled, which suggests that a small subset of brain regions may play a central role in the control of neural circuits, through a trade‐off between performance and communication cost.