脑磁图
临界性
人脑
模块化设计
神经科学
计算机科学
相关性(法律)
纤维束成像
模块化(生物学)
连接组学
人工智能
动力学(音乐)
神经生理学
人类连接体项目
神经网络
大脑活动与冥想
复杂系统
脑电图
物理
大脑定位
功能磁共振成像
统计物理学
功能连接
复杂网络
心理学
生物系统
自组织临界性
网络模型
动力系统理论
实验数据
作者
Marianna Angiolelli,Silvia Scarpetta,Pierpaolo Sorrentino,Emahnuel Troisi Lopez,Mario Quarantelli,C. Granata,Giuseppe Sorrentino,Vincenzo Palmieri,Giovanni Messuti,Mattia Stefano,Simonetta Filippi,Christian Cherubini,Alessandro Loppini,Letizia Chiodo
标识
DOI:10.1103/physrevresearch.7.043153
摘要
A healthy brain exhibits a rich dynamical repertoire, with flexible spatiotemporal patterns replaying on both microscopic and macroscopic scales. We hypothesize that the observed relationship between empirical structure and functional patterns is best explained when the microscopic neuronal dynamics is close to a critical regime. Using a modular spiking neuronal network model based on empirical connectomes, we posit that multiple stored functional patterns can transiently reoccur when the system operates near a critical regime, generating realistic brain dynamics and structural-functional relationships. The connections in the model are chosen so as to force the network to learn and propagate suited modular spatiotemporal patterns. To test our hypothesis, we employ magnetoencephalography and tractography data from five healthy individuals. We show that the extended critical region of the model maximizes the structure-function correlation and generates realistic features, demonstrating the relevance of near-critical regimes for physiological brain activity.
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