Spectral graph theory of brain oscillations.
Spectral graph theory of brain oscillations.
复制标题
脑振荡的谱图理论。
DOI：
10.1002/hbm.24991
复制
发表时间：
2020
影响因子：
4.8
通讯作者：
Nagarajan,Srikantan
中科院分区：
文献类型：
--
作者：
Raj,Ashish;Cai,Chang;Xie,Xihe;Palacios,Eva;Owen,Julia;Mukherjee,Pratik;Nagarajan,Srikantan
大脑的结构连接和神经活动的功能模式之间的关系是计算神经科学的基本兴趣。我们研究了在中观和宏观尺度上的大脑活动的分层的、线性的图形光谱模型。该模型公式为结构-功能问题产生了一个优雅的闭合形式的解，由结构连接体的拉普拉斯函数的图谱指定，具有由最小全局参数集指定的简单、通用的动力学规则。所得的简约和解析解与高维耦合非线性神经场模型的复杂数值模拟形成鲜明对比。该频谱图模型准确地预测了整个大脑神经振荡活动的空间和频谱特征，并成功地同时再现了经验性观察到的阿尔法频段(8-12 赫兹)和贝塔频段(15-30 赫兹)活动的空间和频谱模式，这些模式是从源定位脑磁图(MEG)估计的。这个谱图模型表明，特定的大脑振荡是结构连接体的图形结构的紧急特性，并为理解网络拓扑和宏观全脑动力学之间的基本关系提供了重要的见解。。
The relationship between the brain's structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed‐form solution for the structure–function problem, specified by the graph spectrum of the structural connectome's Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. The resulting parsimonious and analytical solution stands in contrast to complex numerical simulations of high dimensional coupled nonlinear neural field models. This spectral graph model accurately predicts spatial and spectral features of neural oscillatory activity across the brain and was successful in simultaneously reproducing empirically observed spatial and spectral patterns of alpha‐band (8–12 Hz) and beta‐band (15–30 Hz) activity estimated from source localized magnetoencephalography (MEG). This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole‐brain dynamics. .
影响因子：
4.3
作者：
H. Sambrook
通讯作者：
H. Sambrook