Bayesian inference of a directional brain network model for intracranial EEG data
Bayesian inference of a directional brain network model for intracranial EEG data
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颅内脑电图数据定向脑网络模型的贝叶斯推理
DOI：
10.1016/j.csda.2019.106847
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发表时间：
2020
影响因子：
1.8
通讯作者：
Quigg, Mark S.
中科院分区：
文献类型：
--
作者：
Zhang, Tingting;Sun, Yinge;Li, Huazhang;Yan, Guofen;Tanabe, Seiji;Miao, Ruizhong;Wang, Yaotian;Caffo, Brian S.;Quigg, Mark S.
人类大脑是一个网络系统，在这个系统中，大脑区域作为网络节点，不断地相互作用。大脑一个部分对另一个部分施加的定向效应被称为定向连接。由于大脑也是一个连续时间动态系统，因此很自然地使用常微分方程（ode）来模拟大脑区域之间的定向连接。作者提出了一个高维ODE模型来探索颅内脑电图（iEEG）记录的许多脑小区域之间的定向连接。新的ODE模型由阻尼谐振子的物理机制驱动，可以有效地近似神经振荡，这是一种涉及许多重要脑功能的有节奏或重复的神经活动。为了产生具有科学意义的网络结果，假设ODE模型参数具有集群结构，用于量化区域之间的定向连通性。集群结构符合人类大脑的功能专门化；大脑中专门负责同一功能的区域往往位于同一集群中。开发了两种贝叶斯方法来估计所提出的ODE模型的模型参数并识别强连接脑区的簇。本文将提出的ODE模型和贝叶斯方法应用于医学上难治性癫痫患者的脑电图数据，并用于检查癫痫发作前患者的大脑网络。
The human brain is a network system in which brain regions, as network nodes, constantly interact with each other. The directional effect exerted by one brain component on another is referred to as directional connectivity. Since the brain is also a continuous time dynamic system, it is natural to use ordinary differential equations (ODEs) to model directional connections among brain regions. The authors propose a high-dimensional ODE model to explore directional connectivity among many small brain regions recorded by intracranial EEG (iEEG). The new ODE model, motivated by the physical mechanism of the damped harmonic oscillator, is effective for approximating neural oscillation, a rhythmic or repetitive neural activity involved in many important brain functions. To produce scientifically meaningful network results, a cluster structure is assumed for the ODE model parameters that quantify directional connectivity among regions. The cluster structure is in line with the functional specialization of the human brain; the brain areas specialized in the same function tend to be in the same cluster. Two Bayesian methods are developed to estimate the model parameters of the proposed ODE model and to identify clusters of strongly connected brain regions. The proposed ODE model and Bayesian method are applied to iEEG data collected from a patient with medically intractable epilepsy and used to examine the patient’s brain networks before the seizure onset.