A Bayesian approach to determining connectivity of the human brain
A Bayesian approach to determining connectivity of the human brain
复制标题
DOI：
10.1002/hbm.20182
复制
发表时间：
2006-03-01
影响因子：
4.8
通讯作者：
Rilling, JK
中科院分区：
文献类型：
--
作者：
Patel, RS;Bowman, FD;Rilling, JK
最近关于大脑成像数据分析的工作集中在检查大脑的功能和有效连接上。我们开发了一种新的描述和推理方法来使用功能磁共振(FMRI)来分析人脑的连通性。我们通过贝叶斯范式比较体素对活动的预期联合概率和边缘概率来评估不同大脑区域对之间的关系，该范式允许结合先前已知的解剖和功能信息。我们通过测量功能连通性和优势来定义两个不同大脑区域之间的关系。在评估了所有脑体素对之间的关系后，我们能够从任何给定的大脑区域构建分层功能网络，并评估这些网络中重要的功能连通性和优势。我们使用fmrl的一项研究数据来说明我们的连接性分析的使用，该研究是关于玩了一次重复的“囚徒困境”游戏的女性之间的社会合作。我们的分析揭示了一个包括杏仁核、前脑岛皮质和前扣带皮质的功能网络，以及另一个包括腹侧纹状体、眶前皮质和前岛的网络。我们的方法可以用来开发因果大脑网络，用于结构方程建模和动态因果模型。
Recent work regarding the analysis of brain imaging data has focused on examining functional and effective connectivity of the brain. We develop a novel descriptive and inferential method to analyze the connectivity of the human brain using functional MRI (fMRI). We assess the relationship between pairs of distinct brain regions by comparing expected joint and marginal probabilities of elevated activity of voxel pairs through a Bayesian paradigm, which allows for the incorporation of previously known anatomical and functional information. We define the relationship between two distinct brain regions by measures of functional connectivity and ascendancy. After assessing the relationship between all pairs of brain voxels, we are able to construct hierarchical functional networks from any given brain region and assess significant functional connectivity and ascendancy in these networks. We illustrate the use of our connectivity analysis using data from an fMRl study of social cooperation among women who played an iterated "Prisoner's Dilemma" game. Our analysis reveals a functional network that includes the amygdala, anterior insula cortex, and anterior cingulate cortex, and another network that includes the ventral striatum, orbitofrontal cortex, and anterior insula. Our method can be used to develop causal brain networks for use with structural equation modeling and dynamic causal models.