BSMac: a MATLAB toolbox implementing a Bayesian spatial model for brain activation and connectivity.

BSMac: a MATLAB toolbox implementing a Bayesian spatial model for brain activation and connectivity.
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DOI:
10.1016/j.jneumeth.2011.10.025
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发表时间:
2012-02-15
影响因子:
3
通讯作者:
Bowman, F. DuBois
Bowman, F. DuBois
中科院分区:
医学4区
文献类型:
--
作者:
Zhang, Lijun;Agravat, Sanjay;Derado, Gordana;Chen, Shuo;McIntosh, Belinda J.;Bowman, F. DuBois

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我们提出了一个统计和图形可视化MATLAB工具箱的功能磁共振成像(fMRI)数据的分析,称为贝叶斯空间模型的激活和连接(BSMac)。BSMac同时在体素和感兴趣区域(ROI)水平上进行全脑激活分析,以及使用灵活的贝叶斯建模框架进行任务相关功能连接(FC)分析。BSMac允许以Analyze或Nifti文件格式输入数据。用户提供有关分组成员资格,扫描会话,和实验任务(刺激),从其中构建的设计矩阵的信息。然后,BSMac基于马尔可夫链蒙特卡罗(MCMC)方法进行参数估计,并生成激活和FC图,例如体素和区域级任务相关的神经活动变化的交互式2D地图以及FC结果的动画3D图形。工具箱可以从http://www.sph.emory.edu/bios/CBIS/下载。我们说明了BSMac工具箱通过应用程序的功能磁共振成像研究精神分裂症患者的工作记忆。
We present a statistical and graphical visualization MATLAB toolbox for the analysis of functional magnetic resonance imaging (fMRI) data, called the Bayesian Spatial Model for activation and connectivity (BSMac). BSMac simultaneously performs whole-brain activation analyses at the voxel and region of interest (ROI) levels as well as task-related functional connectivity (FC) analyses using a flexible Bayesian modeling framework. BSMac allows for inputting data in either Analyze or Nifti file formats. The user provides information pertaining to subgroup memberships, scanning sessions, and experimental tasks (stimuli), from which the design matrix is constructed. BSMac then performs parameter estimation based on Markov Chain Monte Carlo (MCMC) methods and generates plots for activation and FC, such as interactive 2D maps of voxel and region-level task-related changes in neural activity and animated 3D graphics of the FC results. The toolbox can be downloaded from http://www.sph.emory.edu/bios/CBIS/. We illustrate the BSMac toolbox through an application to an fMRI study of working memory in patients with schizophrenia.
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