Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data
Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data
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根据基于任务的功能磁共振成像数据与静息态功能磁共振成像数据中的区域连接概况预测功能网络
DOI：
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Daniele Marinazzo
中科院分区：
文献类型：
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作者：
J. Rasero;H. Aerts;Marlis Ontivero Ortega;J. Cortes;S. Stramaglia;Daniele Marinazzo
内在连接网络，从“静息状态”血氧水平依赖时间序列中出现的相关活动模式，越来越多地与认知，临床和行为方面相关，并与特定任务引起的活动模式进行比较。我们通过机器学习方法研究了任务和休息状态条件下大脑网络的重新配置，以突出内在连接网络（ICN），它更容易受到任务与休息状态下网络配置变化的影响。我们使用了大量的公开可用的数据在休息和基于任务的功能磁共振成像范例;通过尝试一个电池的不同的监督分类器只依赖于基于任务的测量，我们表明，达到最高的准确性与一个简单的神经网络的一个隐藏层。此外，当测试静息状态测量的拟合模型时，这样的架构对于与所执行的任务相关的区域产生接近90%的性能，其主要涉及视觉和感觉运动皮层，而在其他ICN中观察到性能的相关降低。一方面，我们的研究结果证实了ICN在两种范式（任务和休息）中的对应关系，从而为未来的临床应用打开了一扇窗户，因为受试者无法保证参与所需的任务。另一方面，它表明，大脑区域不参与的任务显示不同的连接模式在两个范例。缩写ICN内在连接网络BOLD血氧水平fMRI功能磁共振成像维斯视觉网络SM体感网络VA视觉注意网络DA背侧注意网络L脑网络FP额顶叶网络DMN默认模式网络CER小脑网络FSL皮层下网络FSRIB软件库FLIRT FMRIB的线性图像配准工具FNIRT FMRIB的非线性图像配准工具线性图像配准工具HCP人类连接组计划RF随机森林SVM支持向量机NN神经网络ROC接收器工作特性PR精确召回TPR真阳性率FPR假阳性率
Intrinsic Connectivity Networks, patterns of correlated activity emerging from “resting-state” Blood Oxygenation Level Dependent time series, are increasingly being associated to cognitive, clinical, and behavioral aspects, and compared with the pattern of activity elicited by specific tasks. We study the reconfiguration of the brain networks between task and resting-state conditions by a machine learning approach, to highlight the Intrinsic Connectivity Networks (ICNs) which are more affected by the change of network configurations in task vs. rest. We use a large cohort of publicly available data in both resting and task-based fMRI paradigms; by trying a battery of different supervised classifiers relying only on task-based measurements, we show that the highest accuracy is reached with a simple neural network of one hidden layer. In addition, when testing the fitted model on resting state measurements, such architecture yields a performance close to 90% for areas connected to the task performed, which mainly involve the visual and sensorimotor cortex, whilst a relevant decrease of the performance is observed in the other ICNs. On one hand, our results confirm the correspondence of ICNs in both paradigms (task and resting) thus opening a window for future clinical applications to subjects whose participation in a required task cannot be guaranteed. On the other hand it is shown that brain areas not involved in the task display different connectivity patterns in the two paradigms. Abbreviations ICN Intrinsic Connectivity Network BOLD Blood Oxygenation Level fMRI Functional magnetic resonance imaging VIS Visual Network SM Somatosensory Network VA Ventral Attention Network DA Dorsal Attention Network L Lymbic Network FP Fronto-pariental Network DMN Default Mode Network CER Cerebellar Network SUB Subcortical Network FSL FMRIB Software Library FLIRT FMRIB's Linear Image Registration Tool FNIRT FMRIB's Non-Linear Image Registration Tool HCP Human Connectome Project RF Random Forest SVM Support Vector Machines NN Neural Network ROC Receiver Operating Characteristic PR Precision-Recall TPR true positive rate FPR false positive rate
影响因子：
2.5
作者：
Vincent, Justin L.;Kahn, Itamar;Buckner, Randy L.
通讯作者：
Buckner, Randy L.
DOI：
10.1097/rmr.0000000000000075
发表时间：
2016-02
期刊：
Topics in magnetic resonance imaging : TMRI
影响因子：
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作者：
Lee MH;Miller-Thomas MM;Benzinger TL;Marcus DS;Hacker CD;Leuthardt EC;Shimony JS
通讯作者：
Shimony JS
DOI：
10.1073/pnas.0604187103
发表时间：
2006-06-27
影响因子：
11.1
作者：
Fox, Michael D.;Corbetta, Maurizio;Raichle, Marcus E.
通讯作者：
Raichle, Marcus E.