Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms
Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms
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DOI：
10.1093/cercor/bhy032
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发表时间：
2019-03-01
期刊：
影响因子：
3.7
通讯作者：
Cannon, Tyrone D.
中科院分区：
文献类型：
--
作者：
Cao, Hengyi;McEwen, Sarah C.;Cannon, Tyrone D.
虽然图论模型极大地促进了我们对复杂大脑系统的理解，但在大型成像联盟中聚合连接组数据的可行性仍不清楚。在这里，我们使用一系列认知、情感和静息功能磁共振成像范例，研究了跨站点和会话的功能连接组测量的普遍性。我们的结果显示，在休息和任务期间，大多数措施的总体可靠性相当出色，尤其是那些量化连接强度、网络隔离和网络集成的措施。节点定义和全局信号回归 (GSR) 等处理方案显着影响了最终的可靠性，Power 图集（相对于 AAL 图集）和没有 GSR 的数据检测到更高的可靠性。虽然默认模式和感觉运动系统的网络诊断始终可靠，不受范式影响，但高阶认知系统的网络诊断主要在面临任务挑战时才可靠。此外，根据我们目前的样本，在考虑了观察到的可靠性后，当效应大小适中或更大时，在样本量约为 250 的多站点研究中可以获得令人满意的统计功效。我们的研究结果为大型联盟中大脑功能图的普遍性提供了经验证据，并鼓励使用多站点和多会话数据聚合连接组测量。
While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating connectomic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the generalizability of functional connectomic measures across sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Processing schemes such as node definition and global signal regression (GSR) significantly affected resulting reliability, with higher reliability detected for the Power atlas (vs. AAL atlas) and data without GSR. While network diagnostics for default-mode and sensori-motor systems were consistently reliable independently of paradigm, those for higher-order cognitive systems were reliable predominantly when challenged by task. In addition, based on our present sample and after accounting for observed reliability, satisfactory statistical power can be achieved in multisite research with sample size of approximately 250 when the effect size is moderate or larger. Our findings provide empirical evidence for the generalizability of brain functional graphs in large consortia, and encourage the aggregation of connectomic measures using multisite and multisession data.