Challenges in measuring individual differences in functional connectivity using fMRI: The case of healthy aging.
Challenges in measuring individual differences in functional connectivity using fMRI: The case of healthy aging.
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DOI：
10.1002/hbm.23653
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发表时间：
2017-08
影响因子：
4.8
通讯作者：
Henson RN
中科院分区：
文献类型：
--
作者：
Geerligs L;Tsvetanov KA;Cam-Can;Henson RN
许多研究报告了功能连接的个体差异，例如与年龄有关的差异。然而，从功能磁共振成像的连通性的估计是混淆了其他因素，如血管健康，头部运动和功能区域的位置变化。在这里，我们研究了这些混淆的影响，以及可以减轻它们的预处理策略，使用来自剑桥老龄化与神经科学中心（http：//www.example.com）的数据。www.cam-can.com该数据集包含来自214名年龄在18-88岁之间的成年人的两次静息状态fMRI。所有区域之间的功能连接与血管健康密切相关，最有可能反映呼吸和心脏信号。平均连接性的这些变化限制了参与者之间连接性估计值比较的有效性，最好通过参与者平均连接性的回归来缓解。我们还表明，高通滤波，而不是带通滤波，产生更强，更可靠的年龄效应。头部运动与选定大脑区域的灰质体积以及各种认知测量相关，表明它具有生物（特质）成分，并警告参与者不要倒退运动。最后，我们发现，功能区域的位置在老年人中变化更大，这可以通过平滑数据或使用多变量连接性测量来缓解。这些结果表明，分析选择对个体之间的连接差异产生了巨大影响，最终影响了连接和认知之间的关联。重要的是，功能磁共振成像连接的研究解决这些问题，我们提出了一些方法来优化分析的选择。《脑地图》38：4125-4156，2017年。© 2017 Wiley Periodicals，Inc.
Many studies report individual differences in functional connectivity, such as those related to age. However, estimates of connectivity from fMRI are confounded by other factors, such as vascular health, head motion and changes in the location of functional regions. Here, we investigate the impact of these confounds, and pre‐processing strategies that can mitigate them, using data from the Cambridge Centre for Ageing & Neuroscience (http://www.cam-can.com). This dataset contained two sessions of resting‐state fMRI from 214 adults aged 18–88. Functional connectivity between all regions was strongly related to vascular health, most likely reflecting respiratory and cardiac signals. These variations in mean connectivity limit the validity of between‐participant comparisons of connectivity estimates, and were best mitigated by regression of mean connectivity over participants. We also showed that high‐pass filtering, instead of band‐pass filtering, produced stronger and more reliable age‐effects. Head motion was correlated with gray‐matter volume in selected brain regions, and with various cognitive measures, suggesting that it has a biological (trait) component, and warning against regressing out motion over participants. Finally, we showed that the location of functional regions was more variable in older adults, which was alleviated by smoothing the data, or using a multivariate measure of connectivity. These results demonstrate that analysis choices have a dramatic impact on connectivity differences between individuals, ultimately affecting the associations found between connectivity and cognition. It is important that fMRI connectivity studies address these issues, and we suggest a number of ways to optimize analysis choices. Hum Brain Mapp 38:4125–4156, 2017. © 2017 Wiley Periodicals, Inc.
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影响因子：
4.2
作者：
Chou YH;Chen NK;Madden DJ
通讯作者：
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作者：
Campbell KL;Shafto MA;Wright P;Tsvetanov KA;Geerligs L;Cusack R;Cam-CAN;Tyler LK
通讯作者：
Tyler LK
DOI：
10.1073/pnas.1415122111
发表时间：
2014-11-18
影响因子：
11.1
作者：
Chan, Micaela Y.;Park, Denise C.;Wig, Gagan S.
通讯作者：
Wig, Gagan S.