Engagement of large-scale networks is related to individual differences in inhibitory control.
Engagement of large-scale networks is related to individual differences in inhibitory control.
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DOI：
10.1016/j.neuroimage.2010.06.062
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发表时间：
2010-11-01
期刊：
影响因子：
5.7
通讯作者：
Poldrack, Russell A.
中科院分区：
文献类型：
--
作者：
Congdon, Eliza;Mumford, Jeanette A.;Cohen, Jessica R.;Galvan, Adriana;Aron, Adam R.;Xue, Gui;Miller, Eric;Poldrack, Russell A.
了解哪些大脑区域调节目标导向行为的执行和抑制，对许多研究领域都有意义。特别是，了解哪些大脑区域在需要执行和抑制运动反应的任务期间参与，可以深入了解反应抑制能力个体差异的机制。然而，神经影像学研究检查激活和停止之间的关系一直不一致的方向的关系，也与行为相关的区域的解剖位置。这些限制可能是由于小样本量的体素相关性的相对较低的功率引起的。在这里，我们汇集了五个独立的功能磁共振成像研究的停止信号任务的数据，以获得足够大的样本量，以稳健地检测大脑/行为的相关性。此外，我们没有对所有体素进行大量单变量相关性分析，而是通过使用独立成分分析降低数据集的维度来增加统计功效，然后检查行为与所得成分评分之间的相关性。我们发现，反映被认为参与停止的区域的活动的组件与更好的停止能力相关，而默认模式网络中的活动与个体之间的停止能力较差相关。这些结果清楚地显示了特定激活网络中个体停止能力差异之间的关系，包括已知对行为至关重要的区域。研究结果还强调了使用降维来增加个体差异研究中检测大脑/行为相关性的能力的有用性。
Understanding which brain regions regulate the execution, and suppression, of goal-directed behavior has implications for a number of areas of research. In particular, understanding which brain regions engaged during tasks requiring the execution and inhibition of a motor response provides insight into the mechanisms underlying individual differences in response inhibition ability. However, neuroimaging studies examing the relation between activation and stopping have been inconsistent regarding the direction of the relationship, and also regarding the anatomical location of regions that correlate with behavior. These limitations likely arise from the relatively low power of vox-elwise correlations with small sample sizes. Here, we pooled data over five separate fMRI studies of the Stop-signal task in order to obtain a sufficiently large sample size to robustly detect brain/behavior correlations. In addition, rather than performing mass univariate correlation analysis across all voxels, we increased statistical power by reducing the dimensionality of the data set using independent components analysis and then examined correlations between behavior and the resulting component scores. We found that components reflecting activity in regions thought to be involved in stopping were associated with better stopping ability, while activity in a default-mode network was associated with poorer stopping ability across individuals. These results clearly show a relationship between individual differences in stopping ability in specific activated networks, including regions known to be critical for the behavior. The results also highlight the usefulness of using dimensionality reduction to increase the power to detect brain/behavior correlations in individual differences research.
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DOI：
10.1073/pnas.96.14.8301
发表时间：
1999-07-06
影响因子：
11.1
作者：
Garavan, H;Ross, TJ;Stein, EA
通讯作者：
Stein, EA
影响因子：
3.2
作者：
Chambers, CD;Bellgrove, MA;Mattingley, JB
通讯作者：
Mattingley, JB
影响因子：
4.3
作者：
Enticott, PG;Ogloff, JRP;Bradshaw, JL
通讯作者：
Bradshaw, JL
影响因子：
5.7
作者：
Calhoun VD;Liu J;Adali T
通讯作者：
Adali T
影响因子：
4.1
作者：
Fillmore, MT;Rush, CR
通讯作者：
Rush, CR