Rieck Jenny R, Baracchini Giulia, Nichol Daniel, Abdi Hervé, Grady Cheryl L
Rotman Research Institute at Baycrest, 3560 Bathurst Street, Toronto, ON M6A2E1, Canada.
Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Data Brief. 2021 Nov 15;39:107573. doi: 10.1016/j.dib.2021.107573. eCollection 2021 Dec.
We provide functional connectivity matrices generated during functional magnetic resonance imaging (MRI) during different tasks of cognitive control in healthy aging adults. These data can be used to replicate the primary results from the related manuscript: (Rieck et al., 2021). One-hundred-forty-four participants (ages 20-86) were scanned on a Siemens 3T MRI scanner while they were completing tasks to measure functional activity during inhibition, initiation, shifting, and working memory. Estimates of functional connectivity (quantified with timeseries correlations) between different brain regions were computed using three different brain atlases: Schaefer 100 parcel 17 network atlas (Schaefer et al., 2018; Yeo et al., 2011), Power 229 node 10 network atlas (Power et al., 2011), and Schaefer 200 parcel 17 network atlas (Schaefer et al., 2018; Yeo et al., 2011). The resulting functional connectivity correlation matrices are provided as text files with this article. Cov-STATIS (Abdi et al., 2012; a multi-table multivariate statistical technique; https://github.com/HerveAbdi/DistatisR) was used to examine similarity between functional connectivity during the different domains of cognitive control. The effect of aging on these functional connectivity patterns was also examined by computing measures of "task differentiation" and "network segregation." This dataset also provides supplemental analyses from the related manuscript (Rieck et al., 2021) to replicate the primary age findings with additional brain atlases. Cognitive neuroscience researchers can benefit from these data by further investigating the age effects on functional connectivity during tasks of cognitive control, in addition to examining the impact of different brain atlases on functional connectivity estimates. These data can also be used for the development of other multi-table and network-based statistical methods in functional neuroimaging.
我们提供了在健康老年成年人进行认知控制的不同任务期间,通过功能磁共振成像(MRI)生成的功能连接矩阵。这些数据可用于复制相关手稿(Rieck等人,2021年)的主要结果。144名参与者(年龄在20 - 86岁之间)在西门子3T MRI扫描仪上进行扫描,同时他们完成测量抑制、启动、转换和工作记忆期间功能活动的任务。使用三种不同的脑图谱计算不同脑区之间的功能连接估计值(用时间序列相关性量化):Schaefer 100分区17网络图谱(Schaefer等人,2018年;Yeo等人,2011年)、Power 229节点10网络图谱(Power等人,2011年)以及Schaefer 200分区17网络图谱(Schaefer等人,2018年;Yeo等人,2011年)。本文以文本文件形式提供了所得的功能连接相关矩阵。使用Cov - STATIS(Abdi等人,2012年;一种多表多变量统计技术;https://github.com/HerveAbdi/DistatisR)来检查认知控制不同领域期间功能连接的相似性。还通过计算“任务区分”和“网络隔离”指标来研究衰老对这些功能连接模式的影响。该数据集还提供了相关手稿(Rieck等人,2021年)的补充分析,以用额外的脑图谱复制主要的年龄研究结果。认知神经科学研究人员可以通过进一步研究认知控制任务期间年龄对功能连接的影响,以及检查不同脑图谱对功能连接估计的影响,从这些数据中受益。这些数据还可用于功能神经成像中其他多表和基于网络的统计方法的开发。