拉丁方块任务核磁共振成像

UQ eSpace Pub Date : 1900-01-01 DOI:10.14264/uql.2019.780
Luke J. Hearne, L. Cocchi, J. Mattingley
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引用次数: 0

摘要

这个数据集是卢克·赫恩在昆士兰大学博士研究工作的一部分。我们感兴趣的是,当个人完成越来越复杂的任务时,大脑功能网络(通过核磁共振成像测量)是如何变化的。我们还对这些网络变化是否与任务表现和流体智力差异有关感兴趣。为了调查这一点,我们收集了一些行为数据测量(包括流体智力测试),并记录了参与者在完成拉丁方块任务时的大脑信号。每个参与者都完成了任务前的静息状态扫描,随后进行了三次拉丁方格任务、脑部结构扫描和任务后静息状态扫描。此外,他们还完成了Raven的高级渐进式矩阵、表格任务、折纸任务和扫描仪外的视觉搜索任务。数据已被识别并以BIDS格式组织。如果您使用这些数据,请引用以下论文:Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley。(2017)。脑网络结构在静息状态和复杂性依赖认知推理之间的重构,神经科学杂志
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Latin Square Task MRI
This dataset was collected as part of Luke Hearne’s PhD work at the University of Queensland. We were interested in investigating how functional brain networks (as measured by MRI) change as individuals complete increasingly complex tasks. We were also interested in whether these network changes are related to task performance and differences in fluid intelligence. To investigate this, we collected a number of behavioural data measures (including tests of fluid intelligence) and recorded brain signals while participants completed the Latin Square Task. Each participant completed a pre-task resting state scan, followed by three runs of the Latin Square Task, a structural brain scan and a post-task resting state scan. In addition, they completed the Raven’s advanced progressive matrices, the form boards task, the paper folding task and a visual search task outside of the scanner. The data has been deidentified and is organised in BIDS format. Please cite the following paper if you use the data: Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley. (2017). Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning, Journal of Neuroscience
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