Hutchison Joanna L, Hubbard Nicholas A, Brigante Ryan M, Turner Monroe, Sandoval Traci I, Hillis G Andrew J, Weaver Travis, Rypma Bart
School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, United States; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States.
School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, United States.
J Neurosci Methods. 2014 Apr 15;226:57-65. doi: 10.1016/j.jneumeth.2014.01.012. Epub 2014 Jan 30.
Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods.
We compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches.
RESULTS AND COMPARISON WITH EXISTING METHOD(S): Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data.
Caution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.
使用标准空间脑模板是确定功能磁共振成像（fMRI）数据分析感兴趣区域（ROI）边界的有效方法。然而，基于个体特异性（即原生空间）脑表面地标确定的ROI在解剖学上是准确的，并且可能最能反映个体的局部血氧水平依赖（BOLD）反应。不幸的是，即使使用自动化方法，准确的原生空间ROI通常也需要耗费大量时间来描绘。
我们使用基于体积和表面的分析方法，比较了使用标准空间ROI与原生空间ROI时的组间差异分析。大学生和退伍军人参与者在fMRI采集过程中完成了按键任务和数字符号验证任务。在代表左、右运动和前额叶皮质的原生空间和标准空间的ROI内对数据进行分析。还使用功能（即信号变化百分比）和结构（即体素或节点计数）方法比较了基于体积和表面的分析结果。
结果表明，转换到标准空间会影响结构和功能分析的结果（根据皮质地理学放大/缩小差异），并且这些转换会影响关于体积数据组间差异的结论。
将标准空间ROI应用于体积fMRI数据时需谨慎。然而，体积分析显示出组间差异，并且在时间有限的情况下是合适的。使用功能ROI的基于表面的分析产生了最大的组间差异，并且对原生空间和标准空间之间的差异不太敏感。我们得出结论，在有足够时间和计算资源的情况下，基于表面的分析更可取。
