Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Radiology Department, Boston, MA, USA.
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Radiology Department, Boston, MA, USA.
Neuroimage. 2018 May 1;171:6-14. doi: 10.1016/j.neuroimage.2017.12.072. Epub 2017 Dec 26.
The false positive rates (FPR) for surface-based group analysis of cortical thickness, surface area, and volume were evaluated for parametric and non-parametric clusterwise correction for multiple comparisons for a range of smoothing levels and cluster-forming thresholds (CFT) using real data under group assignments that should not yield significant results. For whole cortical surface analysis, thickness showed modest inflation in parametric FPRs above the nominal level (10% versus 5%). Surface area and volume FPRs were much higher (20-30%). In the analysis of interhemispheric thickness asymmetries, FPRs were well controlled by parametric correction, but FPRs for surface area and volume asymmetries were still inflated. In all cases, non-parametric permutation adequately controlled the FPRs. It was found that inflated parametric FPRs were caused by violations in the parametric assumptions, namely a heavier-than-Gaussian spatial correlation. The non-Gaussian spatial correlation originates from anatomical features unique to individuals (e.g., a patch of cortex slightly thicker or thinner than average) and is not a by-product of scanning or processing. Thickness performed better than surface area and volume because thickness does not require a Jacobian correction.
基于表面的皮质厚度、表面积和体积的组分析的假阳性率 (FPR) 使用实际数据进行了评估，这些数据在不应产生显著结果的分组下进行了参数和非参数聚类校正的多重比较，用于各种平滑水平和聚类形成阈值 (CFT)。对于整个皮质表面分析，在名义水平（10% 对 5%）之上，参数 FPR 适度膨胀。表面积和体积 FPR 更高（20-30%）。在分析大脑半球间厚度不对称性时，参数校正很好地控制了 FPR，但表面积和体积不对称性的 FPR 仍然膨胀。在所有情况下，非参数置换都充分控制了 FPR。发现膨胀的参数 FPR 是由于参数假设的违反造成的，即比高斯分布更重的空间相关性。非高斯空间相关性源于个体特有的解剖特征（例如，皮质的一小块略厚或略薄于平均值），而不是扫描或处理的副产品。厚度的表现优于表面积和体积，因为厚度不需要雅可比校正。
