Model Specification and the Reliability of fMRI Results: Implications for Longitudinal Neuroimaging Studies in Psychiatry

Functional Magnetic Resonance Imagine (fMRI) is an important assessment tool in longitudinal studies of mental illness and its treatment. Understanding the psychometric properties of fMRI-based metrics, and the factors that influence them, will be critical for properly interpreting the results of these efforts. The current study examined whether the choice among alternative model specifications affects estimates of test-retest reliability in key emotion processing regions across a 6-month interval. Subjects (N = 46) performed an emotional-faces paradigm during fMRI in which neutral faces dynamically morphed into one of four emotional faces. Median voxelwise intraclass correlation coefficients (mvICCs) were calculated to examine stability over time in regions showing task-related activity as well as in bilateral amygdala. Four modeling choices were evaluated: a default model that used the canonical hemodynamic response function (HRF), a flexible HRF model that included additional basis functions, a modified CompCor (mCompCor) model that added corrections for physiological noise in the global signal, and a final model that combined the flexible HRF and mCompCor models. Model residuals were examined to determine the degree to which each pipeline met modeling assumptions. Results indicated that the choice of modeling approaches impacts both the degree to which model assumptions are met and estimates of test-retest reliability. ICC estimates in the visual cortex increased from poor (mvICC = 0.31) in the default pipeline to fair (mvICC = 0.45) in the full alternative pipeline – an increase of 45%. In nearly all tests, the models with the fewest assumption violations generated the highest ICC estimates. Implications for longitudinal treatment studies that utilize fMRI are discussed.功能磁共振成像（Functional Magnetic Resonance Imaging, fMRI）是精神疾病及其治疗纵向研究中的重要评估工具。明晰基于fMRI的指标的心理测量学特性及其影响因素，对于准确解读此类研究的结果具有关键意义。本研究旨在探究，在6个月的时间间隔内，不同的模型设定选择是否会影响关键情绪加工脑区的重测信度估计。受试者（N=46）在fMRI扫描过程中完成一项情绪面孔范式任务：中性面孔会动态变形为四种情绪面孔中的一种。研究计算了体素水平组内相关系数中位数（mvICCs），以考察任务相关活动脑区与双侧杏仁核的随时间稳定性。本次评估了四种建模方案：一是采用典型血流动力学响应函数（HRF）的默认模型，二是包含额外基函数的灵活HRF模型，三是针对全局信号中的生理噪声添加校正的修正版CompCor（mCompCor）模型，四是结合灵活HRF与mCompCor模型的最终组合模型。通过分析模型残差，判断各分析流程符合建模假设的程度。结果表明，建模方法的选择既会影响建模假设的符合程度，也会影响重测信度的估计值。视觉皮层的组内相关系数估计值从默认分析流程中的较差水平（mvICC=0.31）提升至完整备选分析流程中的中等水平（mvICC=0.45），增幅达45%。在几乎所有检验中，假设违背程度最低的模型均得到了最高的组内相关系数估计值。本文最后讨论了本研究对采用fMRI的纵向治疗研究的应用启示。