Abstract

Frontal power asymmetry (FA), a measure of brain function derived from electroencephalography, is a potential biomarker for major depressive disorder (MDD). Though FA is functional in nature, it is typically reduced to a scalar value prior to analysis, possibly obscuring its relationship with MDD and leading to a number of studies that have provided contradictory results. To overcome this issue, we sought to fit a functional regression model to characterize the association between FA and MDD status, adjusting for age, sex, cognitive ability, and handedness using data from a large clinical study that included both MDD and healthy control (HC) subjects. Since nearly 40% of the observations are missing data on either FA or cognitive ability, we propose an extension of multiple imputation (MI) by chained equations that allows for the imputation of both scalar and functional data. We also propose an extension of Rubin’s Rules for conducting valid inference in this setting. The proposed methods are evaluated in a simulation and applied to our FA data. For our FA data, a pooled analysis from the imputed datasets yielded similar results to those of the complete case analysis. We found that, among young females, HCs tended to have higher FA over the θ, α, and β frequency bands, but that the difference between HC and MDD subjects diminishes and ultimately reverses with age. For males, HCs tended to have higher FA in the β frequency band, regardless of age. Young male HCs had higher FA in the θ and α bands, but this difference diminishes with increasing age in the α band and ultimately reverses with increasing age in the θ band. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

摘要

额叶功率不对称 (FA) 是一种源自脑电图的脑功能测量方法，是重度抑郁症 (MDD) 的潜在生物标志物。尽管 FA 本质上是功能性的，但通常在分析之前将其简化为标量值，这可能会掩盖其与 MDD 的关系并导致许多研究提供了相互矛盾的结果。为了克服这个问题，我们试图拟合一个功能回归模型来表征 FA 和 MDD 状态之间的关联，使用来自包括 MDD 和健康控制（HC ) 科目。由于近 40% 的观察结果缺少关于 FA 或认知能力的数据，我们建议通过链式方程扩展多重插补 (MI)，允许对标量和函数数据进行插补。我们还建议扩展鲁宾规则，以便在这种情况下进行有效推理。所提出的方法在模拟中进行了评估，并应用于我们的 FA 数据。对于我们的 FA 数据，来自估算数据集的汇总分析产生了与完整案例分析相似的结果。我们发现，在年轻女性中，HC 的 FA 往往高于θ、α和β频带，但 HC 和 MDD 受试者之间的差异会随着年龄的增长而减小并最终逆转。对于男性而言，无论年龄大小，HC 在β频带内的 FA 值往往较高。年轻男性 HC 在θ和α波段具有更高的 FA，但这种差异随着α波段年龄的增加而减小，最终随着θ波段年龄的增加而逆转。本文的补充材料，包括可用于复制作品的材料的标准化描述，可作为在线补充获得。