Causal mediation analysis is increasingly abundant in biology, psychology, and epidemiology studies, etc. In particular, with the advent of the big data era, the issue of high-dimensional mediators is becoming more prevalent. In neuroscience, with the widespread application of magnetic resonance technology in the field of brain imaging, studies on image being a mediator emerged. In this study, a novel causal mediation analysis method with a three-dimensional image mediator is proposed. We define the average casual effects under the potential outcome framework, explore several sufficient conditions for the valid identification, and develop techniques for estimation and inference. To verify the effectiveness of the proposed method, a series of simulations under various scenarios is performed. Finally, the proposed method is applied to a study on the causal effect of mother$^{\prime}$s delivery mode on child$^{\prime}$s IQ development. It is found that the white matter in certain regions of the frontal-temporal areas has mediating effects.

翻译：因果中介分析在生物学、心理学和流行病学等领域中的应用日益广泛。特别是随着大数据时代的到来，高维中介变量的问题变得越来越普遍。在神经科学领域，随着磁共振技术在脑成像研究中的广泛应用，将图像作为中介变量的研究应运而生。本研究提出了一种新的以三维图像为中介变量的因果中介分析方法。我们在潜在结果框架下定义了平均因果效应，探索了有效识别的若干充分条件，并发展了估计与推断技术。为验证所提方法的有效性，我们在多种场景下进行了一系列模拟实验。最后，将该方法应用于母亲分娩方式对儿童智商发展的因果效应研究，结果发现额颞区某些区域的白质具有中介效应。