Faculty, Staff and Student Publications

Language

English

Publication Date

12-31-2025

Journal

Biostatistics

DOI

10.1093/biostatistics/kxaf019

PMID

40581858

PMCID

PMC12206356

PubMedCentral® Posted Date

6-29-2025

PubMedCentral® Full Text Version

Post-print

Abstract

A primary goal of task-based functional magnetic resonance imaging (fMRI) studies is to quantify the effective connectivity between brain regions when stimuli are presented. Assessing the dynamics of effective connectivity has attracted increasing attention. Causal mediation analysis serves as a widely implemented tool aiming to delineate the mechanism between task stimuli and brain activations. However, the case, where the treatment, mediator, and outcome are continuous functions, has not been studied. Causal mediation analysis for functional data is considered. Semiparametric functional linear structural equation models are introduced and causal assumptions are discussed. The proposed models allow for the estimation of individual effect curves. The models are applied to a task-based fMRI study, providing a new perspective of studying dynamic brain connectivity. The R package cfma for implementation is available on CRAN.

Keywords

Magnetic Resonance Imaging, Humans, Brain, Models, Statistical, Mediation Analysis

Published Open-Access

yes

Download

Included in

Public Health Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.