Functional MRI Training for Biomedical Physics and Engineering Students: Methodological Approach to Acquisition, Processing and Visualization

Abstract

Functional magnetic resonance imaging (fMRI) represents a cornerstone technique for studying brain activity and connectivity, yet its application in biomedical engineering education remains limited. The study’s object was the process of teaching and learning fMRI methodologies within biomedical physics and engineering education. The study’s subject was the methodological framework and practical module integrating acquisition, preprocessing, modelling, and visualisation of fMRI data for undergraduate training. The study aimed to design, implement, and evaluate a hands-on educational module that bridges the gap between theoretical knowledge and practical competence in fMRI workflows for biomedical students. Based on a teaching internship, a practical module was designed and implemented for undergraduate students of biomedical physics, engineering, and informatics that covered the complete fMRI workflow. The module combined an on-site visit to a radiology centre, participation in a scanning session with a simple block-design task, and a hands-on laboratory focused on preprocessing, modeling, and visualization using open-source tools. A preconfigured virtual environment with FSL and standardized data conversion via BIDS/BIDScoin enabled a reproducible pipeline from DICOM to NIfTI/BIDS and downstream modeling in FEAT. Students practiced brain extraction, spatial normalization, model specification for block designs, and interpretation of thresholded activation maps in FSLeyes. Educational outcomes included improved understanding of neuroimaging pipelines, stronger operational skills with widely used software, and higher motivation for interdisciplinary research. This work proposes a methodological framework for integrating fMRI-based training into biomedical curricula and bridging technical education with modern neuroimaging applications.