Advanced Methods and Applications of MRI, fNIRS, and EEG

Dear Colleagues,

Multimodal Magnetic Resonance Imaging (MRI)—including structural, functional, diffusion, MR spectroscopy, and perfusion MRI—has significantly advanced our understanding of the neural basis for normative brain development and what goes awry in neurological and neuropsychiatric illnesses. MRI offers unrivaled spatial resolution and tissue contrast for both anatomical mapping and dynamic functional imaging. On the other hand, functional Near-Infrared Spectroscopy (fNIRS) has emerged as a portable non-invasive technology that is resilient to participant motion. These features make fNIRS particularly well-suited for studying cognitive processing across diverse populations, from infants to children who have difficulty staying still during lengthy MRI scans to patients who cannot be transported for MRI scans. Complementing these two imaging modalities, EEG remains irreplaceable in neuroscience, as its high temporal resolution is essential for capturing rapid neural dynamics in both laboratory and clinical settings. In addition, high-density EEG and brain implants provide an unrivaled opportunity for the development of brain–computer interfaces (BCIs) in the near future.

Synergistic combinations of these modalities (e.g., EEG-fNIRS and EEG-fMRI systems), empowered by artificial intelligence, represent a transformative frontier in neuroimaging for understanding brain structure and function in health and disease. By integrating static structural data with dynamic spatiotemporal characteristics, these hybrid approaches facilitate the development of high-fidelity digital twin brain (DTB) simulations. Such advancements enable precise interventions and real-time monitoring in naturalistic environments, driving the evolution of personalized medicine and redefining research paradigms in cognitive neuroscience by bridging the longstanding gap between controlled laboratory experiments and naturalistic real-world studies.

This Special Issue seeks to establish a curated collection of original research articles and comprehensive reviews, highlighting state-of-the-art methodologies, pioneering applications, and translational innovations, within the interdisciplinary landscape of MRI, fNIRS, and EEG. Topics of interest include, but are not limited to, the following:

（1）MRI Innovations

• Novel MRI techniques for the early detection of diseases (e.g., cancer staging, neurodegenerative disorders);
• Multiparametric MRI for tumor microenvironment characterization and radiomics-guided therapy monitoring​;
• Novel fMRI techniques for cognitive psychology research and real-world studies;
• AI-enhanced MRI/fMRI techniques: Deep learning-based reconstruction (e.g., compressed sensing), automated segmentation, and quantitative biomarker discovery​​.

（2）fNIRS and EEG Advancements

• Novel multimodal hybrid EEG-fNIRS techniques, systems, and applications​;
• Real-time EEG-based or fNIRS-validated BCI techniques;
• EEG-based adaptive neurofeedback closed-loop treatment and rehabilitation technology;
• Cross-disciplinary applications such as human–robot interaction, brain-inspired neural engineering, and social neuroscience.

（3）Computational and Clinical Frontiers

• Innovative MRI pulse sequences, post-processing algorithms, artificial intelligence integration, and hybrid technologies;
• New experimental methods, research paradigms, and clinical applications based on MRI, fNIRS, and EEG technologies;
• Knowledge graph or large model techniques for multimodal MRI, fNIRS, and EEG data;
• Digital twin brain (DTB) simulation​ integrating MRI/fNIRS/EEG datasets.

All submissions centered on innovative technologies or novel applications of MRI, fNIRS, and EEG are welcome. We encourage diverse contributions ranging from fundamental research and clinical trials to advanced computational modeling. 

Dr. Dongrong Xu
Prof. Dr. Ravi Bansal
Prof. Dr. Weihui Dai
Guest Editors

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• MRI
• multiparametric MRI
• cancer Imaging
• tumor characterization
• therapy monitoring
• whole-body MRI
• pediatric MRI
• oncologic imaging
• clinical MRI