Multimodal neuroimaging techniques

This Research Topic is dedicated to highlighting current advances, applications, and methodological innovations in multimodal neuroimaging. We aim to showcase studies that harness the synergistic potential of integrating two or more imaging modalities to decipher the healthy and diseased brain. Our scope spans basic neuroscience, clinical research, and technical development; we are particularly interested in interdisciplinary work that bridges imaging physics, data science, neurobiology, and translational medicine. Through this collection, we seek to advance the field towards a more comprehensive, systems-level understanding of brain organization and function.We invite submissions on a broad range of subjects related to multimodal neuroimaging, including but not limited to:1. Novel approaches for data acquisition, co-registration, and integration of multiple imaging modalities. Examples include simultaneous PET/MRI, EEG-fMRI, optical/MRI, or hybrid MEG-EEG, as well as advancements in artifact correction and motion compensation.2. Studies using multimodal imaging to investigate brain networks, connectivity, and dynamics across the lifespan, during cognitive tasks, resting state, or naturalistic paradigms.3. Multimodal approaches in the diagnosis, prognosis, and monitoring of neurological or psychiatric disorders—including epilepsy, neurodegenerative diseases, brain tumors, stroke, and mental health conditions. We also welcome contributions leveraging machine learning or AI-based tools in multimodal neuroimaging analysis, especially those enhancing cross-modal feature integration or improving clinical decision-making.4. Perspectives and reviews on the challenges facing multimodal neuroimaging, such as standardization, data sharing, big data management, and open science, as well as commentary on the future landscape of the field. Topic editors: Fatma Gargouri, Kh Tohidul Islam Source: https://www.frontiersin.org/research-topics/73391/multimodal-neuroimaging-techniques