About this Research Topic
Recent advancements in neuroimaging technologies have made exceptional strides in brain research. We now have a deeper, richer understanding of brain structure and function. However, the integration of multiple modality data like fMRI, EEG, MEG, and PET, still poses a formidable challenge. This Research Topic aims to dive into this area, focusing on the fusion of multi-modal neuroimaging data for a comprehensive portrayal of the brain.
The primary objective of this Research Topic is to promote the development of innovative fusing methods to overcome the challenge of integrating multi-modal neuroimaging data. Harnessing data derived from various imaging techniques, we aim to provide a more holistic understanding of brain connectivity, activity patterns, and neural dynamics. Key goals include creating robust fusion algorithms, managing data preprocessing, addressing integration issues, and applying brain mapping techniques to study neurological disorders and cognitive processes.
This Research Topic solicits articles that deal with the following themes:
• Development and optimization of fusion algorithms for multi-modal neuroimaging data.
• Methods for data preprocessing and management challenges related to data integration.
• Application of multi-modal data in providing detailed representations of the brain.
• Use of integrated neuroimaging data in studying neurological disorders and cognitive processes.
We invite submissions in the form of original research papers, review articles, methodological papers, and case studies. The ultimate goal of this topic is to support research that broadens our understanding of brain structure and function through cutting-edge neuroimaging research and to guide future research pathways in neurology and cognitive neuroscience.
The primary objective of this Research Topic is to promote the development of innovative fusing methods to overcome the challenge of integrating multi-modal neuroimaging data. Harnessing data derived from various imaging techniques, we aim to provide a more holistic understanding of brain connectivity, activity patterns, and neural dynamics. Key goals include creating robust fusion algorithms, managing data preprocessing, addressing integration issues, and applying brain mapping techniques to study neurological disorders and cognitive processes.
This Research Topic solicits articles that deal with the following themes:
• Development and optimization of fusion algorithms for multi-modal neuroimaging data.
• Methods for data preprocessing and management challenges related to data integration.
• Application of multi-modal data in providing detailed representations of the brain.
• Use of integrated neuroimaging data in studying neurological disorders and cognitive processes.
We invite submissions in the form of original research papers, review articles, methodological papers, and case studies. The ultimate goal of this topic is to support research that broadens our understanding of brain structure and function through cutting-edge neuroimaging research and to guide future research pathways in neurology and cognitive neuroscience.
Keywords: Neuroimaging, Brain Mapping, Multi-Modal Neuroimagin
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
