Neuroimaging is a frontier interdiscipline, which has integrated the theories and methods of medicine, life science and engineering. In recent years, many advanced imaging methodologies have enhanced human interpretive powers for specific structures and functions. Multi-modal and multi-scale neuroimaging technologies include MRI, PET, CT, ultrasound, as well as other sources like fluorescence microscope image, MEG, EEG and fNIRS.
Recently, the development of machine learning/deep learning, complex networks, nonlinear dynamics, and even data visualization has provided a favorable guarantee for data analysis. These technologies allow measuring, modeling, and mining of multi-modal and multi-scale biomedical big data, and assist in cellular mechanism, organizational network mechanism, and improving the treatment efficacy of autism, Alzheimer's disease, depression and other related disease disorders. Also, brain function related studies guide educators and other professionals achieve a better understanding of human sleep, memory, learning, and rehabilitation process.
However, at present, the neuroimaging and data analysis methods are not yet mature. Advanced methods for multiscale, high resolution and functional imaging as well as novel computational techniques are highly expected to continuously develop the depth and scope of neuroscience.
In this Research Topic we will address several of these points with Original Research Articles, Review Articles and Methods Articles covering topics ranging from basic research to translational studies. We are looking for novelty in the methodological and/or theoretical content of data analysis and imaging as well as novel biomedical applications.
Neuroimaging is a frontier interdiscipline, which has integrated the theories and methods of medicine, life science and engineering. In recent years, many advanced imaging methodologies have enhanced human interpretive powers for specific structures and functions. Multi-modal and multi-scale neuroimaging technologies include MRI, PET, CT, ultrasound, as well as other sources like fluorescence microscope image, MEG, EEG and fNIRS.
Recently, the development of machine learning/deep learning, complex networks, nonlinear dynamics, and even data visualization has provided a favorable guarantee for data analysis. These technologies allow measuring, modeling, and mining of multi-modal and multi-scale biomedical big data, and assist in cellular mechanism, organizational network mechanism, and improving the treatment efficacy of autism, Alzheimer's disease, depression and other related disease disorders. Also, brain function related studies guide educators and other professionals achieve a better understanding of human sleep, memory, learning, and rehabilitation process.
However, at present, the neuroimaging and data analysis methods are not yet mature. Advanced methods for multiscale, high resolution and functional imaging as well as novel computational techniques are highly expected to continuously develop the depth and scope of neuroscience.
In this Research Topic we will address several of these points with Original Research Articles, Review Articles and Methods Articles covering topics ranging from basic research to translational studies. We are looking for novelty in the methodological and/or theoretical content of data analysis and imaging as well as novel biomedical applications.