About this Research Topic
The goal of this research topic is to promote the novel data analysis methodologies and innovative investigation paradigms into multi-scale, multidimensional characterization of the neuropsychiatric diseases/disorders (depression, anxiety disorder, obsessive-compulsive disorder, schizophrenia, Tourette syndrome, attention deficit and hyperactivity disorder, autism spectrum disorder, Alzheimer’s disease, etc.), as well as their potential clinical applications.
Research areas to be covered by this Research Topic include, but are not limited to:
-Discovery of the biomarkers with pathological significance related to neuropsychiatric disorders and the possible connection between them, using modalities such as MRI, EEG/MEG, NIRS, eye movements, body movement, skin conductivity, dynamic heart rate and other techniques.
-Data-driven characterization of the neuropsychiatric disorders with imaging, behaviour, and physiological biomarkers by statistical and machine learning approaches, and their application in diagnosis / differential diagnosis/treatment efficacy studies.
-Solutions for the fusion and integrated analysis of multi-dimensional biomarkers collected from heterogeneous sources, and the analysis of the interaction between different biomarkers, using advanced machine learning methods such as deep neural networks and representation learning on the graphs.
-Novel algorithms and analytics frameworks adaptive to data collected from multiple scales, both spatial and temporal, for analysing the individual and groupwise nervous system at scales.
Review articles and comments are also welcomed.
Keywords: Neuropsychiatric disorders, Algorithms, MRI, EEG, MEG, NIRS
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.