This Research Topic is part of the Advanced Neuroimaging Methods in Brain Disorders series:
Advanced Neuroimaging Methods in Brain DisordersThe human brain is a large, interacting, complex system. Researchers have been working on the mechanisms of human brain under healthy and disease states for decades. Advanced neuroimaging techniques (e.g. functional magnetic resonance imaging and diffusion tensor imaging) enable us to explore the underlying principles of brain structural and functional architectures, as well as pathology alterations in various brain disorders. Furthermore, multi-modal neuroimaging techniques can provide more comprehensive understanding of pathomechanism of brain disorders, which is quite useful for the early diagnosis and the assessment of therapeutic effect and prognosis. Thus, the development of robust neuroimaging analytical methods is crucial to extract useful information from neuroimaging techniques.
The aim of this Research Topic is to present an overview on the recent developments of neuroimaging methods and its applications in brain disorders including (but are not limited to) epilepsy, autism spectrum disorder, Alzheimer's disease, major depression, anxiety, schizophrenia and brain tumors. We intend to further explore disease-related alterations on brain function and structure and seek imaging biomarkers in brain disorders via advanced neuroimaging analytical methods, such as dynamic functional connectivity, complex network analysis, multi-modal neuroimaging analysis, machine learning, and so on. New methods, theories and tools promoting neuroimaging analysis are well welcome. This Research Topic will broaden our current knowledge about brain disorders from the aspect of neuroimaging.
Submissions may be related to (but are not limited to) the following themes:
• development of novel neuroimaging analytical methods
• disease-related alterations on brain function or structure
• brain network analysis in brain disorders
• multi-modal neuroimaging analysis in brain disorders
• machine learning in classifying or predicting disease
For this Research Topic, we warmly welcome the submissions in the form of Original Research Articles, Method Articles, Review Articles, Mini Review Articles, Technology Report, Perspectives, Opinion, Brief Research Report, Book Reviews, and General Commentaries.
