Spatiotemporal Complexity Analysis of Brain Function
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 3379
Special Issue Editors
Interests: biomedical signal processing; applied machine learning; brain function and structure; signal complexity analysis; time–frequency analysis; brain connectivity analysis
Interests: biomedical signal analysis and processing; nonstationary signal analysis; smart systems and control; applied artificial intelligence
Interests: biomedical signal processing; neuroimaging of brain networks; sparsity; time–frequency signal analysis; applied machine learning
Special Issue Information
Dear Colleagues,
The world we live in is a complex dynamical system that goes through numerous stable and unstable behaviors. One of the most obvious realizations of dynamical complexity can be found in the brain function as spontaneous changes in pattern irregularity in time and across multiple spatial scales. The biological mechanisms behind this spatiotemporal behavior and its mathematical properties are yet to be fully understood. To this end, different aspects of brain function, such as electrical activity, hemodynamics, glucose metabolism, and the diffusion of water molecules, can be investigated.
This Special Issue is dedicated to new advances in (i) spatiotemporal analysis of brain complexity using neuroimaging data, (ii) realistic modelling of brain complexity, and (iii) the development of quantitative tools for the differentiation of brain complexity between health and disease. We invite original contributions and comprehensive reviews from complex dynamics, neuroscience, network science, signal processing, and information theory on these topics:
- Biological and anatomical bases of complexity in brain function.
- Analysis of brain complexity in time and space using neuroimaging modalities such as EEG, MEG, functional/anatomical/diffusion MRI, and PET.
- Clinical applications of brain complexity analysis in brain abnormalities using machine learning techniques.
- Replication studies of previous findings using independent and large populations are also encouraged.
Dr. Amir Omidvarnia
Dr. Mostefa Mesbah
Dr. Ghasem Azemi
Guest Editors
Manuscript Submission Information
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Keywords
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complex dynamics
- spatiotemporal complexity
- neuroimaging
- brain structure and function
- diagnosis and prognosis of brain diseases
- brain connectivity analysis
- time series analysis
- network analysis
- numerical algorithms
- machine learning
