Graph Theoretical Approaches in Brain Networks
1Sapienza University of Rome, Roma, Italy
2University of California, Santa Barbara, CA, USA
3Chinese Academy of Sciences, Beijing, China
Graph Theoretical Approaches in Brain Networks
Description
Over the last decade, there has been growing interest in the study of brain networks. As other systems in nature, anatomical or functional brain networks can exhibit a certain level of complexity related to the emergence of nontrivial connectivity patterns in physiological as well as in pathological conditions. In simple networks of few cortical regions, as well as in those describing functional bindings between the activities of different brains, the need to extract the characteristic properties from the intermingled structure of those connectivity patterns led to an innovative use of a well-established mathematical framework, that is, graph theory.
The main focus of this special issue will be on the use of new and existing network analyses, the goal of which is to have a clearer understanding of the anatomical structure and functional dynamics of the brain.
The present special issue is intended to be an international space for researchers to summarize the most recent developments and ideas in the field, with a special emphasis given to the methodological and clinical results obtained within the last five years. Potential topics include, but are not limited to:
- Graph methods for brain networks
- Structure and dynamics of brain networks
- The brain's default-mode and cognitive networks
- Time-varying brain networks
- Inter-brain connectivity and social behavior
- The human “Connectome” and “Brainnetome” projects
- Computational models of brain networks
- Statistical approaches to identify group and task differences
- Prediction and classification methods for brain networks
- Applications to real neuroscientific and neuropsychiatric data (EEG, fMRI, MEG, NIRS)
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