Special Issue on Connectomics

Connectomics is the study of whole-brain maps of connectivity, commonly referred to as the brain connectome, that focuses on quantifying, visualizing, and understanding brain network organization including their applications in neuroimaging. The primary academic objective of this special issue is to bring together computational researchers (computer scientists, data scientists, computation neuroscientists) to present new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies.

In this special issue, Guest Editor Paul J. Laurienti, MD, PhD welcomes papers that address many of the challenges of connectomics in brain connectivity. The scope of this special issue is interdisciplinary.

The list of possible topics includes, but is not limited to:

• New developments in connectome construction from different imaging modalities;
• Development of data-driven techniques to identify biomarkers in connectome data;
• Brain network modeling and formal conceptual models of connectome data;
• Machine learning algorithms and connectome data analysis;
• Evaluation and validation of connectome models;
• New cutting-edge graphic techniques to visualize connectome data;
• Longitudinal connectome data analysis (e.g., brain development and aging studies);
• Multi-modal and combinatorial fusion of connectome data;
• Statistical methods for assessing individual and population connectome data;
• Computer-assisted diagnosis systems and connectomics.

Contributions will receive prompt and thorough peer review and will be published online ahead of print after acceptance.

Please refer to our Instructions for Authors before submitting your manuscript for consideration. For questions, please contact Dr. Paul J. Laurienti.

*Submitting Authors: Please include the title of the special issue in the cover letter upon submission

Deadline for manuscript submission: March 1, 2018