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Connectomics methods (GraphVar & NBS-Predict)

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Connectomics methods (GraphVar & NBS-Predict)

The increasing popularity of non-invasive neuroimaging techniques has resulted in large datasets that enable the study of the structural and functional architecture of the human brain. The neuroimaging community is therefore faced with a growing need for comprehensive methods and accessible tools to derive rigorous neuroscientific inferences from such datasets. In this context, brain network theory, or connectomics, is becoming increasingly important in assessing the whole brain as an interconnected network and is proving to be a powerful tool for capturing the complexity of brain function and structure. However, due to the complexity of brain networks, these methods are largely inaccessible to researchers without sufficient computational skills, making them inaccessible to scientists whose research would otherwise benefit from brain network analyses (e.g., in clinical settings). In this project, we are exploring new methods for functional brain network analysis to address this important and unmet need for accessible software. Methodological developments already published are:  

Members: Emin Serin, MSc 
Head: Dr. rer. medic. J. Kruschwitz, habil., Dipl.-Psych. (CCM)  
Contact: Dr. rer. medic. J. Kruschwitz, habil., Dipl.-Psych. (CCM)