Abstract: Our current understanding of how brain activity supports mental functions has received a considerable scientific boost from the study of connectomics and the characterising the human connectome. This field of research has focused on the idea that complex but specific patterns of connectivity networks between brain areas subserve cognition. Large-scale projects have gotten underway to advance and exploit this understanding, including the $100 million BRAIN initiative in the United States, and the €1 billion Human Brain Project funded by the EU. However, advancing towards this objective requires the development of sophisticated computational techniques for analysing the large quantities of data being generated. In my talk, I will provide examples of how computational connectomics with large datasets could improve diagnostics in neurology. In particular, I will describe how the combination of signal processing, network analysis and machine learning can diagnose consciousness after brain injury. Ongoing trials of this technology could eventually help reduce the high rates of misdiagnosis, currently estimated to be as high as 40%.
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Contact: Michael Kampouridis