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Machine learning techniques for quantifying neural synchrony: application to the diagnosis of Alzheimer's disease from E

Machine learning techniques for quantifying neural synchrony: application to the diagnosis of Alzheimer's disease from EEG. Justin Dauwels LIDS, MIT Amari Research Unit, Brain Science Institute, RIKEN June 9, 2008. RIKEN Brain Science Institute. RIKEN Wako Campus (near Tokyo)

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Frequency patterns - PowerPoint PPT Presentation

Machine learning techniques for quantifying neural synchrony: application to the diagnosis of Alzheimer's disease from E