Abstract #2386

Application of Graph Theory in the study of functional and structural connectivity in Mild Cognitive Impairment (MCI) disease

Emilio Cipriano^1,2, Laura Biagi¹, Paolo Bosco¹, Giovanni Cioni¹, Alessandro Sale³, Nicoletta Berardi³, Michela Matteoli³, Michela Tosetti¹, and the Train the Brain Consortium⁴

¹FiRMLAB, IRCCS Stella Maris, Pisa, Italy, ²Department of Physics, University of Pisa, Pisa, Italy, ³Institute of Neuroscience of the CNR, Pisa, Italy, ⁴the Train the Brain Consortium, Pisa, Italy

Synopsis

Graph theory approach was used to analyze structural and functional connectivity networks to identify candidate biomarkers of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer’s disease (AD), for an early diagnosis and intervention. We proposed a method of brain network analysis to combine structural and functional connectivity networks information. Through graph measures (Segregation, Centrality and Global Efficiency), we evaluated the differences between MCI and healthy control (HC) subjects as well the possible effects of physical/cognitive training, in terms of structural and functional connectivity, in MCI population.

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