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Abstract #0889

Support Vector Classification and Prediction of Resting-State Functional Connectivity Over the Lifespan

Scott J. Peltier1, 2, Jillian Wiggins3, Laura Jelsone-Swain4, Christopher Monk3, Rachael Seidler, 35, Robert Cary Welsh4, 6

1Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, United States; 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States; 3Psychology, University of Michigan, Ann Arbor, MI, United States; 4Radiology, University of Michigan, Ann Arbor, MI, United States; 5Kinesiology, University of Michigan, Ann Arbor, MI, United States; 6Psychiatry, University of Michigan, Ann Arbor, MI, United States


Multivariate classification is an important alternative to univariate techniques in studying functional connectivity. This study extends the investigation of predicting brain age to the entire lifespan.