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.