Meeting Banner
Abstract #3989

Behavioral performance prediction in aging with advanced resting-state imaging acquisitions

Scott James Peltier1,2, Michelle Karker2, Bruno Giordani3, Henry Paulson3, and Benjamin M Hampstead4,5
1Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 3Neurology, University of Michigan, Ann Arbor, MI, United States, 4Psychiatry, University of Michigan, Ann Arbor, MI, United States, 5Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States

Multi-band resting state data using two different protocols was collected in older subjects. Connectome-based predictive modeling yielded significant fits for measures of learning, memory, and language; with higher spatiotemporal sampling being more sensitive.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here