Abstract #4987
Brain-behavior prediction using functional connectivity from older adults with mild cognitive impairment
Michelle Karker1,2, Douglas Noll1,2,3, Benjamin M. Hampstead4,5, and Scott Peltier1,2
1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 2Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, United States, 3Radiology, University of Michigan, Ann Arbor, MI, United States, 4Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States, 5Research Program on Cognition and Neuromodulation Based Interventions, Psychiatry, University of Michigan, Ann Arbor, MI, United States
Synopsis
Partial least squares regression with feature selection (PLS-BETA) was applied to task-based and resting-state connectivity data. Leveraging a MCI-relevant object-location or face-name task illuminates relationships with measures of total cognition (RBANStotal) and memory (RBANSdelayed). This provides support for the use of clinically-relevant tasks in cases where a “driven” connectivity network may elucidate pathological changes.
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