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Abstract #2844

Approximate Entropy as a Metric for Quantifying FMRI Changes Across Time

MAGNA25Kyle D. Steinke1, David Frakes2, Jose Rios3, Gabe Oland2, Leslie C. Baxter1

1Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States; 2School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States; 3Biomedical Engineering, Cornell University, Ithaca, NY, United States

Functional MRI is of limited utility in longitudinal studies because it lacks a quantitative baseline. We tested whether a test of interest (e.g., a motor task) could be compared to a generally stable vision task to overcome this weakness. We used approximate entropy (ApEn) to characterize each time series signal. The motor task ApEn was then compared to the vision task ApEn to form a ratio, which remained stable after a caffeine intervention, as expected, but changed in surgical patients that had behavioral decline.