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Abstract #4519

Improving Sensitivity of Task-fMRI Signals by Use of Time Delayed Systemic Regressors: A Comparison of Probe Regressors from Peripheral NIRS Recordings and BOLD-fMRI

Sinem Burcu Erdogan1, Yunjie Tong2, Lia Maria Hocke3, Kimberly P. Lindsay (Dec.)4, and Blaise DeBonneval Frederick5

1Medical Engineering, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 2College of Engineering, Purdue University, West LaFayette, IN, United States, 3Department of Radiology, University of Calgary, Calgary, Alberta, Canada, 4Department of Psychiatry, Harvard University Medical School, Belmont, MA, United States, 5Department of Psychiatry, Harvard Medical School, Belmont, MA, United States

A fundamental problem with fMRI measurements is the strong presence of low frequency systemic physiological noise (<0.15 Hz), which significantly corrupts detection power for hemodynamic variations caused by task induced neuronal activation. In this study, we propose a novel noise removal strategy for task-fMRI studies by taking into consideration a relatively new established property of systemic low frequency oscillations (sLFOs): their dynamic propagation within cerebral vasculature causing voxel-specific arrival delays. We compare the performance of dynamic noise modelling regressors obtained from i) BOLD data and ii) a fingertip HBO signal of non-neuronal origin concurrently recorded with near infrared spectroscopy (NIRS).

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