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Sparse Sampling of Silence Type I Errors With an Emphasis on Primary Auditory Cortex

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Sparse sampling functional MRI (ssfMRI) enables stronger primary auditory cortex blood oxygen level-dependent (BOLD) signal by acquiring volumes interspersed with silence, reducing the physiological artifacts associated with scanner noise. Recent… Click to show full abstract

Sparse sampling functional MRI (ssfMRI) enables stronger primary auditory cortex blood oxygen level-dependent (BOLD) signal by acquiring volumes interspersed with silence, reducing the physiological artifacts associated with scanner noise. Recent calculations of type I error rates associated with resting-state fMRI suggest that the techniques used to model the hemodynamic response function (HRF) might be resulting in higher false positives than is generally acceptable. In the present study, we analyze ssfMRI to determine type I error rates associated with whole brain and primary auditory cortex voxel-wise activation patterns. Study participants (n = 15, age 27.62 ± 3.21 years, range: 22–33 years; 6 females) underwent ssfMRI. An optimized paradigm was used to determine the HRF to auditory stimuli, which was then substituted for silent stimuli to ascertain false positives. We report that common techniques used for analyzing ssfMRI result in high type I error rates. The whole brain and primary auditory cortex voxel-wise analysis resulted in similar error distributions. The number of type I errors for P < 0.05, P < 0.01, and P < 0.001 for the whole brain was 7.88 ± 9.29, 2.37 ± 3.54, and 0.53 ± 0.96% and for the auditory cortex was 9.02 ± 1.79, 2.95 ± 0.91, and 0.58 ± 0.21%, respectively. When conducting a ssfMRI analysis, conservative α level should be employed (α < 0.001) to bolster the results in the face of false positive results.

Keywords: sparse sampling; cortex; primary auditory; type; auditory cortex

Journal Title: Frontiers in Neuroscience
Year Published: 2019

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