Effect of spatial smoothing on physiological noise in high-resolution fMRI

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Abstract

Physiological noise dominates the SNR of the fMRI time-course at commonly used spatial resolutions at field strengths of 3 T and above. Operating in this physiological noise dominated regime limits some benefits of high field acquisition since increases in image SNR produce only modest increases in time-course SNR. Although previous studies have shown that the physiological noise dominance can be mitigated by using higher spatial resolutions, not all functional studies require voxel sizes smaller than the thickness of the human cortex. In this study, we examine the effect of acquiring high spatial resolution, thermal noise dominated time-courses and spatially smoothing the images to lower resolutions, which would otherwise be physiological noise dominated. At high field strengths, where physiological noise is most problematic, this strategy lowered the overall time-course variance compared to direct acquisition at commonly used spatial resolution. At 7 T for example, 5 × 5 × 3 mm3 resolution images derived from smoothing 1.5 × 1.5 × 3 mm3 data improved time-course SNR by a factor of 1.89 compared to a time-series acquired at 5 × 5 × 3 mm3. Presumably, this effect was derived from the reduced physiological-to-thermal noise ratio in the high spatial resolution data followed by a smoothing operation that improves SNR without adding physiological noise. Our findings demonstrate that in contrast to conventional SNR penalties associated with spatially smoothing Fourier data, the time-course SNR of smoothed high-resolution data can be improved compared to direct acquisition at the desired resolution.

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