High-resolution fMRI data enables strategies to improve spatial specificity of the measured fMRI activations through anatomically-informed sampling. Here we demonstrate that cortical surface-based smoothing of high-resolution data can improve the specificity of fMRI activations by simultaneously canceling thermal noise through spatial averaging while avoiding physiological noise contamination from superficial CSF and signal dilution from subjacent white matter. By combining both tangential and radial smoothing using our surface-based analysis framework, specificity of responses to a breathold challenge can be similar in high-resolution data natively sampled at 1.1 mm iso. and unsmoothed data at a conventional resolution of 3.0 mm iso.
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