Spatial smoothing is common in fMRI analyses but the benefit to functional sensitivity can vary depending on baseline signal-to-noise, inherent smoothness and physiological noise characteristics. Here we propose an extended model that can quantify each of these properties in addition to parameterising the degree of spatial correlation in the physiological noise. The model is validated through simulation and in vivo experiment. This new model allows the complete characterisation of the impact of spatial smoothing from a single fMRI time series enabling researchers to efficiently gain insight into their data and to optimise processing pipelines.
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