Improper selection of analysis methods can lead to significant errors when analyzing fMRI data with heterogeneous BOLD responses. Here, we used rodent optogenetic fMRI data and simulations to investigate different analysis methods’ detection and characterization performance. Our results show that, in the presence of heterogeneous BOLD responses, conventionally used GLM with a canonical basis set leads to considerable errors, while the gamma, finite impulse response, B-spline, and Fourier basis sets show robust performance.
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