Representative activation maps for the two processing methods, NEMO and SVarM, for different levels of B₀ and B₁⁺ inhomogeneities. On the right, corresponding plots of Dice score and surviving pixels ration (mean ± std). On the top, ground truth activation map, obtained from BOLD fMRI experiments, and representative B₀ and B₁⁺ field maps.

Simulated neuro-current time series with (a) or without (b) concomitant neural activation. Time courses (mean ± std) after each step of data processing. NEMO consists of a regression and high-pass filtering step to remove low frequency confounds (d), a rectification step converting variance differences in mean shifts (e) and extraction of the peak magnitude in the frequency spectrum at the task frequency (f). SVarM uses GLM regression to remove low frequency confounds (h), then pools the data into ON and OFF groups and tests the difference in their variance with Levene’s test (i-j).