tedana.metrics.dependence.compute_signal_minus_noise_t

compute_signal_minus_noise_t(z_maps, z_clmaps, f_t2_maps, z_thresh=1.95)[source]

Compare signal and noise t-statistic distributions with a two-sample t-test.

Divide voxel-level thresholded F-statistic maps into distributions of signal (voxels in significant clusters) and noise (voxels from non-significant clusters) statistics, then compare these distributions with a two-sample t-test.

Parameters:

  • z_maps ((S x C) array_like) – Z-statistic maps for components, reflecting voxel-wise component loadings.

  • z_clmaps ((S x C) array_like) – Cluster-extent thresholded Z-statistic maps for components.

  • f_t2_maps ((S x C) array_like) – Pseudo-F-statistic maps for components from TE-dependence models. Each voxel reflects the model fit for the component weights to the TE-dependence model across echoes.

  • z_thresh (float, optional) – Z-statistic threshold for voxel-wise significance. Default is 1.95.

Returns:

  • signal_minus_noise_t ((C) array_like) – T-statistics from component-wise signal > noise paired t-tests.

  • signal_minus_noise_p ((C) array_like) – P-values from component-wise signal > noise paired t-tests.