gastropy.neuro.fmri.compute_surrogate_plv_map

gastropy.neuro.fmri.compute_surrogate_plv_map#

gastropy.neuro.fmri.compute_surrogate_plv_map(egg_phase, bold_phases, vol_shape=None, mask_indices=None, artifact_mask=None, **kwargs)[source]#

Compute a surrogate PLV map via circular time-shifting.

Same as compute_plv_map but uses surrogate PLV to generate a null distribution map for statistical comparison.

Parameters:

  • egg_phase (array_like, shape (n_timepoints,)) – Gastric phase per volume.

  • bold_phases (array_like, shape (n_voxels, n_timepoints)) – BOLD phase per volume for each voxel.

  • vol_shape (tuple of int, optional) – 3D volume dimensions for reshaping output.

  • mask_indices (array_like, optional) – Mask indices for 3D volume reconstruction.

  • artifact_mask (array_like of bool, shape (n_timepoints,), optional) – Boolean mask where True = clean volume, False = artifact. Artifact volumes are excluded from the surrogate PLV computation.

  • **kwargs – Additional arguments passed to surrogate_plv (e.g., buffer_samples, n_surrogates, stat, seed).

Returns:

surr_plv – Surrogate PLV values. Shape depends on vol_shape and stat parameter.

Return type:

np.ndarray

See also

gastropy.coupling.surrogate_plv

Core surrogate PLV computation.

Contents