This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

8.12.13. nilearn.glm.cluster_level_inference

nilearn.glm.cluster_level_inference(stat_img, mask_img=None, threshold=3.0, alpha=0.05, verbose=False)[source]

Report the proportion of active voxels for all clusters defined by the input threshold.

This implements the method described in [1].

stat_imgNiimg-like object or None, optional

statistical image (presumably in z scale)

mask_imgNiimg-like object, optional,

mask image

thresholdlist of floats, optional

Cluster-forming threshold in z-scale. Default=3.0.

alphafloat or list, optional

Level of control on the true positive rate, aka true dsicovery proportion. Default=0.05.

verbosebool, optional

Verbosity mode. Default=False.


The statistical map that gives the true positive.


This function is experimental. It may change in any future release of Nilearn.



Rosenblatt JD, Finos L, Weeda WD, Solari A, Goeman JJ. All-Resolutions Inference for brain imaging. Neuroimage. 2018 Nov 1;181:786-796. doi: 10.1016/j.neuroimage.2018.07.060 Examples using nilearn.glm.cluster_level_inference