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.


nilearn.glm.cluster_level_inference(stat_img, mask_img=None, threshold=3.0, alpha=0.05, verbose=0)[source]

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

This implements the method described in Rosenblatt et al.[1].

stat_imgNiimg-like object or None, optional

statistical image (presumably in z scale)

mask_imgNiimg-like object, optional,

mask image

thresholdlist of floats, default=3.0

Cluster-forming threshold in z-scale.

alphafloat or list, default=0.05

Level of control on the true positive rate, aka true discovery proportion.

verboseint or bool, default=0

Verbosity mode.


The statistical map that gives the true positive.


Examples using nilearn.glm.cluster_level_inference

Second-level fMRI model: true positive proportion in clusters

Second-level fMRI model: true positive proportion in clusters