Welcome to ConnInfPy’s documentation!

ConnInfPy (Connectivity Inference in Python) is a Python package for statistical inference on brain connectivity networks (fMRI, EEG). It provides permutation-based tests for group comparisons (t-test) and continuous predictors with confound regression (GLM with Freedman-Lane), together with a family of enhancement methods: classical NBS, TFNBS (Threshold-Free Network-Based Statistics), cNBS, network-informed TFNBS, and functional-block clustering TFNBS. The TFNBS family eliminates the need for an arbitrary statistical threshold by integrating cluster statistics across a range of thresholds via TFCE-style enhancement.

Contents:

• Installation
• Usage
• How Inference Works
• Recommended Workflows
• conninfpy
• References

To cite this toolbox you can use the following: doi:………

[Cite ConnInfPy as]