Frites

Frites is a Python toolbox for assessing information-theorical measures on human and animal neurophysiological data (M/EEG, Intracranial). The aim of Frites is to extract task-related cognitive brain networks (i.e modulated by the task). The toolbox also includes directed and undirected connectivity metrics such as group-level statistics ([Combrisson_2022a], [Combrisson_2022b]).

Official resources

• Frites documentation

• Frites GitHub

• Frites tutorials

References

Combrisson_2022a

Combrisson E, Allegra M, Basanisi R, Ince RAA, Giordano BL, Bastin J, Brovelli A. Group-level inference of information-based measures for the analyses of cognitive brain networks from neurophysiological data. Neuroimage. 2022 Sep;258:119347. doi: 10.1016/j.neuroimage.2022.119347. Epub 2022 May 31. PMID: 35660460.

Combrisson_2022b

Etienne Combrisson, Ruggero Basanisi, Vinicius Lima Cordeiro, Robin A. A Ince and Andrea Brovelli. (2022). Frites: A Python package for functional connectivity analysis and group-level statistics of neurophysiological data. Journal of Open Source Software, 7(79), 3842, https://doi.org/10.21105/joss.03842