In the past recent years, the Python programming language became popular and widely used in many science areas, that you can notes from huge amount of high quality scientific libraries available in GitHub. Python has already won the confidence in neuro-imaging community
Analysis of different neuroimaging modalities consists of identifying such a complex pipeline that include supporting specific MRI data acquisition, image processing, statistics and predictive modeling, and visualization of the results. Nilearn is a Python package designed to face these challenges. It provides state-of-the-art machine-learning methods for analysis task fMRI, resting-state, or anathomical data. In my talk, I would like to present general purpose of Nilearn, focusing on functional connectivity and connectome analysis in resting-state fMRI.