Giga Connectome: a BIDS-app for time series and functional connectome extraction

Researchers perform two steps before functional magnetic resonance imaging (fMRI) data analysis: standardised preprocessing and customised denoising.fMRIPrep (Esteban et al., 2019; RRID:SCR_016216), a popular software in the neuroimaging community, is a common choice for preprocessing.fMRIPrep performs minimal preprocessing, leaving a few steps for the end user: smoothing, denoising, and standardisation.The present software, giga-connectome, is a Brain Imaging Data Structure (BIDS; Gorgolewski et al., 2016; RRID:SCR_016124) compliant container image that aims to perform these steps as well as extract time series signals and generate connectomes for machine learning applications.All these steps are implemented with functions from nilearn (Nilearn contributors, 2024; RRID:SCR_001362), a Python library for machine learning in neuroimaging.