NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines - Meunier, David; Pascarella, Annalisa; Altukhov, Dmitrii; Jas, Mainak; Combrisson, Etienne; Lajnef, Tarek; Bertrand-Dubois, Daphné; Hadid, Vanessa; Alamian, Golnoush; Alves, Jordan; Barlaam, Fanny; Saive, Anne-Lise; et al. (NeuroImage (Orlando, Fla.), 2020)
Keywords: Algorithms; Brain - diagnostic imaging; Brain imaging; Brain mapping; Brain networks; Brain research; Coding standards; Computational neuroscience; Computer programs; Data analysis; Data processing; Documentation; EEG; Electroencephalography; Electroencephalography (EEG); Electrophysiology; Functional connectivity; Functional magnetic resonance imaging; Graph theory; Humans; Interfaces; Life Sciences; Magnetic Resonance Imaging; Magnetoencephalography; Magnetoencephalography (MEG); Medical imaging; MNE; MRI; Multi-modality; Nerve Net - diagnostic imaging; Nervous system; Neural networks; Neuroimaging; Neuroimaging - methods; Neurons and Cognition; Nipype; Packaging; Pipelines; Python; Quantitative Methods; Replication; Reproducibility of Results; Reproducible science; Signal processing; Software; Software packages; Source reconstruction; Functional connectivity; Brain imaging; MRI; MNE; Brain networks; Pipelines; Multi-modality; Electrophysiology; Source reconstruction; Graph theory; Reproducible science; Nipype; Magnetoencephalography (MEG); Electroencephalography (EEG); Python; Electrophysiology MRI; MNE Source reconstruction