title: Machine learning for neuroimaging with scikit-learn.
abstract: Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Abraham
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Fabian
authors.initials: F
authors.lastname: Pedregosa
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Michael
authors.initials: M
authors.lastname: Eickenberg
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Gervais
authors.affiliation: Institute of Computer Science VI, University of Bonn Bonn, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Mueller
authors.affiliation: Department of Computing, Imperial College London London, UK.
authors.forename: Jean
authors.initials: J
authors.lastname: Kossaifi
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France ; Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI Paris, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Gramfort
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Bertrand
authors.initials: B
authors.lastname: Thirion
authors.affiliation: Parietal Team, INRIA Saclay-Île-de-France Saclay, France ; Neurospin, I2 BM, DSV, CEA Gif-Sur-Yvette, France.
authors.forename: Gaël
authors.initials: G
authors.lastname: Varoquaux
keywords: Python; machine learning; neuroimaging; scikit-learn; statistical learning