P. Cook, Y. Bai, S. Nedjati-gilani, K. Seunarine, M. Hall et al., Camino: 634 Open-Source Diffusion-MRI Reconstruction and Processing, Proc. Intl. Soc. Magn. Reson, 2005.

. Med,

A. Abraham, F. Pedregosa, M. Eickenberg, P. Gervais, A. Mueller et al., , 2014.

, Machine learning for neuroimaging with scikit-learn

J. Ashburner, A fast diffeomorphic image registration algorithm, NeuroImage, vol.38, pp.95-113, 2007.

J. Ashburner, SPM: A history. Neuroimage 62-248, 2012.

J. Ashburner and K. J. Friston, Unified segmentation, NeuroImage, vol.26, pp.839-851, 2005.

B. B. Avants, C. L. Epstein, M. Grossman, and J. C. Gee, Symmetric diffeomorphic image 646 registration with cross-correlation: Evaluating automated labeling of elderly and 647 neurodegenerative brain, Medical Image Analysis, vol.12, pp.26-41, 2008.

B. B. Avants, N. J. Tustison, M. Stauffer, G. Song, B. Wu et al., The Insight 649 ToolKit image registration framework, Front Neuroinform, vol.8, 2014.

M. Brett, M. Hanke, C. Markiewicz, . Marc-alexandre, . Côté et al., , 2019.

,

Y. Cointepas, J. Mangin, L. Garnero, J. Poline, and H. Benali, BrainVISA: Software 653 platform for visualization and analysis of multi-modality brain data, NeuroImage, vol.13, pp.91441-91448, 2001.

R. W. Cox, AFNI: software for analysis and visualization of functional magnetic resonance 656 neuroimages, Comput. Biomed. Res, vol.29, pp.162-173, 1996.

R. Cuingnet, J. A. Glaunès, M. Chupin, H. Benali, and O. Colliot, Spatial and Anatomical Regularization of SVM: A General 659 Framework for Neuroimaging Data, IEEE Trans Pattern Anal Mach Intell, vol.35, pp.682-696, 2013.

R. S. Desikan, F. Ségonne, B. Fischl, B. T. Quinn, B. C. Dickerson et al., An 662 automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral 663 based regions of interest, NeuroImage, vol.31, pp.968-980, 2006.

C. Destrieux, B. Fischl, A. Dale, and E. Halgren, Automatic parcellation of human cortical 665 gyri and sulci using standard anatomical nomenclature, Neuroimage, vol.53, pp.1-15, 2010.

O. Esteban, C. J. Markiewicz, R. W. Blair, C. A. Moodie, A. I. Isik et al., 668 fMRIPrep: a robust preprocessing pipeline for functional MRI, Nat Methods, vol.16, pp.111-116, 2019.

B. Fischl, FreeSurfer, NeuroImage, vol.62, pp.774-781, 2012.

B. Fischl and A. M. Dale, Measuring the thickness of the human cerebral cortex from 672 magnetic resonance images, PNAS, vol.97, pp.11050-11055, 2000.

B. Fischl, D. H. Salat, E. Busa, M. Albert, M. Dieterich et al., Whole Brain 674 Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain, 2002.

, Neuron, vol.33, pp.341-355

B. Fischl, D. H. Salat, A. J. Van-der-kouwe, N. Makris, F. Ségonne et al., , 2004.

, Sequence-independent segmentation of magnetic resonance images, NeuroImage, vol.23

B. Fischl, M. I. Sereno, and A. M. Dale, Cortical Surface-Based Analysis: II: Inflation, 680 Flattening, and a Surface-Based Coordinate System, NeuroImage, vol.9, pp.195-207, 1999.

B. Fischl, A. Van-der-kouwe, C. Destrieux, E. Halgren, F. Ségonne et al., , 2004.

, Automatically Parcellating the Human Cerebral Cortex. Cerebral Cortex, vol.14

C. Foulon, L. Cerliani, S. Kinkingnéhun, R. Levy, C. Rosso et al., Advanced 686 lesion symptom mapping analyses and implementation as BCBtoolkit, 2018.

R. S. Frackowiak, K. J. Friston, C. Frith, R. Dolan, and J. Mazziotta, Human Brain 689 Function, 1997.

K. Friston, J. Ashburner, S. Kiebel, T. Nichols, and W. Penny, Statistical Parametric 692 Mapping, 2007.

K. J. Friston, C. D. Frith, R. S. Frackowiak, and R. Turner, Characterizing Dynamic Brain 694 Responses with fMRI: A Multivariate Approach, NeuroImage, vol.2, pp.166-172, 1995.

E. Garyfallidis, M. Brett, B. Amirbekian, A. Rokem, S. Van-der-walt et al., , 2014.

, Dipy, a library for the analysis of diffusion MRI data

T. Glatard, G. Kiar, T. Aumentado-armstrong, N. Beck, P. Bellec et al., , 2017.

, Boutiques: a flexible framework for automated application integration in computing platforms, vol.701, 2018.

K. Gorgolewski, C. D. Burns, C. Madison, D. Clark, Y. O. Halchenko et al., , 2011.

:. Nipype and . Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in 705 Python, Front. Neuroinform, vol.5

K. J. Gorgolewski, F. Alfaro-almagro, T. Auer, P. Bellec, M. Capot? et al., BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging 708 data analysis methods, PLOS Computational Biology, vol.13, 2017.

K. J. Gorgolewski, T. Auer, V. D. Calhoun, R. C. Craddock, S. Das et al., The 711 brain imaging data structure, a format for organizing and describing outputs of neuroimaging 712 experiments, Scientific Data, vol.3, p.160044, 2016.

I. S. Gousias, D. Rueckert, R. A. Heckemann, L. E. Dyet, J. P. Boardman et al., Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest, p.714, 2008.

, NeuroImage, vol.40, pp.672-684

Y. O. Halchenko and M. Hanke, Open is Not Enough. Let's Take the Next Step: An 717 Integrated, Community-Driven Computing Platform for, Neuroscience. Front. Neuroinform. 6, vol.718, 2012.

A. Hammers, R. Allom, M. J. Koepp, S. L. Free, R. Myers et al., Three-720 dimensional maximum probability atlas of the human brain, with particular reference to the 721 temporal lobe, Human Brain Mapping, vol.19, pp.224-247, 2003.

R. N. Henson, C. Buechel, O. Josephs, and K. J. Friston, The slice-timing problem in 723 event-related fMRI, NeuroImage, vol.9, p.125, 1999.

K. Hua, J. Zhang, S. Wakana, H. Jiang, X. Li et al., Tract probability maps in 725 stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification, 2008.

, NeuroImage, vol.39, pp.336-347

M. Jenkinson, C. F. Beckmann, T. E. Behrens, M. W. Woolrich, and S. M. Smith, Neuroimage, vol.62, pp.782-790, 2012.

M. Joliot, G. Jobard, M. Naveau, N. Delcroix, L. Petit et al., AICHA: An atlas of 730 intrinsic connectivity of homotopic areas, Journal of Neuroscience Methods, vol.254, pp.46-59, 2015.

E. Jones, T. Oliphant, and P. Peterson, SciPy: Open source scientific tools for Python, vol.733, 2001.

A. D. Leow, I. Yanovsky, M. C. Chiang, A. D. Lee, A. D. Klunder et al., Statistical 735 Properties of Jacobian Maps and the Realization of Unbiased Large-Deformation Nonlinear 736 Image Registration, IEEE Transactions on Medical Imaging, vol.26, 2007.

W. Mckinney, Data Structures for Statistical Computing in Python, Proceedings of the 9th, 2010.

S. Mori, S. Wakana, L. Nagae-poetscher, and P. Van-zijl, MRI Atlas of Human White Matter, 2005.

. Amsterdam,

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-743 learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, 2011.

J. Poline, J. L. Breeze, S. S. Ghosh, K. Gorgolewski, Y. O. Halchenko et al., , 2012.

, Data sharing in neuroimaging research, Front. Neuroinform, vol.6

A. Routier, Imagerie cérébrale multimodale pour l'étude des aphasies primaires progressives, vol.747, 2018.

J. Samper-gonzález, N. Burgos, S. Bottani, S. Fontanella, P. Lu et al., , 2018.

, Reproducible evaluation of classification methods in Alzheimer's disease: Framework and 750 application to MRI and PET data, NeuroImage

A. M. Savio, M. Schutte, M. Graña, Y. , and I. , Pypes: Workflows for Processing, p.752, 2017.

, Multimodal Neuroimaging Data. Front Neuroinform, vol.11

D. W. Shattuck, M. Mirza, V. Adisetiyo, C. Hojatkashani, G. Salamon et al., , 2008.

, Construction of a 3D probabilistic atlas of human cortical structures, NeuroImage, vol.39, p.1080

B. A. Thomas, V. Cuplov, A. Bousse, A. Mendes, K. Thielemans et al., , 2016.

, PETPVC: a toolbox for performing partial volume correction techniques in positron emission 758 tomography, Physics in Medicine and Biology, vol.61, pp.7975-7993

J. Tournier, F. Calamante, and A. Connelly, Robust determination of the fibre orientation 761 distribution in diffusion MRI: Non-negativity constrained super-resolved spherical 762 deconvolution, NeuroImage, vol.35, pp.1459-1472, 2007.

J. Tournier, F. Calamante, and A. Connelly, Improved probabilistic streamlines 764 tractography by 2nd order integration over fibre orientation distributions, Proceedings of the 765 International Society for Magnetic Resonance in Medicine Available at: 766, 2010.

J. Tournier, F. Calamante, and A. Connelly, MRtrix: Diffusion tractography in crossing 769 fiber regions, Int. J. Imaging Syst. Technol, vol.22, pp.53-66, 2012.

N. J. Tustison, B. B. Avants, P. A. Cook, Y. Zheng, A. Egan et al., , 2010.

, N4ITK: Improved N3 Bias Correction, vol.29

N. Tzourio-mazoyer, B. Landeau, D. Papathanassiou, F. Crivello, O. Etard et al., Automated Anatomical Labeling of Activations in SPM Using a Macroscopic 775, p.774, 2002.

, Anatomical Parcellation of the MNI MRI Single-Subject Brain, NeuroImage, vol.15, pp.273-289

S. Van-der-walt, S. C. Colbert, and G. Varoquaux, The NumPy Array: A Structure for Efficient 778 Numerical Computation, Comput. Sci. Eng, vol.13, pp.22-30, 2011.

S. Wakana, A. Caprihan, M. M. Panzenboeck, J. H. Fallon, M. Perry et al., , 2007.

, Reproducibility of quantitative tractography methods applied to cerebral white matter

, NeuroImage, vol.36, pp.630-644

K. Worsley, J. Taylor, F. Carbonell, M. Chung, E. Duerden et al., SurfStat: 783 A Matlab toolbox for the statistical analysis of univariate and multivariate surface and 784 volumetric data using linear mixed effects models and random field theory, NeuroImage, vol.47, p.102, 2009.