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CHANGES.rst

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<https://www.nipreps.org/devs/releases/#long-term-support-series>`__.
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This LTS version will be kindly steered and maintained by
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the group of Dr. Basile Pinsard and Prof. Pierre Bellec at
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`CRIUGM <http://www.criugm.qc.ca/>`__, (Université de Montréal).
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`CRIUGM <https://criugm.qc.ca/>`__, (Université de Montréal).
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The LTS is planned for a window of 4 years of support (i.e., until
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September 2024).
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README.rst

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:target: https://circleci.com/gh/nipreps/fmriprep/tree/master
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.. image:: https://readthedocs.org/projects/fmriprep/badge/?version=latest
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:target: http://fmriprep.readthedocs.io/en/latest/?badge=latest
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:target: https://fmriprep.org/en/latest/?badge=latest
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:alt: Documentation Status
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.. image:: https://img.shields.io/pypi/v/fmriprep.svg

REFERENCES.md

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| DVARS | https://arxiv.org/abs/1704.01469 https://doi.org/10.1101/125021 | https://nipype.readthedocs.io/en/latest/interfaces/generated/nipype.algorithms.confounds.html#computedvars |
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| Framewise displacement | | https://nipype.readthedocs.io/en/latest/interfaces/generated/nipype.algorithms.confounds.html#framewisedisplacement |
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| **Other**
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| a/tCompCor | https://doi.org/10.1016/j.neuroimage.2007.04.042 | http://nipype.readthedocs.io/en/latest/interfaces/generated/nipype.algorithms.confounds.html#compcor |
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| a/tCompCor | https://doi.org/10.1016/j.neuroimage.2007.04.042 | https://nipype.readthedocs.io/en/latest/api/generated/nipype.algorithms.confounds.html#nipype-algorithms-confounds-compcor |
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| Connectome Workbench | | https://humanconnectome.org/software/connectome-workbench
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| phdiff2fmap | https://doi.org/10.1006/nimg.2001.1054 | https://fmriprep.readthedocs.io/en/stable/sdc/estimation.html#fmriprep.interfaces.fmap.phdiff2fmap |
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| nibabel | https://doi.org/10.5281/zenodo.60808 | https://github.com/nipy/nibabel/ |

docs/usage.rst

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Logs and crashfiles are output into the
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``<output dir>/fmriprep/sub-<participant_label>/log`` directory.
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Information on how to customize and understand these files can be found on the
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`Debugging Nipype Workflows <http://nipype.readthedocs.io/en/latest/users/debug.html>`_
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`Debugging Nipype Workflows <https://miykael.github.io/nipype_tutorial/notebooks/basic_debug.html>`_
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page.
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**Support and communication**.

fmriprep/data/boilerplate.bib

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pages = {179-194},
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shorttitle = {Cortical Surface-Based Analysis},
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title = {Cortical Surface-Based Analysis: I. Segmentation and Surface Reconstruction},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811998903950},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811998903950},
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volume = 9,
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year = 1999
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}
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number = 2,
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pages = {e1005350},
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title = {Mindboggling morphometry of human brains},
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url = {http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005350},
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url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005350},
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volume = 13,
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year = 2017
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}
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pages = {26-41},
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shorttitle = {Symmetric diffeomorphic image registration with cross-correlation},
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title = {Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain},
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url = {http://www.sciencedirect.com/science/article/pii/S1361841507000606},
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url = {https://www.sciencedirect.com/science/article/pii/S1361841507000606},
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volume = 12,
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year = 2008
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}
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journal = {Frontiers in Neuroinformatics},
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language = {English},
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title = {Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion {MRI}},
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url = {http://journal.frontiersin.org/article/10.3389/fninf.2017.00017/full},
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url = {https://www.frontiersin.org/articles/10.3389/fninf.2017.00017/full},
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volume = 11,
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year = 2017
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}
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school = {Freie Universität},
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title = {Evaluating nonlinear coregistration of {BOLD} {EPI} and T1w images},
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type = {Master's Thesis},
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url = {http://hdl.handle.net/11858/00-001M-0000-002B-1CB5-A},
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url = {https://hdl.handle.net/11858/00-001M-0000-002B-1CB5-A},
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year = 2014
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}
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number = 3,
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pages = {e0152472},
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title = {Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images},
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url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152472},
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url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152472},
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volume = 11,
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year = 2016
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}
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title = {A global optimisation method for robust affine registration of brain images},
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volume = {5},
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issn = {1361-8415},
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url = {http://www.sciencedirect.com/science/article/pii/S1361841501000366},
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url = {https://www.sciencedirect.com/science/article/pii/S1361841501000366},
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doi = {10.1016/S1361-8415(01)00036-6},
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number = {2},
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urldate = {2018-07-27},
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number = 2,
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pages = {825-841},
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title = {Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811902911328},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811902911328},
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volume = 17,
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year = 2002
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}
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number = {Supplement C},
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pages = {320-341},
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title = {Methods to detect, characterize, and remove motion artifact in resting state fMRI},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811913009117},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811913009117},
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volume = 84,
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year = 2014
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}
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number = 1,
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pages = {240--256},
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title = {{An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data}},
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url = {http://linkinghub.elsevier.com/retrieve/pii/S1053811912008609},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811912008609},
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volume = 64,
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year = 2013
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}
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number = 1,
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pages = {76-85},
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title = {Evaluation of Noisy Data},
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url = {http://epubs.siam.org/doi/10.1137/0701007},
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url = {https://epubs.siam.org/doi/10.1137/0701007},
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volume = 1,
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year = 1964
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}
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number = 1,
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pages = {90-101},
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title = {A component based noise correction method ({CompCor}) for {BOLD} and perfusion based fMRI},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811907003837},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811907003837},
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volume = 37,
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year = 2007
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}
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pages = {105-124},
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series = {Mapping the Connectome},
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title = {The minimal preprocessing pipelines for the Human Connectome Project},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811913005053},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811913005053},
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volume = 80,
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year = 2013
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}
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title = {An improved model of motion-related signal changes in {fMRI}},
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volume = {144, Part A},
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issn = {1053-8119},
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url = {http://www.sciencedirect.com/science/article/pii/S1053811916304360},
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url = {https://www.sciencedirect.com/science/article/pii/S1053811916304360},
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doi = {10.1016/j.neuroimage.2016.08.051},
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abstract = {Head motion is a significant source of noise in the estimation of functional connectivity from resting-state functional MRI (rs-fMRI). Current strategies to reduce this noise include image realignment, censoring time points corrupted by motion, and including motion realignment parameters and their derivatives as additional nuisance regressors in the general linear model. However, this nuisance regression approach assumes that the motion-induced signal changes are linearly related to the estimated realignment parameters, which is not always the case. In this study we develop an improved model of motion-related signal changes, where nuisance regressors are formed by first rotating and translating a single brain volume according to the estimated motion, re-registering the data, and then performing a principal components analysis (PCA) on the resultant time series of both moved and re-registered data. We show that these “Motion Simulated (MotSim)” regressors account for significantly greater fraction of variance, result in higher temporal signal-to-noise, and lead to functional connectivity estimates that are less affected by motion compared to the most common current approach of using the realignment parameters and their derivatives as nuisance regressors. This improvement should lead to more accurate estimates of functional connectivity, particularly in populations where motion is prevalent, such as patients and young children.},
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urldate = {2017-01-18},

fmriprep/data/tests/ds000005/README

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This dataset was obtained from the OpenfMRI project (http://www.openfmri.org).
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This dataset was obtained from the OpenfMRI project (https://www.openfmri.org).
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Accession #: ds005
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Description: Mixed-gambles task
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This dataset is made available under the Public Domain Dedication and License
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v1.0, whose full text can be found at
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http://www.opendatacommons.org/licenses/pddl/1.0/.
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https://opendatacommons.org/licenses/pddl/1-0/.
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We hope that all users will follow the ODC Attribution/Share-Alike
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Community Norms (http://www.opendatacommons.org/norms/odc-by-sa/);
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Community Norms (https://opendatacommons.org/norms/odc-by-sa/);
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in particular, while not legally required, we hope that all users
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of the data will acknowledge the OpenfMRI project and NSF Grant
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OCI-1131441 (R. Poldrack, PI) in any publications.

fmriprep/data/tests/ds000005/dataset_description.json

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{
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"BIDSVersion": "1.0.0rc4",
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"License": "This dataset is made available under the Public Domain Dedication and License \nv1.0, whose full text can be found at \nhttp://www.opendatacommons.org/licenses/pddl/1.0/. \nWe hope that all users will follow the ODC Attribution/Share-Alike \nCommunity Norms (http://www.opendatacommons.org/norms/odc-by-sa/); \nin particular, while not legally required, we hope that all users \nof the data will acknowledge the OpenfMRI project and NSF Grant \nOCI-1131441 (R. Poldrack, PI) in any publications.",
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"License": "This dataset is made available under the Public Domain Dedication and License \nv1.0, whose full text can be found at \nhttps://opendatacommons.org/licenses/pddl/1-0/. \nWe hope that all users will follow the ODC Attribution/Share-Alike \nCommunity Norms (https://opendatacommons.org/norms/odc-by-sa/); \nin particular, while not legally required, we hope that all users \nof the data will acknowledge the OpenfMRI project and NSF Grant \nOCI-1131441 (R. Poldrack, PI) in any publications.",
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"Name": "Mixed-gambles task",
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"Authors": ["Tom, S.M.", "Fox, C.R.", "Trepel, C.", "Poldrack, R.A."],
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"ReferencesAndLinks": "Tom, S.M., Fox, C.R., Trepel, C., Poldrack, R.A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315(5811):515-8"

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