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}

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    title = {Nipype},
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    journal = {Software}
}

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    year = 2010
}

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}



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    journal = {PLOS Computational Biology},
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    pages = {e1005350},
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    volume = 13,
    year = 2017
}

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    author = {Mazziotta, John C. and Toga, Arthur W. and Evans, Alan and Fox, Peter and Lancaster, Jack},
    volume = {2},
    issn = {1053-8119},
    shorttitle = {A {Probabilistic} {Atlas} of the {Human} {Brain}},
    doi = {10.1006/nimg.1995.1012},
    number = {2, Part A},
    journal = {NeuroImage},
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    pages = {89--101}
}

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    volume = {47, Supplement 1},
    year = 2009
}

@article{mni152nlin6asym,
    author = {Evans, AC and Janke, AL and Collins, DL and Baillet, S},
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}

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    url = {https://www.sciencedirect.com/science/article/pii/S1361841507000606},
    volume = 12,
    year = 2008
}

@article{fsl_fast,
    author = {Zhang, Y. and Brady, M. and Smith, S.},
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    journal = {IEEE Transactions on Medical Imaging},
    number = 1,
    pages = {45-57},
    title = {Segmentation of brain {MR} images through a hidden Markov random field model and the expectation-maximization algorithm},
    volume = 20,
    year = 2001
}


@article{fieldmapless1,
    author = {Wang, Sijia and Peterson, Daniel J. and Gatenby, J. C. and Li, Wenbin and Grabowski, Thomas J. and Madhyastha, Tara M.},
    doi = {10.3389/fninf.2017.00017},
    issn = {1662-5196},
    journal = {Frontiers in Neuroinformatics},
    language = {English},
    title = {Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion {MRI}},
    url = {https://www.frontiersin.org/articles/10.3389/fninf.2017.00017/full},
    volume = 11,
    year = 2017
}

@phdthesis{fieldmapless2,
    address = {Berlin},
    author = {Huntenburg, Julia M.},
    language = {eng},
    school = {Freie Universität},
    title = {Evaluating nonlinear coregistration of {BOLD} {EPI} and T1w images},
    type = {Master's Thesis},
    url = {https://hdl.handle.net/11858/00-001M-0000-002B-1CB5-A},
    year = 2014
}

@article{fieldmapless3,
    author = {Treiber, Jeffrey Mark and White, Nathan S. and Steed, Tyler Christian and Bartsch, Hauke and Holland, Dominic and Farid, Nikdokht and McDonald, Carrie R. and Carter, Bob S. and Dale, Anders Martin and Chen, Clark C.},
    doi = {10.1371/journal.pone.0152472},
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    journal = {PLOS ONE},
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    pages = {e0152472},
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    year = 2016
}

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    volume = {5},
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    number = {2},
    urldate = {2018-07-27},
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    author = {Jenkinson, Mark and Smith, Stephen},
    year = {2001},
    keywords = {Affine transformation, flirt, fsl, Global optimisation, Multi-resolution search, Multimodal registration, Robustness},
    pages = {143--156}
}

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    number = 2,
    pages = {825-841},
    title = {Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images},
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    volume = 17,
    year = 2002
}

@article{bbr,
    author = {Greve, Douglas N and Fischl, Bruce},
    doi = {10.1016/j.neuroimage.2009.06.060},
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    pages = {63-72},
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    volume = 48,
    year = 2009
}

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    journal = {NeuroImage},
    number = {Supplement C},
    pages = {320-341},
    title = {Methods to detect, characterize, and remove motion artifact in resting state fMRI},
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    volume = 84,
    year = 2014
}

@article{confounds_satterthwaite_2013,
    author = {Satterthwaite, Theodore D. and Elliott, Mark A. and Gerraty, Raphael T. and Ruparel, Kosha and Loughead, James and Calkins, Monica E. and Eickhoff, Simon B. and Hakonarson, Hakon and Gur, Ruben C. and Gur, Raquel E. and Wolf, Daniel H.},
    doi = {10.1016/j.neuroimage.2012.08.052},
    issn = {10538119},
    journal = {NeuroImage},
    number = 1,
    pages = {240--256},
    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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    volume = 64,
    year = 2013
}


@article{nilearn,
    author = {Abraham, Alexandre and Pedregosa, Fabian and Eickenberg, Michael and Gervais, Philippe and Mueller, Andreas and Kossaifi, Jean and Gramfort, Alexandre and Thirion, Bertrand and Varoquaux, Gael},
    doi = {10.3389/fninf.2014.00014},
    issn = {1662-5196},
    journal = {Frontiers in Neuroinformatics},
    language = {English},
    title = {Machine learning for neuroimaging with scikit-learn},
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    year = 2014
}

@article{lanczos,
    author = {Lanczos, C.},
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    pages = {76-85},
    title = {Evaluation of Noisy Data},
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    year = 1964
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    pages = {90-101},
    title = {A component based noise correction method ({CompCor}) for {BOLD} and perfusion based fMRI},
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    year = 2007
}

@article{hcppipelines,
    author = {Glasser, Matthew F. and Sotiropoulos, Stamatios N. and Wilson, J. Anthony and Coalson, Timothy S. and Fischl, Bruce and Andersson, Jesper L. and Xu, Junqian and Jbabdi, Saad and Webster, Matthew and Polimeni, Jonathan R. and Van Essen, David C. and Jenkinson, Mark},
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    journal = {NeuroImage},
    pages = {105-124},
    series = {Mapping the Connectome},
    title = {The minimal preprocessing pipelines for the Human Connectome Project},
    url = {https://www.sciencedirect.com/science/article/pii/S1053811913005053},
    volume = 80,
    year = 2013
}

@article{fs_template,
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    title = {Highly accurate inverse consistent registration: A robust approach},
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    year = 2010
}

@article{afni,
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    year = 1997
}

@article{posse_t2s,
    author = {Posse, Stefan and Wiese, Stefan and Gembris, Daniel and Mathiak, Klaus and Kessler, Christoph and Grosse-Ruyken, Maria-Liisa and Elghahwagi, Barbara and Richards, Todd and Dager, Stephen R. and Kiselev, Valerij G.},
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    journal = {Magnetic Resonance in Medicine},
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    pages = {87-97},
    title = {Enhancement of {BOLD}-contrast sensitivity by single-shot multi-echo functional {MR} imaging},
    volume = 42,
    year = 1999
}

@article{topup,
    author = {Jesper L.R. Andersson and Stefan Skare and John Ashburner},
    title = {How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging},
    journal = {NeuroImage},
    volume = 20,
    number = 2,
    pages = {870-888},
    year = 2003,
    issn = {1053-8119},
    doi = {10.1016/S1053-8119(03)00336-7},
    url = {https://www.sciencedirect.com/science/article/pii/S1053811903003367}
}

@article{patriat_improved_2017,
    title = {An improved model of motion-related signal changes in {fMRI}},
    volume = {144, Part A},
    issn = {1053-8119},
    url = {https://www.sciencedirect.com/science/article/pii/S1053811916304360},
    doi = {10.1016/j.neuroimage.2016.08.051},
    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.},
    urldate = {2017-01-18},
    journal = {NeuroImage},
    author = {Patriat, Rémi and Reynolds, Richard C. and Birn, Rasmus M.},
    month = jan,
    year = {2017},
    keywords = {Motion, Correction, Methods, Rs-fMRI},
    pages = {74--82},
}
