General bibliography#

The references below are arranged alphabetically by first author. You can download the bib file here.

  1. Hunar Abdulrahman and Richard N Henson. Effect of trial-to-trial variability on optimal event-related fmri design: implications for beta-series correlation and multi-voxel pattern analysis. NeuroImage, 125:756–766, 2016.

  2. Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, and Gael Varoquaux. Region segmentation for sparse decompositions: better brain parcellations from rest fMRI. Sparsity Techniques in Medical Imaging, September 2014. URL: https://hal.inria.fr/hal-01093944.

  3. Elena Allen, Erik Erhardt, Eswar Damaraju, William Gruner, Judith Segall, Rogers Silva, Martin Havlicek, Srinivas Rachakonda, Jill Fries, Ravi Kalyanam, Andrew Michael, Arvind Caprihan, Jessica Turner, Tom Eichele, Steven Adelsheim, Angela Bryan, Juan Bustillo, Vincent Clark, Sarah Feldstein Ewing, Francesca Filbey, Corey Ford, Kent Hutchison, Rex Jung, Kent Kiehl, Piyadasa Kodituwakku, Yuko Komesu, Andrew Mayer, Godfrey Pearlson, John Phillips, Joseph Sadek, Michael Stevens, Ursina Teuscher, Robert Thoma, and Vince Calhoun. A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5:2, 2011. URL: https://www.frontiersin.org/article/10.3389/fnsys.2011.00002, doi:10.3389/fnsys.2011.00002.

  4. Marti J. Anderson and John Robinson. Permutation tests for linear models. Australian & New Zealand Journal of Statistics, 43(1):75–88, 2001. URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-842X.00156, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/1467-842X.00156, doi:https://doi.org/10.1111/1467-842X.00156.

  5. Luca Baldassarre, Janaina Mourao-Miranda, and Massimiliano Pontil. Structured sparsity models for brain decoding from fmri data. In 2012 Second International Workshop on Pattern Recognition in NeuroImaging, volume, 5–8. 2012. URL: http://www0.cs.ucl.ac.uk/staff/M.Pontil/reading/neurosparse_prni.pdf, doi:10.1109/PRNI.2012.31.

  6. Yashar Behzadi, Khaled Restom, Joy Liau, and Thomas T. Liu. A component based noise correction method (compcor) for bold and perfusion based fmri. NeuroImage, 37(1):90–101, 2007. URL: https://www.sciencedirect.com/science/article/pii/S1053811907003837, doi:https://doi.org/10.1016/j.neuroimage.2007.04.042.

  7. Pierre Bellec. Mining the hierarchy of resting-state brain networks: selection of representative clusters in a multiscale structure. In 2013 International Workshop on Pattern Recognition in Neuroimaging, volume, 54–57. 06 2013. doi:10.1109/PRNI.2013.23.

  8. Pierre Bellec, Pedro Rosa-Neto, Oliver C. Lyttelton, Habib Benali, and Alan C. Evans. Multi-level bootstrap analysis of stable clusters in resting-state fmri. NeuroImage, 51(3):1126–1139, 2010. URL: https://www.sciencedirect.com/science/article/pii/S1053811910002697, doi:https://doi.org/10.1016/j.neuroimage.2010.02.082.

  9. Rastko Ciric, Daniel H. Wolf, Jonathan D. Power, David R. Roalf, Graham L. Baum, Kosha Ruparel, Russell T. Shinohara, Mark A. Elliott, Simon B. Eickhoff, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Danielle S. Bassett, and Theodore D. Satterthwaite. Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. NeuroImage, 154(1):174–187, 2017. doi:10.1016/j.neuroimage.2017.03.020.

  10. Josh M Cisler, Keith Bush, and J Scott Steele. A comparison of statistical methods for detecting context-modulated functional connectivity in fmri. Neuroimage, 84:1042–1052, 2014.

  11. Alex Clarke and Lorraine K. Tyler. Object-specific semantic coding in human perirhinal cortex. Journal of Neuroscience, 34(14):4766–4775, 2014. URL: https://www.jneurosci.org/content/34/14/4766, arXiv:https://www.jneurosci.org/content/34/14/4766.full.pdf, doi:10.1523/JNEUROSCI.2828-13.2014.

  12. D. Louis Collins, Alex P. Zijdenbos, Wim F. C. Baaré, and Alan C. Evans. Animal+insect: improved cortical structure segmentation. In Attila Kuba, Martin Šáamal, and Andrew Todd-Pokropek, editors, Information Processing in Medical Imaging, 210–223. Berlin, Heidelberg, 1999. Springer Berlin Heidelberg.

  13. R. Cameron Craddock, G.Andrew James, Paul E. Holtzheimer III, Xiaoping P. Hu, and Helen S. Mayberg. A whole brain fmri atlas generated via spatially constrained spectral clustering. Human Brain Mapping, 33(8):1914–1928, 2012. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.21333, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.21333, doi:https://doi.org/10.1002/hbm.21333.

  14. Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit, Krzysztof J. Gorgolewski, Demian Wassermann, Bertrand Thirion, and Arthur Mensch. Fine-grain atlases of functional modes for fmri analysis. NeuroImage, 221:117126, 2020. URL: https://www.sciencedirect.com/science/article/pii/S1053811920306121, doi:https://doi.org/10.1016/j.neuroimage.2020.117126.

  15. Russell Davidson and James G. MacKinnon. Econometric theory and methods. Oxford Univ. Press, New York, NY [u.a.], 2004. ISBN 978-0-19-512372-2. URL: http://gso.gbv.de/DB=2.1/CMD?ACT=SRCHA&SRT=YOP&IKT=1016&TRM=ppn+393847152&sourceid=fbw_bibsonomy.

  16. C Destrieux, B Fischl, AM Dale, and E Halgren. A sulcal depth-based anatomical parcellation of the cerebral cortex. NeuroImage, 47(Supplement 1):S151, 2009. doi:10.1016/S1053-8119(09)71561-7.

  17. Christophe Destrieux, Bruce Fischl, Anders Dale, and Eric Halgren. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. NeuroImage, 53(1):1–15, 2010. URL: https://www.sciencedirect.com/science/article/pii/S1053811910008542, doi:https://doi.org/10.1016/j.neuroimage.2010.06.010.

  18. Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, and Gaël Varoquaux. Speeding-up model-selection in GraphNet via early-stopping and univariate feature-screening. In PRNI. Stanford, United States, June 2015. URL: https://hal.inria.fr/hal-01147731.

  19. Elvis Dohmatob, Alexandre Gramfort, Bertrand Thirion, and Gaël Varoquaux. Benchmarking solvers for TV-l1 least-squares and logistic regression in brain imaging. In PRNI 2014 - 4th International Workshop on Pattern Recognition in NeuroImaging. Tübingen, Germany, June 2014. IEEE. URL: https://hal.inria.fr/hal-00991743.

  20. Nico U. F. Dosenbach, Binyam Nardos, Alexander L. Cohen, Damien A. Fair, Jonathan D. Power, Jessica A. Church, Steven M. Nelson, Gagan S. Wig, Alecia C. Vogel, Christina N. Lessov-Schlaggar, Kelly Anne Barnes, Joseph W. Dubis, Eric Feczko, Rebecca S. Coalson, John R. Pruett, Deanna M. Barch, Steven E. Petersen, and Bradley L. Schlaggar. Prediction of individual brain maturity using fmri. Science, 329(5997):1358–1361, 2010. URL: https://science.sciencemag.org/content/329/5997/1358, arXiv:https://science.sciencemag.org/content/329/5997/1358.full.pdf, doi:10.1126/science.1194144.

  21. John Duchi, Stephen Gould, and Daphne Koller. Projected subgradient methods for learning sparse gaussians. arXiv:1206.3249 [cs, stat], 06 2012. URL: https://arxiv.org/abs/1206.3249, arXiv:1206.3249.

  22. Joset A. Etzel, Jeffrey M. Zacks, and Todd S. Braver. Searchlight analysis: promise, pitfalls, and potential. NeuroImage, 78:261–269, 2013. URL: https://www.sciencedirect.com/science/article/pii/S1053811913002917, doi:https://doi.org/10.1016/j.neuroimage.2013.03.041.

  23. Nicola Filippini, Bradley J. MacIntosh, Morgan G. Hough, Guy M. Goodwin, Giovanni B. Frisoni, Stephen M. Smith, Paul M. Matthews, Christian F. Beckmann, and Clare E. Mackay. Distinct patterns of brain activity in young carriers of the apoe-ε4 allele. Proceedings of the National Academy of Sciences, 106(17):7209–7214, 2009. URL: https://www.pnas.org/content/106/17/7209, arXiv:https://www.pnas.org/content/106/17/7209.full.pdf, doi:10.1073/pnas.0811879106.

  24. Bruce Fischl, Martin I. Sereno, Roger B.H. Tootell, and Anders M. Dale. High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8(4):272–284, 1999. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291097-0193%281999%298%3A4%3C272%3A%3AAID-HBM10%3E3.0.CO%3B2-4, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291097-0193%281999%298%3A4%3C272%3A%3AAID-HBM10%3E3.0.CO%3B2-4, doi:https://doi.org/10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4.

  25. Bruce Fischl, André van der Kouwe, Christophe Destrieux, Eric Halgren, Florent Ségonne, David H. Salat, Evelina Busa, Larry J. Seidman, Jill Goldstein, David Kennedy, Verne Caviness, Nikos Makris, Bruce Rosen, and Anders M. Dale. Automatically Parcellating the Human Cerebral Cortex. Cerebral Cortex, 14(1):11–22, 01 2004. URL: https://doi.org/10.1093/cercor/bhg087, arXiv:https://academic.oup.com/cercor/article-pdf/14/1/11/1193353/bhg087.pdf, doi:10.1093/cercor/bhg087.

  26. R.A. Fisher. The design of experiments. 1935. Oliver and Boyd, Edinburgh, 1935.

  27. P. Thomas Fletcher and Sarang Joshi. Riemannian geometry for the statistical analysis of diffusion tensor data. Signal Processing, 87(2):250–262, 2007. Tensor Signal Processing. URL: https://www.sciencedirect.com/science/article/pii/S0165168406001691, doi:https://doi.org/10.1016/j.sigpro.2005.12.018.

  28. Vladimir Fonov, Alan C. Evans, Kelly Botteron, C. Robert Almli, Robert C. McKinstry, and D. Louis Collins. Unbiased average age-appropriate atlases for pediatric studies. NeuroImage, 54(1):313–327, 2011. URL: https://www.sciencedirect.com/science/article/pii/S1053811910010062, doi:https://doi.org/10.1016/j.neuroimage.2010.07.033.

  29. VS Fonov, AC Evans, RC McKinstry, CR Almli, and DL Collins. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. NeuroImage, 47(Supplement 1):S102, 2009. doi:10.1016/S1053-8119(09)70884-5.

  30. Michael D. Fox, Abraham Z. Snyder, Justin L Vincent, Maurizio Corbetta, David C. Van Essen, and Marcus E. Raichle. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102(27):9673–9678, July 2005. doi:10.1073/pnas.0504136102.

  31. David Freedman and David Lane. A nonstochastic interpretation of reported significance levels. Journal of Business & Economic Statistics, 1(4):292–298, 1983. URL: https://www.tandfonline.com/doi/abs/10.1080/07350015.1983.10509354, arXiv:https://www.tandfonline.com/doi/pdf/10.1080/07350015.1983.10509354, doi:10.1080/07350015.1983.10509354.

  32. K. J. Friston, A. P. Holmes, K. J. Worsley, J.-P. Poline, C. D. Frith, and R. S. J. Frackowiak. Statistical parametric maps in functional imaging: a general linear approach. Human Brain Mapping, 2(4):189–210, 1994. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.460020402, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.460020402, doi:https://doi.org/10.1002/hbm.460020402.

  33. Krzysztof J. Gorgolewski, Gael Varoquaux, Gabriel Rivera, Yannick Schwarz, Satrajit S. Ghosh, Camille Maumet, Vanessa V. Sochat, Thomas E. Nichols, Russell A. Poldrack, Jean-Baptiste Poline, Tal Yarkoni, and Daniel S. Margulies. Neurovault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers in Neuroinformatics, 9:8, 2015. URL: https://www.frontiersin.org/article/10.3389/fninf.2015.00008, doi:10.3389/fninf.2015.00008.

  34. Alexandre Gramfort, Bertrand Thirion, and Gaël Varoquaux. Identifying predictive regions from fMRI with TV-L1 prior. In Pattern Recognition in Neuroimaging (PRNI). Philadelphia, United States, June 2013. IEEE. URL: https://hal.inria.fr/hal-00839984.

  35. William H. Greene. Econometric Analysis. Pearson Education, fifth edition, 2003. ISBN 0-13-066189-9. URL: http://pages.stern.nyu.edu/~wgreene/Text/econometricanalysis.htm.

  36. Logan Grosenick, Brad Klingenberg, Kiefer Katovich, Brian Knutson, and Jonathan E. Taylor. Interpretable whole-brain prediction analysis with graphnet. NeuroImage, 72:304–321, 2013. URL: https://www.sciencedirect.com/science/article/pii/S1053811912012487, doi:https://doi.org/10.1016/j.neuroimage.2012.12.062.

  37. James V. Haxby, M. Ida Gobbini, Maura L. Furey, Alumit Ishai, Jennifer L. Schouten, and Pietro Pietrini. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293(5539):2425–2430, 2001. URL: https://science.sciencemag.org/content/293/5539/2425, arXiv:https://science.sciencemag.org/content/293/5539/2425.full.pdf, doi:10.1126/science.1063736.

  38. Jean Honorio, Tommi Jaakkola, and Dimitris Samaras. On the statistical efficiency of l1,p multi-task learning of gaussian graphical models. arXiv:1207.4255 [cs, stat], 10 2015. URL: https://arxiv.org/abs/1207.4255, arXiv:1207.4255.

  39. Andres Hoyos-Idrobo, Gael Varoquaux, Jonas Kahn, and Bertrand Thirion. Recursive nearest agglomeration (rena): fast clustering for approximation of structured signals. IEEE Trans. Pattern Anal. Mach. Intell., 41(3):669–681, 3 2019. URL: https://doi.org/10.1109/TPAMI.2018.2815524, doi:10.1109/TPAMI.2018.2815524.

  40. Andrés Hoyos-Idrobo, Gaël Varoquaux, Yannick Schwartz, and Bertrand Thirion. Frem – scalable and stable decoding with fast regularized ensemble of models. NeuroImage, 180:160–172, 2018. New advances in encoding and decoding of brain signals. URL: https://www.sciencedirect.com/science/article/pii/S1053811917308182, doi:https://doi.org/10.1016/j.neuroimage.2017.10.005.

  41. Koji Jimura and Russell A. Poldrack. Analyses of regional-average activation and multivoxel pattern information tell complementary stories. Neuropsychologia, 50(4):544–552, 2012. Multivoxel pattern analysis and cognitive theories. URL: https://www.sciencedirect.com/science/article/pii/S0028393211005070, doi:https://doi.org/10.1016/j.neuropsychologia.2011.11.007.

  42. Thorsten Kahnt, Marcus Grueschow, Oliver Speck, and John-Dylan Haynes. Perceptual learning and decision-making in human medial frontal cortex. Neuron, 70(3):549–559, 2011. URL: https://www.sciencedirect.com/science/article/pii/S0896627311002960, doi:https://doi.org/10.1016/j.neuron.2011.02.054.

  43. Nikolaus Kriegeskorte, Rainer Goebel, and Peter Bandettini. Information-based functional brain mapping. Proceedings of the National Academy of Sciences, 103(10):3863–3868, 2006. URL: https://www.pnas.org/content/103/10/3863, doi:10.1073/pnas.0600244103.

  44. Angela R. Laird, P. Mickle Fox, Simon B. Eickhoff, Jessica A. Turner, Kimberly L. Ray, D. Reese McKay, David C. Glahn, Christian F. Beckmann, Stephen M. Smith, and Peter T. Fox. Behavioral Interpretations of Intrinsic Connectivity Networks. Journal of Cognitive Neuroscience, 23(12):4022–4037, 12 2011. URL: https://doi.org/10.1162/jocn\_a\_00077, arXiv:https://direct.mit.edu/jocn/article-pdf/23/12/4022/1777164/jocn\_a\_00077.pdf, doi:10.1162/jocn_a_00077.

  45. J.L. Lancaster, L.H. Rainey, J.L. Summerlin, C.S. Freitas, P.T. Fox, A.C. Evans, A.W. Toga, and J.C. Mazziotta. Automated labeling of the human brain: a preliminary report on the development and evaluation of a forward-transform method. Human Brain Mapping, 5(4):238–242, 1997. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291097-0193%281997%295%3A4%3C238%3A%3AAID-HBM6%3E3.0.CO%3B2-4, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291097-0193%281997%295%3A4%3C238%3A%3AAID-HBM6%3E3.0.CO%3B2-4, doi:https://doi.org/10.1002/(SICI)1097-0193(1997)5:4<238::AID-HBM6>3.0.CO;2-4.

  46. Jack L. Lancaster, Marty G. Woldorff, Lawrence M. Parsons, Mario Liotti, Catarina S. Freitas, Lacy Rainey, Peter V. Kochunov, Dan Nickerson, Shawn A. Mikiten, and Peter T. Fox. Automated talairach atlas labels for functional brain mapping. Human Brain Mapping, 10(3):120–131, 2000. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/1097-0193%28200007%2910%3A3%3C120%3A%3AAID-HBM30%3E3.0.CO%3B2-8, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/1097-0193%28200007%2910%3A3%3C120%3A%3AAID-HBM30%3E3.0.CO%3B2-8, doi:https://doi.org/10.1002/1097-0193(200007)10:3<120::AID-HBM30>3.0.CO;2-8.

  47. Martin A. Lindquist, Stephan Geuter, Tor D. Wager, and Brian S. Caffo. Modular preprocessing pipelines can reintroduce artifacts into fmri data. bioRxiv, 2018. URL: https://www.biorxiv.org/content/early/2018/09/04/407676, arXiv:https://www.biorxiv.org/content/early/2018/09/04/407676.full.pdf, doi:10.1101/407676.

  48. Daniel S. Marcus, Tracy H. Wang, Jamie Parker, John G. Csernansky, John C. Morris, and Randy L. Buckner. Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults. Journal of Cognitive Neuroscience, 19(9):1498–1507, 09 2007. URL: https://doi.org/10.1162/jocn.2007.19.9.1498, arXiv:https://direct.mit.edu/jocn/article-pdf/19/9/1498/1756878/jocn.2007.19.9.1498.pdf, doi:10.1162/jocn.2007.19.9.1498.

  49. Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, and Bertrand Thirion. Total variation regularization for fMRI-based prediction of behaviour. IEEE Transactions on Medical Imaging, 30(7):1328 – 1340, February 2011. URL: https://hal.inria.fr/inria-00563468, doi:10.1109/TMI.2011.2113378.

  50. Yoichi Miyawaki, Hajime Uchida, Okito Yamashita, Masa-aki Sato, Yusuke Morito, Hiroki C. Tanabe, Norihiro Sadato, and Yukiyasu Kamitani. Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. Neuron, 60(5):915–929, 2008. URL: https://www.sciencedirect.com/science/article/pii/S0896627308009586, doi:https://doi.org/10.1016/j.neuron.2008.11.004.

  51. Douglas C. Montgomery, Elizabeth A. Peck, and Geoffrey G. Vining. Introduction to Linear Regression Analysis (4th ed.). Wiley & Sons, 2006. ISBN 0471754951.

  52. Jeanette A Mumford, Benjamin O Turner, F Gregory Ashby, and Russell A Poldrack. Deconvolving bold activation in event-related designs for multivoxel pattern classification analyses. Neuroimage, 59(3):2636–2643, 2012.

  53. Thomas Naselaris, Kendrick N. Kay, Shinji Nishimoto, and Jack L. Gallant. Encoding and decoding in fmri. NeuroImage, 56(2):400–410, May 2011. 20691790[pmid]. URL: https://pubmed.ncbi.nlm.nih.gov/20691790, doi:10.1016/j.neuroimage.2010.07.073.

  54. Jared Nielsen, Brandon Zielinski, P Fletcher, Andrew Alexander, Nicholas Lange, Erin Bigler, Janet Lainhart, and Jeffrey Anderson. Multisite functional connectivity mri classification of autism: abide results. Frontiers in Human Neuroscience, 7:599, 2013. URL: https://www.frontiersin.org/article/10.3389/fnhum.2013.00599, doi:10.3389/fnhum.2013.00599.

  55. Kate Nooner, Stanley Colcombe, Russell Tobe, Maarten Mennes, Melissa Benedict, Alexis Moreno, Laura Panek, Shaquanna Brown, Stephen Zavitz, Qingyang Li, Sharad Sikka, David Gutman, Saroja Bangaru, Rochelle Tziona Schlachter, Stephanie Kamiel, Ayesha Anwar, Caitlin Hinz, Michelle Kaplan, Anna Rachlin, Samantha Adelsberg, Brian Cheung, Ranjit Khanuja, Chaogan Yan, Cameron Craddock, Vincent Calhoun, William Courtney, Margaret King, Dylan Wood, Christine Cox, Clare Kelly, Adriana DiMartino, Eva Petkova, Philip Reiss, Nancy Duan, Dawn Thompsen, Bharat Biswal, Barbara Coffey, Matthew Hoptman, Daniel Javitt, Nunzio Pomara, John Sidtis, Harold Koplewicz, Francisco Castellanos, Bennett Leventhal, and Michael Milham. The nki-rockland sample: a model for accelerating the pace of discovery science in psychiatry. Frontiers in Neuroscience, 6:152, 2012. URL: https://www.frontiersin.org/article/10.3389/fnins.2012.00152, doi:10.3389/fnins.2012.00152.

  56. Jill X. O'Reilly, Christian F. Beckmann, Valentina Tomassini, Narender Ramnani, and Heidi Johansen-Berg. Distinct and Overlapping Functional Zones in the Cerebellum Defined by Resting State Functional Connectivity. Cerebral Cortex, 20(4):953–965, 08 2009. URL: https://doi.org/10.1093/cercor/bhp157, arXiv:https://academic.oup.com/cercor/article-pdf/20/4/953/17303287/bhp157.pdf, doi:10.1093/cercor/bhp157.

  57. Linden Parkes, Ben Fulcher, Murat Yücel, and Alex Fornito. An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage, 171:415–436, May 2018. doi:10.1016/j.neuroimage.2017.12.073.

  58. Wolfgang M. Pauli, Amanda N. Nili, and J. Michael Tyszka. A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei. Scientific Data, 5(1):180063, Apr 2018. URL: https://doi.org/10.1038/sdata.2018.63, doi:10.1038/sdata.2018.63.

  59. Philippe Pinel, Bertrand Thirion, Sébastien Meriaux, Antoinette Jobert, Julien Serres, Denis Le Bihan, Jean-Baptiste Poline, and Stanislas Dehaene. Fast reproducible identification and large-scale databasing of individual functional cognitive networks. BMC Neuroscience, 2007.

  60. R.A. Poldrack, E. Congdon, W. Triplett, K.J. Gorgolewski, K.H. Karlsgodt, J.A. Mumford, F.W. Sabb, N.B. Freimer, E.D. London, T.D. Cannon, and R.M. Bilder. A phenome-wide examination of neural and cognitive function. Scientific Data, 3(1):160110, December 2016. URL: https://doi.org/10.1038/sdata.2016.110, doi:10.1038/sdata.2016.110.

  61. Jonathan D. Power. A simple but useful way to assess fmri scan qualities. NeuroImage, 154:150–158, 2017. Cleaning up the fMRI time series: Mitigating noise with advanced acquisition and correction strategies. URL: https://www.sciencedirect.com/science/article/pii/S1053811916303871, doi:https://doi.org/10.1016/j.neuroimage.2016.08.009.

  62. Jonathan D. Power, Kelly A. Barnes, Abraham Z. Snyder, Bradley L. Schlaggar, and Steven E. Petersen. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3):2142–2154, 2012. URL: http://www.ncbi.nlm.nih.gov/pubmed/22019881 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3254728, doi:10.1016/j.neuroimage.2011.10.018.

  63. Jonathan D. Power, Alexander L. Cohen, Steven M. Nelson, Gagan S. Wig, Kelly Anne Barnes, Jessica A. Church, Alecia C. Vogel, Timothy O. Laumann, Fran M. Miezin, Bradley L. Schlaggar, and Steven E. Petersen. Functional network organization of the human brain. Neuron, 72(4):665–678, Nov 2011. URL: https://doi.org/10.1016/j.neuron.2011.09.006, doi:10.1016/j.neuron.2011.09.006.

  64. Jonathan D. Power, Anish Mitra, Timothy O. Laumann, Abraham Z. Snyder, Bradley L. Schlaggar, and Steven E. Petersen. Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage, 84:320–341, 2014. URL: http://www.sciencedirect.com/science/article/pii/S1053811913009117, doi:10.1016/j.neuroimage.2013.08.048.

  65. Raimon H. R. Pruim, Maarten Mennes, Daan van Rooij, Alberto Llera, Jan K. Buitelaar, and Christian F. Beckmann. ICA-AROMA: a robust ICA-based strategy for removing motion artifacts from fMRI data. Neuroimage, 112:267–277, 2015. doi:10.1016/j.neuroimage.2015.02.064.

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