Definition
Software is defined by as “a plan specification composed of a series of instructions that can be interpreted by or directly executed by a processing unit.” We define Software for Neuroimaging Data Analysis as software whose primary goal is to support the extraction of information, and ultimately knowledge, from data acquired by an imaging device used on the brain (of human or animal subjects).
Detailed Description
Introduction
Tell us what you think about neuroimaging software, and we will tell you who you are. To some, using software to analyze data is little more than a technical step that stands between data acquisition and publishing. Doctoral students, postdocs, or technical assistants only need to operate the appropriate software, i.e., the script to run or the right sequence of buttons to press. To others, choosing, adapting, running, or developing the right software code is critical and requires investing significant time and resources.
Data analysis is one of the...
This is a preview of subscription content, log in via an institution.
References
Ad-Dab’bagh Y, Lyttelton O, Muehlboeck JS, Lepage C, Einarson D, Mok K, Ivanov O, Vincent RD, Lerch J, Fombonne E (2006) The CIVET image-processing environment: a fully automated comprehensive pipeline for anatomical neuroimaging research. In: Proceedings of the 12th annual meeting of the organization for human brain mapping, M. Corbetta, p S45
Amazon. Amazon Elastic Compute Cloud (EC2) (n.d.) http://aws.amazon.com/ec2
Amazon. Amazon Web Service (AWS) (n.d.) http://aws.amazon.com/.
Ashburner J (2012) SPM: a history. Neuroimage 62(2):791–800. doi:10.1016/j.neuroimage.2011.10.025
Avants BB, Yushkevich P, Pluta J, Minkoff D, Korczykowski M, Detre J, Gee JC (2010) The optimal template effect in hippocampus studies of diseased populations. Neuroimage 49(3):2457–2466. doi:10.1016/j.neuroimage.2009.09.062
Baggerly KA, Coombes KR (2009) Deriving chemosensitivity from cell lines: forensic bioinformatics and reproducible research in high-throughput biology. Ann Appl Stat 3(4):1309–1334. doi:10.1214/09-AOAS291
Baillet S, Karl F, Robert O (2011) Academic software applications for electromagnetic brain mapping using MEG and EEG. Comput Intell Neurosci. doi:10.1155/2011/972050
Begley CG, Ellis LM (2012) Drug development: raise standards for preclinical cancer research. Nature 483(7391):531–533
Biswal BB, Mennes M, Zuo XN, Gohel S, Kelly C, Smith SM, Beckmann CF et al (2010) Toward discovery science of human brain function. Proc Natl Acad Sci 107(10):4734–4739. doi:10.1073/pnas.0911855107
Di Martino A, Yan C-G, Li Q, Denio E, Castellanos FX, Alaerts K, Anderson JS et al (2013) The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry. doi:10.1038/mp.2013.78
Donoho DL (2010) An invitation to reproducible computational research. Biostatistics 11(3):385–388. doi:10.1093/biostatistics/kxq028
Donoho DL, Maleki A, Rahman IU, Shahram M, Stodden V (2009) Reproducible research in computational harmonic analysis. Comput Sci Eng 11(1):8–18
Ed Gronenschild HBM, Habets P, Jacobs HIL, Mengelers R, Rozendaal N, van Os J, Marcelis M (2012) The effects of FreeSurfer version, workstation type, and Macintosh operating system version on anatomical volume and cortical thickness measurements. PLoS One 7(6):e38234. doi:10.1371/journal.pone.0038234
Fischl B (2012) FreeSurfer. Neuroimage 62(2):774–781. doi:10.1016/j.neuroimage.2012.01.021
Goebel R (1996) BRAINVOYAGER: a program for analyzing and visualizing functional and structural magnetic resonance data sets. Neuroimage 3(3):S604. doi:10.1016/S1053-8119(96)80606-9
Halchenko YO, Hanke M (2012) Open is not enough. Let’s take the next step: an integrated, community-driven computing platform for neuroscience. Front Neuroinf 6:22. doi:10.3389/fninf.2012.00022
Hall D, Huerta MF, McAuliffe MJ, Farber GK (2012) Sharing heterogeneous data: the national database for autism research. Neuroinformatics 10(4):331–339
Hanke M, Halchenko YO (2011) Neuroscience runs on GNU/Linux. Front Neuroinf 5:8. doi:10.3389/fninf.2011.00008
Ioannidis JP (2005) Why most published research findings are false. PLoS Med 2(8):e124. doi:10.1371/journal.pmed.0020124
Jenkinson M, Beckmann CF, Behrens TEF, Woolrich MW, Smith SM (2012) FSL. Neuroimage 62(2):782–790. doi:10.1016/j.neuroimage.2011.09.015
Kennedy DN, Haselgrove C, Buccigrossi R, Grethe J (2009) Software development for neuroimaging: promoting community access and best practices through NITRC. In: Biomedical imaging: from nano to macro, 2009. ISBI’09. IEEE international symposium on, IEEE, pp 1146–1149. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5193260
Klein A, Andersson J, Ardekani BA, Ashburner J, Avants B, Chiang MC, Christensen GE et al (2009) Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage 46(3):786–802. doi:10.1016/j.neuroimage.2008.12.037
Luo XZJ, Kennedy DN (2009) Neuroimaging informatics tools and resources clearinghouse (NITRC) resource announcement. Neuroinformatics 7:55–56. doi:10.1385/NI
Marcus DS, Olsen TR, Ramaratnam M, Buckner RL (2007) The extensible neuroimaging archive toolkit. Neuroinformatics 5(1):11–33
Mennes M, Biswal BB, Xavier Castellanos F, Milham MP (2013) Making data sharing work: the FCP/INDI experience. Neuroimage 82:683–691. doi:10.1016/j.neuroimage.2012.10.064
MNI Software Tools (n.d.) http://www.bic.mni.mcgill.ca/ServicesSoftware/HomePage
Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W, Trojanowski JQ, Toga AW, Beckett L (2005) Ways toward an early diagnosis in Alzheimer’s disease: the Alzheimer’s disease neuroimaging initiative (ADNI). Alzheimer Dementia 1(1):55–66
Ou Y, Sotiras A, Paragios N, Davatzikos C (2011) DRAMMS: deformable registration via attribute matching and mutual-saliency weighting. Med Image Anal 15(4):622–639. doi:10.1016/j.media.2010.07.002
Poline J-B, Breeze JL, Ghosh S, Gorgolewski K, Halchenko YO, Hanke M, Haselgrove C et al (2012) Data sharing in neuroimaging research. Front Neuroinf 6:1–13. doi:10.3389/fninf.2012.00009
Raymond E (1999) The cathedral and the bazaar. Knowl Technol Policy 12(3):23–49. doi:10.1007/s12130-999-1026-0
Simmons JP, Nelson LD, Simonsohn U (2011) False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol Sci 22(11):1359–1366. doi:10.1177/0956797611417632
The ADHD-200 Consortium (2012) The ADHD-200 consortium: a model to advance the translational potential of neuroimaging in clinical neuroscience. Front Syst Neurosci 6:62. doi:10.3389/fnsys.2012.00062
Toussaint N, Souplet JC, Fillard P (2007) MedINRIA: medical image navigation and research tool by INRIA. In: Proceedings of MICCAI, vol 7. http://med.inria.fr/
Woods RP, Cherry SR, Mazziotta JC (1992) Rapid automated algorithm for aligning and reslicing PET images. J Comput Assist Tomogr 16(4):620–633
Further Reading
Gray WR, Bogovic JA, Vogelstein JT, Landman BA, Prince JL, Vogelstein RJ (2012) Magnetic resonance connectome automated pipeline: an overview. IEEE Pulse 3(2):42–48. doi:10.1109/MPUL.2011.2181023
Johnson H, Harris G, Williams K (2007) BRAINSFit: mutual information rigid registrations of whole-brain 3D images, using the insight toolkit. http://www.insight-journal.org/download/pdf/8169/BRAINSFit.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this entry
Cite this entry
Poline, J.B., Kennedy, D. (2014). Software for Neuroimaging Data Analysis. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_538-1
Download citation
DOI: https://doi.org/10.1007/978-1-4614-7320-6_538-1
Received:
Accepted:
Published:
Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4614-7320-6
eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences