NeuroQuery, comprehensive meta-analysis of human brain mapping

Abstract

Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and terminology poses a fundamental challenge to relating brain imaging results across the scientific literature. Existing meta-analysis methods perform statistical tests on sets of publications associated with a particular concept. Thus, large-scale meta-analyses only tackle single terms that occur frequently. We propose a new paradigm, focusing on prediction rather than inference. Our multivariate model predicts the spatial distribution of neurological observations, given text describing an experiment, cognitive process, or disease. This approach handles text of arbitrary length and terms that are too rare for standard meta-analysis. We capture the relationships and neural correlates of 7547 neuroscience terms across 13 459 neuroimaging publications. The resulting meta-analytic tool, neuroquery.org, can ground hypothesis generation and data-analysis priors on a comprehensive view of published findings on the brain.

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References 53

1. 1.

   Bishop CM. Pattern Recognition and Machine Learning. 2006.

   Not in our library

2. 2.

   Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. Journal of Machine Learning Research. 2003;3:993-1022.

   Not in our library

3. 3.

   Bouma G. Normalized (pointwise) mutual information in collocation extraction. 2009;31-40.

   Not in our library

4. 4.

   Bowden DM, Martin RF. NeuroNames brain hierarchy. NeuroImage. 1995;2:63-83.

   Not in our library10.1006/nimg.1995.1009

5. 5.

   Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, Munafò MR. Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience. 2013;14:365-376.

   Not in our library10.1038/nrn3475

6. 6.

   Cichocki A, Phan A-H. Fast local algorithms for large scale nonnegative matrix and tensor factorizations. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2009;E92-A:708-721.

   Not in our library10.1587/transfun.e92.a.708

7. 7.

   Deerwester S, Dumais ST, Furnas GW, Landauer TK, Harshman R. Indexing by latent semantic analysis. Journal of the American Society for Information Science. 1990;41:391-407.

   Not in our library10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9

8. 8.

   Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31:968-980.

   Not in our library10.1016/j.neuroimage.2006.01.021

9. 9.

   Eickhoff SB, Laird AR, Grefkes C, Wang LE, Zilles K, Fox PT. Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping. 2009;30:2907-2926.

   Not in our library10.1002/hbm.20718

10. 10.

    Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters. 2006;27:861-874.

    Not in our library10.1016/j.patrec.2005.10.010

11. 11.

    Gaonkar B, Davatzikos C. Deriving statistical significance maps for svm based image classification and group comparisons. 2012;723-730.

    Not in our library10.1007/978-3-642-33415-3_89

12. 12.

    Gardner D, Akil H, Ascoli GA, Bowden DM, Bug W, Donohue DE, Goldberg DH, Grafstein B, Grethe JS, Gupta A, Halavi M, Kennedy DN, Marenco L, Martone ME, Miller PL, Müller HM, Robert A, Shepherd GM, Sternberg PW, Van Essen DC, Williams RW. The neuroscience information framework: a data and knowledge environment for neuroscience. Neuroinformatics. 2008;6:149-160.

    Not in our library10.1007/s12021-008-9024-z

13. 13.

    Humphries C, Binder JR, Medler DA, Liebenthal E. Syntactic and semantic modulation of neural activity during auditory sentence comprehension. Journal of Cognitive Neuroscience. 2006;18:665-679.

    Not in our library10.1162/jocn.2006.18.4.665

14. 14.

    Kang J, Johnson TD, Nichols TE, Wager TD. Meta analysis of functional neuroimaging data via bayesian spatial point processes. Journal of the American Statistical Association. 2011;106:124-134.

    Not in our library10.1198/jasa.2011.ap09735

15. 15.

    Laird AR, Lancaster JJ, Fox PT. Brainmap. Neuroinformatics. 2005;3:65-77.

    Not in our library10.1385/ni:3:1:065

16. 16.

    Lancaster JL, Tordesillas-Gutiérrez D, Martinez M, Salinas F, Evans A, Zilles K, Mazziotta JC, Fox PT. Bias between MNI and talairach coordinates analyzed using the ICBM-152 brain template. Human Brain Mapping. 2007;28:1194-1205.

    Not in our library10.1002/hbm.20345

17. 17.

    Lee DD, Seung HS. Learning the parts of objects by non-negative matrix factorization. Nature. 1999;401:788-791.

    Not in our library10.1038/44565

18. 18.

    Lipscomb CE. Medical subject headings (mesh). Bulletin of the Medical Library Association. 2000;88:265.

    Not in our library

19. 19.

    Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. Distributed representations of words and phrases and their compositionality. 2013;3111-3119.

    Not in our library

20. 20.

    Mitchell TM, Shinkareva SV, Carlson A, Chang KM, Malave VL, Mason RA, Just MA. Predicting human brain activity associated with the meanings of nouns. Science. 2008;320:1191-1195.

    Not in our library10.1126/science.1152876

21. 21.

    Naselaris T, Kay KN, Nishimoto S, Gallant JL. Encoding and decoding in fMRI. NeuroImage. 2011;56:400-410.

    Not in our library10.1016/j.neuroimage.2010.07.073

22. 22.

    Newell A. You can’t play 20 questions with nature and win: Projective comments on the papers of this symposium. 1973.

    Not in our library

23. 23.

    Nielsen FA, Hansen LK, Balslev D. Mining for associations between text and brain activation in a functional neuroimaging database. Neuroinformatics. 2004;2:369-380.

    Not in our library10.1385/ni:2:4:369

24. 24.

    Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V. Scikit-learn: machine learning in Python. Journal of Machine Learning Research. 2011;12:2825-2830.

    Not in our library

25. 25.

    Piantadosi ST. Zipf's word frequency law in natural language: a critical review and future directions. Psychonomic Bulletin & Review. 2014;21:1112-1130.

    Not in our library10.3758/s13423-014-0585-6

26. 26.

    Pinho AL, Amadon A, Ruest T, Fabre M, Dohmatob E, Denghien I, Ginisty C, Becuwe-Desmidt S, Roger S, Laurier L, Joly-Testault V, Médiouni-Cloarec G, Doublé C, Martins B, Pinel P, Eger E, Varoquaux G, Pallier C, Dehaene S, Hertz-Pannier L, Thirion B. Individual brain charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data. 2018;5:180105.

    Not in our library10.1038/sdata.2018.105

27. 27.

    Poldrack RA. Can cognitive processes be inferred from neuroimaging data? Trends in Cognitive Sciences. 2006;10:59-63.

    Not in our library10.1016/j.tics.2005.12.004

28. 28.

    Poldrack RA. Subtraction and beyond: the logic of experimental designs for neuroimaging. In Foundational Issues in Human Brain Mapping. 2010;147:14.

    Not in our library10.7551/mitpress/9780262014021.003.0014

29. 29.

    Poldrack RA, Mumford JA, Nichols TE. Handbook of Functional MRI Data Analysis. 2011.

    Not in our library10.1017/cbo9780511895029

30. 30.
    Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping · 2012

    No notice
31. 31.

    Poldrack RA, Baker CI, Durnez J, Gorgolewski KJ, Matthews PM, Munafò MR, Nichols TE, Poline JB, Vul E, Yarkoni T. Scanning the horizon: towards transparent and reproducible neuroimaging research. Nature Reviews Neuroscience. 2017;18:115-126.

    Not in our library10.1038/nrn.2016.167

32. 32.

    Poldrack RA, Yarkoni T. From brain maps to cognitive ontologies: informatics and the search for mental structure. Annual Review of Psychology. 2016;67:587-612.

    Not in our library10.1146/annurev-psych-122414-033729

33. 33.

    Rifkin RM, Lippert RA. Notes on Regularized Least Squares. 2007.

    Not in our library

34. 34.

    Rubin TN, Koyejo O, Gorgolewski KJ, Jones MN, Poldrack RA, Yarkoni T. Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition. PLOS Computational Biology. 2017;13:e1005649.

    Not in our library10.1371/journal.pcbi.1005649

35. 35.

    Salimi-Khorshidi G, Smith SM, Keltner JR, Wager TD, Nichols TE. Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. NeuroImage. 2009;45:810-823.

    Not in our library10.1016/j.neuroimage.2008.12.039

36. 36.

    Salton G, Buckley C. Term-weighting approaches in automatic text retrieval. Information Processing & Management. 1988;24:513-523.

    Not in our library10.1016/0306-4573(88)90021-0

37. 37.

    Sayers E. The e-utilities in-depth: parameters, syntax and more. Entrez Programming Utilities Help [Internet]. 2009.

    Not in our library

38. 38.

    Scott DW. Multivariate Density Estimation: Theory, Practice, and Visualization. 2015.

    Not in our library10.1002/9780470316849

39. 39.

    Silverman BW. Density Estimation for Statistics and Data Analysis. 1986.

    Not in our library

40. 40.

    Sitek EJ, Thompson JC, Craufurd D, Snowden JS. Unawareness of deficits in Huntington's disease. Journal of Huntington's Disease. 2014;3:125-135.

    Not in our library10.3233/jhd-140109

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