Ten simple rules for neuroimaging meta-analysis

Neuroscience and Biobehavioral Reviews

Volumn 84, Issue , 2018, Pages 151-161

  Müller, Veronika I ^a,b   Cieslik, Edna C ^a,b   Laird, Angela R ^c   Fox, Peter T ^d,e,f   Radua, Joaquim ^g,h,i   Mataix Cols, David ^h   Tench, Christopher R ^j   Yarkoni, Tal ^k   Nichols, Thomas E ^l,m   Turkeltaub, Peter E ^n,o   Wager, Tor D ^p   Eickhoff, Simon B ^a,b  

^a HEINRICH HEINE UNIVERSITY   (Germany)

^b FORSCHUNGSZENTRUM JÜLICH   (Germany)

^c FLORIDA INTERNATIONAL UNIVERSITY   (United States)

^d UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

^e VETERANS AFFAIRS MEDICAL CENTER   (United States)

^f SHENZHEN UNIVERSITY   (China)

^g CENTRO DE INVESTIGACIÓN BIOMÉDICA EN RED DE SALUD MENTAL CIBERSAM   (Spain)

^h KAROLINSKA INSTITUTE   (Sweden)

ⁱ KING'S COLLEGE LONDON   (United Kingdom)

^j UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^k UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^l UNIVERSITY OF WARWICK   (United Kingdom)

^m UNIVERSITY OF WARWICK   (United Kingdom)

ⁿ GEORGETOWN UNIVERSITY MEDICAL CENTER   (United States)

^o NATIONAL REHABILITATION HOSPITAL   (United States)

^p UNIVERSITY OF COLORADO   (United States)

more..

Author keywords

fMRI; Guidelines; Meta analysis; Neuroimaging; PET; Ten simple rules

Indexed keywords

ANTERIOR CINGULATE; COGNITION; DORSOLATERAL PREFRONTAL CORTEX; FALSE POSITIVE RESULT; FUNCTIONAL MAGNETIC RESONANCE IMAGING; INFORMATION PROCESSING; INFORMATION RETRIEVAL; META ANALYSIS (TOPIC); NEUROIMAGING; POSITRON EMISSION TOMOGRAPHY; PRACTICE GUIDELINE; PRIORITY JOURNAL; REVIEW; HUMAN; STANDARDS;

GUIDELINES AS TOPIC; HUMANS; META-ANALYSIS AS TOPIC; NEUROIMAGING;

EID: 85036521642     PISSN: 01497634     EISSN: 18737528     Source Type: Journal    
DOI: 10.1016/j.neubiorev.2017.11.012     Document Type: Review

References (62)

1. Ahmed, I., Sutton, A.J., Riley, R.D., Assessment of publication bias, selection bias, and unavailable data in meta-analyses using individual participant data: a database survey. Br. Med. J., 344, 2012.
2. Alegria, A.A., Radua, J., Rubia, K., Meta-analysis of fMRI studies of disruptive behavior disorders. Am. J. Psychiatry 173 (2016), 1119–1130.
3. Alustiza, I., Radua, J., Albajes-Eizagirre, A., Dominguez, M., Auba, E., Ortuno, F., Meta-analysis of functional neuroimaging and cognitive control studies in Schizophrenia: preliminary elucidation of a core dysfunctional timing network. Front. Psychol., 7, 2016, 192.
4. American Psychological Association, Publication Manual of the American Psychological Association. 6th ed., 2010, American Psychological Association, Washington, DC.
5. Brett, M., Christoff, K., Cusack, R., Lancaster, J., Using the Talairach atlas with the MNI template. NeuroImage, 13, 2001, S85.
6. Brett, M., Johnsrude, I.S., Owen, A.M., The problem of functional localization in the human brain. Nat. Rev. Neurosci. 3 (2002), 243–249.
7. Button, K.S., Ioannidis, J.P., Mokrysz, C., Nosek, B.A., Flint, J., Robinson, E.S., Munafo, M.R., Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14 (2013), 365–376.
8. Carp, J., On the plurality of (methodological) worlds: estimating the analytic flexibility of FMRI experiments. Front. Neurosci., 6, 2012, 149.
9. Carter, R., The Brain Book. 2014, Dorling Kindersley, London.
10. Chumbley, J.R., Friston, K.J., False discovery rate revisited: FDR and topological inference using Gaussian random fields. NeuroImage 44 (2009), 62–70.
11. Cieslik, E.C., Müller, V.I., Eickhoff, C.R., Langner, R., Eickhoff, S.B., Three key regions for supervisory attentional control: evidence from neuroimaging meta-analyses. Neurosci. Biobehav. Rev. 48 (2015), 22–34.
12. Cieslik, E.C., Seidler, I., Laird, A.R., Fox, P.T., Eickhoff, S.B., Different involvement of subregions within dorsal premotor and medial frontal cortex for pro- and antisaccades. Neurosci. Biobehav. Rev. 68 (2016), 256–269.
13. Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C., Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomogr. 18 (1994), 192–205.
14. Costafreda, S.G., David, A.S., Brammer, M.J., A parametric approach to voxel-based meta-analysis. Neuroimage 46 (2009), 115–122.
15. Daniel, T.A., Katz, J.S., Robinson, J.L., Delayed match-to-sample in working memory: a BrainMap meta-analysis. Biol. Psychol. 120 (2016), 10–20.
16. Diggle, P.J., Statistics: a data science for the 21st century. J. R. Stat. Soc. Ser. A (Stat. Soc.) 178:4 (2015), 793–813.
17. Eickhoff, S.B., Laird, A.R., Grefkes, C., Wang, L.E., Zilles, K., Fox, P.T., Coordinate-based ALE meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty. Hum. Brain Mapp. 30 (2009), 2907–2926.
18. Eickhoff, S.B., Bzdok, D., Laird, A.R., Kurth, F., Fox, P.T., Activation likelihood estimation meta-analysis revisited. NeuroImage 59 (2012), 2349–2361.
19. Eickhoff, S.B., Nichols, T.E., Laird, A.R., Hoffstaedter, F., Amunts, K., Fox, P.T., Bzdok, D., Eickhoff, C.R., Behavior, Sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation. NeuroImage 137 (2016), 70–85.
20. Eklund, A., Nichols, T.E., Knutsson, H., Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc. Natl. Acad. Sci. U. S. A. 113 (2016), 7900–7905.
21. Forstmeier, W., Wagenmakers, E.J., Parker, T.H., Detecting and avoiding likely false-positive findings—a practical guide. Biol. Rev. Camb. Philos. Soc. 92:4 (2017), 1941–1968.
22. Fox, P.T., Lancaster, J.L., Opinion: mapping context and content: the BrainMap model. Nat. Rev. Neurosci. 3 (2002), 319–321.
23. Fox, K.C.R., Spreng, R.N., Ellamil, M., Andrews-Hanna, J.R., Christoff, K., The wandering brain: meta-analysis of functional neuroimaging studies of mind-wandering and related spontaneous thought processes. NeuroImange 111 (2015), 611–621.
24. Gilbert, S.J., Spengler, S., Simons, J.S., Frith, C.D., Burgess, P.W., Differential functions of lateral and medial rostral prefrontal cortex (area 10) revealed by brain-behavior associations. Cereb. Cortex 16 (2006), 1783–1789.
25. Gorgolewski, K.J., Varoquaux, G., Rivera, G., Schwarz, Y., Ghosh, S.S., Maumet, C., Sochat, V.V., Nichols, T.E., Poldrack, R.A., Poline, J.B., Yarkoni, T., Margulies, D.S., NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Front. Neuroinf., 9, 2015, 8.
26. Ioannidis, J.P., Munafo, M.R., Fusar-Poli, P., Nosek, B.A., David, S.P., Publication and other reporting biases in cognitive sciences: detection, prevalence, and prevention. Trends Cognit. Sci. 18 (2014), 235–241.
27. Kicinski, M., How does under-reporting of negative and inconclusive results affect the false-positive rate in meta-analysis? A simulation study. BMJ Open, 4, 2014, e004831.
28. Kurkela, K.A., Dennis, N.A., Event-related fMRI studies of false memory: an activation likelihood estimation meta-analysis. Neuropsychologia 81 (2016), 149–167.
29. Laird, A.R., Lancaster, J.L., Fox, P.T., BrainMap: the social evolution of a human brain mapping database. Neuroinformatics 3 (2005), 65–78.
30. Laird, A.R., Riedel, M.C., Sutherland, M.T., Eickhoff, S.B., Ray, K.L., Uecker, A.M., Fox, P.M., Turner, J.A., Fox, P.T., Neural architecture underlying classification of face perception paradigms. NeuroImage 119 (2015), 70–80.
31. Lancaster, J.L., Tordesillas-Gutierrez, D., Martinez, M., Salinas, F., Evans, A., Zilles, K., Mazziotta, J.C., Fox, P.T., Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Hum. Brain Mapp. 28 (2007), 1194–1205.
32. Langner, R., Eickhoff, S.B., Sustaining attention to simple tasks: a meta-analytic review of the neural mechanisms of vigilant attention. Psychol. Bull. 139 (2013), 870–900.
33. Lieberman, M.D., Cunningham, W.A., Type I and Type II error concerns in fMRI research: re-balancing the scale. Soc. Cognit. Affect. Neurosci. 4 (2009), 423–428.
34. Müller, V.I., Cieslik, E.C., Serbanescu, I., Laird, A.R., Fox, P.T., Eickhoff, S.B., Altered brain activity in unipolar depression revisited: meta-analyses of neuroimaging studies. JAMA Psychiatry 74:1 (2017), 47–55.
35. Nichols, T.E., Das, S., Eickhoff, S.B., Evans, A.C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M.P., Poldrack, R.A., Poline, J.-B., Proal, E., Thirion, B., Van Essen, D.C., White, T., Yeo, B.T.T., Best practices in data analysis and sharing in neuroimaging using MRI. Nat. Neurosci. 20:3 (2017), 299–303.
36. Pauli, W.M., OReilly, R.C., Yarkoni, T., Wager, T.D., Regional Specialization within the human striatum for diverse psychological functions. Proc. Natl. Acad. Sci. U. S. A. 113:7 (2016), 1907–1912.
37. Purcell, J.J., Turkeltaub, P.E., Eden, G.F., Rapp, B., Examining the central and peripheral processes of written word production through meta-analysis. Front. Psychol., 2, 2011, 239.
38. Radua, J., Mataix-Cols, D., Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br. J. Psychiatry 195 (2009), 393–402.
39. Radua, J., Mataix-Cols, D., Meta-analytic methods for neuroimaging data explained. Biol. Mood Anxiety Disorders, 2, 2012, 6.
40. Radua, J., Mataix-Cols, D., Phillips, M.L., El-Hage, W., Kronhaus, D.M., Cardoner, N., Surguladze, S., A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur. Psychiatry 27 (2012), 605–611.
41. Reid, A.T., Bzdok, D., Genon, S., Langner, R., Muller, V.I., Eickhoff, C.R., Hoffstaedter, F., Cieslik, E.C., Fox, P.T., Laird, A.R., Amunts, K., Caspers, S., Eickhoff, S.B., ANIMA: a data-sharing initiative for neuroimaging meta-analyses. NeuroImage 124 (2016), 1245–1253.
42. Remijnse, P.L., Nielen, M.M., van Balkom, A.J., Hendriks, G.J., Hoogendijk, W.J., Uylings, H.B., Veltman, D.J., Differential frontal-striatal and paralimbic activity during reversal learning in major depressive disorder and obsessive-compulsive disorder. Psychol. Med. 39 (2009), 1503–1518.
43. Rosenthal, R., The file drawer problem and tolerance for null results. Psychol. Bull. 86 (1979), 638–641.
44. Rottschy, C., Langner, R., Dogan, I., Reetz, K., Laird, A.R., Schulz, J.B., Fox, P.T., Eickhoff, S.B., Modelling neural correlates of working memory: a coordinate-based meta-analysis. NeuroImage 60 (2012), 830–846.
45. Rubia, K., Alegria, A.A., Cubillo, A.I., Smith, A.B., Brammer, M.J., Radua, J., Effects of stimulants on brain function in attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. Biol. Psychiatry 76 (2014), 616–628.
46. Salimi-Khorshidi, G., Smith, S.M., Keltner, J.R., Wager, T.D., Nichols, T.E., Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. NeuroImage 45 (2009), 810–823.
47. Salimi-Khorshidi, G., Nichols, T.E., Smith, S.M., Woolrich, M.W., Using Gaussian-process regression for meta-analytic neuroimaging inference based on sparse observations. IEEE Trans. Med. Imaging 30 (2011), 1401–1416.
48. Simmons, J.P., Nelson, L.D., Simonsohn, U., False-positive psychology: undisclosed flexibility in datacollection and analysis allows presenting anything as significant. Psychol. Sci. 22 (2011), 1359–1366.
49. Spreng, R.N., Wojtowicz, M., Grady, C.L., Reliable differences in brain activity between young and old adults: a quantitative meta-analysis across multiple cognitive domains. Neurosci. Biobehav. Rev. 34 (2010), 1178–1194.
50. Talairach, J., Tournoux, P., Co-Planar Stereotaxic Atlas of the Human Brain. 1988, Thieme, New York.
51. Tench, C.R., Tanasescu, R., Auer, D.P., Constantinescu, C.S., Coordinate based meta-analysis of functional neuroimaging data; false discovery rate control and diagnostics. PLoS One, 8, 2013, e70143.
52. Tench, C.R., Tanasescu, R., Auer, D.P., Cottam, W.J., Constantinescu, C.S., Coordinate based meta-analysis of functional neuroimaging data using activation likelihood estimation; full width half max and group comparisons. PLoS One, 9, 2014, 3106734.
53. Turkeltaub, P.E., Eden, G.F., Jones, K.M., Zeffiro, T.A., Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. NeuroImage 16 (2002), 765–780.
54. Turkeltaub, P.E., Messing, S., Norise, C., Hamilton, R.H., Are networks for residual language function and recovery consistent across aphasic patients?. Neurology 76 (2011), 1726–1734.
55. Turkeltaub, P.E., Eickhoff, S.B., Laird, A.R., Fox, M., Wiener, M., Fox, P., Minimizing within-experiment and within-group effects in Activation Likelihood Estimation meta-analyses. Hum. Brain Mapp. 33 (2012), 1–13.
56. Wager, T.D., Jonides, J., Reading, S., Neuroimaging studies of shifting attention: a meta-analysis. NeuroImage 22 (2004), 1679–1693.
57. Wager, T.D., Lindquist, M., Kaplan, L., Meta-analysis of functional neuroimaging data: current and future directions. Soc. Cognit. Affect. Neurosci. 2 (2007), 150–158.
58. Wager, T.D., Lindquist, M.A., Nichols, T.E., Kober, H., Van Snellenberg, J.X., Evaluating the consistency and specificity of neuroimaging data using meta-analysis. NeuroImage 45 (2009), S210–221.
59. Woo, C.W., Krishnan, A., Wager, T.D., Cluster-extent based thresholding in fMRI analyses: pitfalls and recommendations. NeuroImage 91 (2014), 412–419.
60. Yang, D.Y., Rosenblau, G., Keifer, C., Pelphrey, K.A., An integrative neural model of social perception, action observation, and theory of mind. Neurosci. Biobehav. Rev. 51 (2015), 263–275.
61. Yarkoni, T., Poldrack, R.A., Nichols, T.E., Van Essen, D.C., Wager, T.D., Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8 (2011), 665–670.
62. zu Eulenburg, P., Caspers, S., Roski, C., Eickhoff, S.B., Meta-analytical definition and functional connectivity of the human vestibular cortex. NeuroImage 60 (2012), 162–169.