Acar, F., Maumet, C., Heuten, T., Vervoort, M., Bossier, H., Seurinck, R., & Moerkerke, B. (2022). Review paper: reporting practices for task fMRI studies. Neuroinformatics.

Acar, F., Seurinck, R., Eickhoff, S. B., & Moerkerke, B. (2018). Assessing robustness against potential publication bias in Activation Likelihood Estimation (ALE) meta-analyses for fMRI. PLoS ONE, 13, 1–23. https://doi.org/10.1371/journal.pone.0208177

Article  CAS  Google Scholar 

Bossier, H., Nichols, T. E., & Moerkerke, B. (2019). Standardized effect sizes and image-based meta-analytical approaches for fMRI data. bioRxiv. https://doi.org/10.1101/865881

Bowring, A., Maumet, C., & Nichols, T. E. (2019). Exploring the impact of analysis software on task fMRI results. Human Brain Mapping, 40, 3362–3384.

Article  PubMed  PubMed Central  Google Scholar 

Button, K. S., Ioannidis, J. P., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S., & Munafo, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 365–376.

Article  CAS  PubMed  Google Scholar 

Carp, J. (2012). The secret lives of experiments: Methods reporting in the fMRI literature. NeuroImage, 63, 289–300.

Article  PubMed  Google Scholar 

Chen, G., Taylor, P. A., & Cox, R. W. (2017). Is the statistic value all we should care about in neuroimaging? NeuroImage, 147, 952–959.

Article  PubMed  Google Scholar 

Cooper, H., & Hedges, L. V. (2009). The Handbook of Research Synthesis. Russell Sage Foundation.

Costafreda, S. G. (2012). Parametric coordinate-based meta-analysis: Valid effect size meta-analysis of studies with differing statistical thresholds. Journal of Neuroscience Methods, 210, 291–300.

Article  PubMed  Google Scholar 

Cox, R. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29, 162–173.

Article  CAS  PubMed  Google Scholar 

Cox, R. W., & Hyde, J. S. (1997). Software tools for analysis and visualization of FMRI Data. NMR in Biomedicine, 10, 171–178.

Article  CAS  PubMed  Google Scholar 

Durnez, J., Moerkerke, B., & Nichols, T. E. (2014). Post-hoc power estimation for topological inference in fMRI. NeuroImage, 84, 45–64.

Article  PubMed  Google Scholar 

Eickhoff, S. B., Nichols, T. E., Laird, A. R., Hoffstaedter, F., Amunts, K., Fox, P. T., & Eickhoff, C. R. (2016). Behavior, Sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation. Neuroimage, 137, 70–85.

Article  PubMed  Google Scholar 

Eickhoff, S. B., Bzdok, D., Laird, A. R., Kurth, F., & Fox, P. T. (2012). Activation likelihood estimation revisited. NeuroImage, 59, 2349–2361.

Article  PubMed  Google Scholar 

Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping, 30, 2907–2926.

Article  PubMed  PubMed Central  Google Scholar 

Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd (Edinburgh).

Fox, P. T., Laird, A. R., Fox, S. P., Fox, P. M., Uecker, A. M., Crank, M., & Lancaster, J. L. (2005). Brainmap taxonomy of experimental design: description and evaluation. Human Brain Mapping, 25, 185–198.

Article  PubMed  PubMed Central  Google Scholar 

Fox, P. T., & Lancaster, J. L. (2002). Mapping context and content: The BrainMap model. Nature Reviews Neuroscience, 3, 319–321.

Article  CAS  PubMed  Google Scholar 

Friston, K. J., Stephan, K. E., Lund, T. E., Morcom, A., & Kiebel, S. (2005). Mixed-effects and fMRI studies. NeuroImage, 24, 244–252.

Article  CAS  PubMed  Google Scholar 

Gorgolewski, K., Esteban, O., Schaefer, G., Wandell, B., & Poldrack, R. (2017). OpenNeuro—a free online platform for sharing and analysis of neuroimaging data (p. 1677). Vancouver, Canada: Organization for Human Brain Mapping.

Google Scholar 

Gorgolewski, K. J., Alfaro-Almagro, F., Auer, T., Bellec, P., Capotă, M., Chakravarty, M. M., & Poldrack, R. A. (2017). BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods. PLOS Computational Biology, 13, 1–16.

Article  Google Scholar 

Jennings, R. G., & Van Horn, J. D. (2012). Publication bias in neuroimaging research: implications for meta-analyses. Neuroinformatics, 10, 67–80.

Article  PubMed  PubMed Central  Google Scholar 

Kober, H., Barrette, L. F., Joseph, J., Bliss-Moreau, E., Lindquis, K., & Wager, T. D. (2008). Functional grouping and cortical-subcortical interactions in emotion: A meta-analysis of neuroimaging studies. NeuroImage, 42, 998–1031.

Article  PubMed  Google Scholar 

Laird, A. R., Lancaster, J. J., & Fox, P. T. (2005). BrainMap: The social evolution of a functional neuroimaging database. Neuroinformatics, 3, 65–78.

Article  PubMed  Google Scholar 

Lindquist, M. A. (2008). The statistical analysis of fMRI data. Statistical Science, 23, 439–464.

Article  Google Scholar 

Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI. Nature, 453, 869–878.

Article  CAS  PubMed  Google Scholar 

Maumet, C., Auer, T., Bowring, A., Chen, G., Das, S., Flandin, G., & Nichols, T. G. (2016). Sharing brain mapping statistical results with the neuroimaging data model. Scientific Data, 3, 1–15.

Article  Google Scholar 

Maumet C, & Nichols TE (2016). Minimal data needed for valid & accurate image-based fMRI meta-analysis. bioRxiv. https://doi.org/10.1101/048249

Mehta, R. K., & Parasuraman, R. (2013). Neuroergonomics: a review of applications to physical and cognitive work. Frontiers in human neuroscience, 7, 889. https://doi.org/10.3389/fnhum.2013.00889

Article  PubMed  PubMed Central  Google Scholar 

Mosteller, F., & Bush, R. R. (1954). Selected quantitative techniques. In G. Lindzey (Ed.), Handbook of social psychology (Vol. 1).

Müller, V. I., Cieslik, E. C., Laird, A. R., Fox, P. T., Radua, J., Mataix-Cols, D., & Eickhoff, S. B. (2018). Ten simple rules for neuroimaging meta-analysis. Neuroscience Biobehavioral Reviews, 84, 151–161. https://doi.org/10.1016/j.neubiorev.2017.11.012

Article  PubMed  Google Scholar 

Mumford, J. A., & Nichols, T. E. (2008). Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation. NeuroImage, 39, 261–268.

Article  PubMed  Google Scholar 

Nichols, T. (2012). SPM PLOT UNITS. Retrieved from SPM PLOT UNITS: https://blog.nisox.org/2012/07/31/spm-plot-units/

Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Yeo, B. T. (2016). Best Practices in Data Analysis and Sharing in Neuroimaging using MRI. bioRxiv. https://doi.org/10.1101/054262

Penny, W. D., Friston, K. J., Ashburner, J. T., Kiebel, S. J., & Nichols, T. E. (2011). Statistical parametric mapping: the analysis of functional brain images. Elsevier.

Google Scholar 

Pernet, C. (2014). Misconceptions in the use of the General Linear Model applied to functional MRI: A tutorial for junior neuro-imagers. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2014.00001

Article  PubMed  PubMed Central  Google Scholar 

Poldrack, R. A., Fletcher, P. C., Henson, R. N., Worsley, K. J., Brett. M., & Nichols, T. E. (2008). Guidelines for reporting an fMRI study. Neuroimage, 409–414.

Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafò, M. R., & Yarkoni, T. (2017). Scanning the horizon: towards transparent and reproducible neuroimaging research. Nature Reviews Neuroscience, 18, 115–126.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Radua, J., & Mataix-Cols, D. (2009). Voxel-wise meta-analysis of grey matter changes in obsessive−compulsive disorder. The British Journal of Psychiatry, 195, 393–402.

Article  PubMed  Google Scholar 

Radua, J., & Mataix-Cols, D. (2012). Meta-analytic methods for neuroimaging data explained. Biology of Mood & Anxiety Disorders, 2, 1–11.

Article  Google Scholar 

Radua, J., van den Heuvel, O. A., Surguladze, S., & Mataix-Cols, D. (2010). Meta-analytical comparison of voxel-based morphometry studies in obsessive compulsive disorder vs other anxiety disorders. Archives of General Psychiatry, 67, 701–711.

Article  PubMed  Google Scholar 

Radua, J., Mataix-Cols, D., Phillips, M. L., El-hage, W., Kronhaus, D. M., Cardoner, N., & Surguladze, S. (2012). A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. European Psychiatry, 27, 605–611.

Article  CAS  PubMed  Google Scholar 

Radua, J., Rubia, K., Canales-Rodríguez, E. J., Pomarol-Clotet, E., Fusar-Poli, P., & Mataix-Cols, D. (2014). Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies. Frontiers in Psychiatry, 5, 1–8.

Article  Google Scholar 

Salimi-Khorshidi, G., Smith, S. M., Keltner, J. R., Wager, T. D., & Nichols, T. E. (2009). Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. NeuroImage, 45, 810–823.

Article  PubMed  Google Scholar 

Salo, T., Yarkoni, T., Nichols, T. E., Poline, J-B., Bilgel, M., Bottenhorn, K. L., Jarecka, D., Kent, J. D., Kimbler, A., Nielson, D. M., Oudyk, K. M., Peraza, J. A., Pérez, A., Reeders, P. C., Yanes, J. A., & Laird, A. R. (2022). NiMARE: Neuroimaging meta-analysis research. NeuroLibre. https://doi.org/10.55458/neurolibre.00007

Stouffer, S. A., Suchman, E. A., Devinney, L. C., Star, S. A., & Williams, R. M., Jr. (1949). The American soldier, Vol. 1: Adjustment during army life. Princeton: Princeton University Press.

Sutton, A. J., Jones, K. R., Abrams, D. R., Sheldon, T. A., & Song, F. (2000). Methods for meta-analysis in medical research. John Wiley.

Google Scholar 

Szucs, D. A. (2020). Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990–2012) and of latest practices (2017–2018) in high-impact journals. NeuroImage. https://doi.org/10.1016/j.neuroimage.2020.117164

Article  PubMed  Google Scholar 

Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002). Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. NeuroImage, 16, 765–780.

Article  PubMed  Google Scholar