The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses
Open accessAbstract
Activation Likelihood Estimation (ALE) is an objective, quantitative technique for coordinate‐based meta‐analysis (CBMA) of neuroimaging results that has been validated for a variety of uses. Stepwise modifications have improved ALE's theoretical and statistical rigor since its introduction. Here, we evaluate two avenues to further optimize ALE. First, we demonstrate that the maximum contribution of an experiment makes to an ALE map is related to the number of foci it reports and their proximity. We present a modified ALE algorithm that eliminates these within‐experiment effects. However, we show that these effects only account for 2–3% of cumulative ALE values, and removing them has little impact on thresholded ALE maps. Next, we present an alternate organizational approach to datasets that prevents subject groups with multiple experiments in a dataset from influencing ALE values more than others. This modification decreases cumulative ALE values by 7–9%, changes the relative magnitude of some clusters, and reduces cluster extents. Overall, differences between results of the standard approach and these new methods were small. This finding validates previous ALE reports against concerns that they were driven by within‐experiment or within‐group effects. We suggest that the modified ALE algorithm is theoretically advantageous compared with the current algorithm, and that the alternate organization of datasets is the most conservative approach for typical ALE analyses and other CBMA methods. Combining the two modifications minimizes both within‐experiment and within‐group effects, optimizing the degree to which ALE values represent concordance of findings across independent reports. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc.
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Cites
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150
Self-citationBinder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp055 · Cited by 4,060
Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009) · Human Brain Mapping · doi:10.1002/hbm.20718 · Cited by 1,924
Self-citationMeta-analysis of the functional neuroanatomy of single-word reading: method and validation
Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002) · NeuroImage · doi:10.1006/nimg.2002.1131 · Cited by 1,604
Self-citationALE meta-analysis of action observation and imitation in the human brain
Caspers, S., Zilles, K., Laird, A. R., & Eickhoff, S. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.112 · Cited by 1,386
Self-citationMeta-analysis of 41 functional neuroimaging studies of executive function in schizophrenia
Minzenberg, M. J., Laird, A. R., Thelen, S., Carter, C. S., & Glahn, D. C. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.91 · Cited by 1,158
Self-citationALE meta-analysis: controlling the false discovery rate and performing statistical contrasts
Laird, A. R., Fox, P. M., Price, C. J., Glahn, D. C., Uecker, A. M., Lancaster, J. L., Turkeltaub, P. E., Kochunov, P., & Fox, P. T. (2005) · Human Brain Mapping · doi:10.1002/hbm.20136 · Cited by 868
Self-citationNeuroimaging Support for Discrete Neural Correlates of Basic Emotions: A Voxel-based Meta-analysis
Vytal, K., & Hamann, S. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21366 · Cited by 680
Neuroimaging studies of shifting attention: a meta-analysis
Wager, T. D., Jonides, J., & Reading, S. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.052 · Cited by 654
Glahn, D. C., Laird, A. R., Ellison-Wright, I., Thelen, S. M., Robinson, J. L., Lancaster, J. L., Bullmore, E., & Fox, P. T. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.03.031 · Cited by 628
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Bartra, O., McGuire, J. T., & Kable, J. W. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.063 · Cited by 1,927
Identification of a Common Neurobiological Substrate for Mental Illness
Goodkind, M., Eickhoff, S. B., Oathes, D. J., Jiang, Y., Chang, A., Jones-Hagata, L. B., Ortega, B. N., Zaiko, Y. V., Roach, E. L., Korgaonkar, M. S., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.2206 · Cited by 1,404
Self-citationModelling neural correlates of working memory: A coordinate-based meta-analysis
Rottschy, C., Langner, R., Dogan, I., Reetz, K., Laird, A. R., Schulz, J. B., Fox, P. T., & Eickhoff, S. B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.050 · Cited by 951
Self-citationNeural network of cognitive emotion regulation—an ALE meta-analysis and MACM analysis
Kohn, N., Eickhoff, S. B., Scheller, M., Laird, A. R., Fox, P. T., & Habel, U. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.001 · Cited by 956
Self-citationBeissner, F., Meissner, K., Bar, K.-J., & Napadow, V. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1103-13.2013 · Cited by 920
Metadata
- Authors
- Turkeltaub, P. E., Eickhoff, S. B., Laird, A. R., Fox, M., Wiener, M., & Fox, P.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2011-02-08
- Volume
- 33
- Issue
- 1
- Pages
- 1-13
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2089596781
- Cited by
- 1,119
- References
- 27
- FWCI
- 22.01
- Type
- journal article
- Language
- en
- Open access
- green
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