The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses
| Autor: | Herve Lemaitre, Simone Kühn, Tobias Banaschewski, Arun L.W. Bokde, Ruth Seurinck, Gareth J. Barker, Sabina Millenet, Han Bossier, Beatrijs Moerkerke, Jean-Luc Martinot, Tomáš Paus |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
coordinate-based meta-analysis
POWER Inference 050105 experimental psychology random effects models lcsh:RC321-571 ACTIVATION LIKELIHOOD models 03 medical and health sciences 0302 clinical medicine REPRODUCIBILITY Resampling Statistics Medicine and Health Sciences mixed effects Journal Article FAILURE 0501 psychology and cognitive sciences mixed effects models lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Reliability (statistics) group modeling Original Research BRAIN-FUNCTION Mathematics reliability General Neuroscience 05 social sciences Aggregate (data warehouse) fMRI NEUROIMAGING DATA Random effects model Maxima and minima NEUROSCIENCE Group analysis Ordinary least squares BEHAVIOR 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | Frontiers in Neuroscience, Vol 11 (2018) Bossier, H, Seurinck, R, Kühn, S, Banaschewski, T, Barker, G J, Bokde, A L W, Martinot, J-L, Lemaitre, H, Paus, T, Millenet, S & Moerkerke, B 2018, ' The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses ', Frontiers in Neuroscience, vol. 11, pp. 745 . https://doi.org/10.3389/fnins.2017.00745 FRONTIERS IN NEUROSCIENCE Frontiers in Neuroscience |
| ISSN: | 1662-453X |
| DOI: | 10.3389/fnins.2017.00745/full |
| Popis: | Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1) the balance between false and true positives and (2) the activation reliability of the outcome from a coordinate-based meta-analysis. More particularly, we consider the influence of the chosen group level model at the study level [fixed effects, ordinary least squares (OLS), or mixed effects models], the type of coordinate-based meta-analysis [Activation Likelihood Estimation (ALE) that only uses peak locations, fixed effects, and random effects meta-analysis that take into account both peak location and height] and the amount of studies included in the analysis (from 10 to 35). To do this, we apply a resampling scheme on a large dataset (N = 1,400) to create a test condition and compare this with an independent evaluation condition. The test condition corresponds to subsampling participants into studies and combine these using meta-analyses. The evaluation condition corresponds to a high-powered group analysis. We observe the best performance when using mixed effects models in individual studies combined with a random effects meta-analysis. Moreover the performance increases with the number of studies included in the meta-analysis. When peak height is not taken into consideration, we show that the popular ALE procedure is a good alternative in terms of the balance between type I and II errors. However, it requires more studies compared to other procedures in terms of activation reliability. Finally, we discuss the differences, interpretations, and limitations of our results. |
| Databáze: | OpenAIRE |
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