Potential reporting bias in fMRI studies of the brain.
BACKGROUND
Functional magnetic resonance imaging (fMRI) studies have reported multiple activation foci associated with a variety of conditions, stimuli or tasks. However, most of these studies used fewer than 40 participants.


METHODS
After extracting data (number of subjects, condition studied, number of foci identified and threshold) from 94 brain fMRI meta-analyses (k = 1,788 unique datasets) published through December of 2011, we analyzed the correlation between individual study sample sizes and number of significant foci reported. We also performed an analysis where we evaluated each meta-analysis to test whether there was a correlation between the sample size of the meta-analysis and the number of foci that it had identified. Correlation coefficients were then combined across all meta-analyses to obtain a summary correlation coefficient with a fixed effects model and we combine correlation coefficients, using a Fisher's z transformation.


RESULTS
There was no correlation between sample size and the number of foci reported in single studies (r = 0.0050) but there was a strong correlation between sample size and number of foci in meta-analyses (r = 0.62, p<0.001). Only studies with sample sizes <45 identified larger (>40) numbers of foci and claimed as many discovered foci as studies with sample sizes ≥ 45, whereas meta-analyses yielded a limited number of foci relative to the yield that would be anticipated from smaller single studies.


CONCLUSIONS
These results are consistent with possible reporting biases affecting small fMRI studies and suggest the need to promote standardized large-scale evidence in this field. It may also be that small studies may be analyzed and reported in ways that may generate a larger number of claimed foci or that small fMRI studies with inconclusive, null, or not very promising results may not be published at all.
Division of General Medical Disciplines, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America. spdavid@stanford.edu
Sean P
SP
David
Jennifer J
JJ
Ware
Isabella M
IM
Chu
Pooja D
PD
Loftus
Paolo
P
Fusar-Poli
Joaquim
J
Radua
Marcus R
MR
Munafò
John P A
JP
Ioannidis
D001921:Brain / Q000502:physiology / Q000503:physiopathology; D016206:Databases, Bibliographic; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000592:standards / Q000706:statistics & numerical data*; D017594:Publication Bias; D012107:Research Design; D018401:Sample Size; D013223:Statistics as Topic