Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 38.00 4.00 2.00 4.84 6912
1a 38.00 14.00 -6.00 4.14
1b 34.00 20.00 0.00 3.98
1c 38.00 -10.00 -6.00 2.87
2 54.00 -28.00 20.00 4.31 1736
3 -34.00 14.00 0.00 4.14 1280
4 2.00 4.00 52.00 3.72 5760
4a -6.00 8.00 42.00 3.43
4b 2.00 -4.00 64.00 2.99
4c -8.00 14.00 34.00 2.95
5 -32.00 -60.00 -34.00 3.47 2880
5a -26.00 -66.00 -38.00 2.69
5b -28.00 -58.00 -46.00 2.27
6 -62.00 -22.00 20.00 2.97 1832
6a -54.00 -32.00 22.00 2.84
6b -64.00 -22.00 28.00 2.30
7 -36.00 4.00 -16.00 2.81 552
8 20.00 -102.00 -4.00 2.72 496
9 -6.00 -48.00 54.00 2.46 576
10 -4.00 -70.00 50.00 2.23 168
11 -36.00 -22.00 10.00 2.23 208
12 -46.00 -58.00 -54.00 2.21 128
13 36.00 -18.00 12.00 2.21 112
14 -34.00 -90.00 -12.00 2.19 152
15 -54.00 -66.00 2.00 2.14 248
16 -52.00 -8.00 6.00 2.11 88
17 10.00 -68.00 36.00 2.09 176
18 36.00 40.00 30.00 1.97 88

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

Jackknife

The Jackknife analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by looping through experiments, calculating the Estimator's summary statistic for all experiments except the target experiment, dividing the resulting test summary statistics by the summary statistics from the original meta-analysis, and finally averaging the resulting proportion values across all voxels in each cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

An activation likelihood estimation (ALE) meta-analysis
\citep{turkeltaub2002meta,turkeltaub2012minimizing,eickhoff2012activation} was performed with
NiMARE 0.2.2+0.g07ac3b6.dirty (RRID:SCR_017398; \citealt{Salo2023}), using a(n) ALE kernel. An ALE
kernel \citep{eickhoff2012activation} was used to generate study-wise modeled activation maps from
coordinates. In this kernel method, each coordinate is convolved with a Gaussian kernel with full-
width at half max values determined on a study-wise basis based on the study sample sizes according
to the formulae provided in \cite{eickhoff2012activation}. For voxels with overlapping kernels, the
maximum value was retained. ALE values were converted to p-values using an approximate null
distribution \citep{eickhoff2012activation}. The input dataset included 267 foci from 21
experiments, with a total of 334 participants. False discovery rate correction was performed with
the Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{eickhoff2012activation,
  title={Activation likelihood estimation meta-analysis revisited},
  author={Eickhoff, Simon B and Bzdok, Danilo and Laird, Angela R and Kurth, Florian and Fox, Peter T},
  journal={Neuroimage},
  volume={59},
  number={3},
  pages={2349--2361},
  year={2012},
  publisher={Elsevier},
  url={https://doi.org/10.1016/j.neuroimage.2011.09.017},
  doi={10.1016/j.neuroimage.2011.09.017}
}
@article{turkeltaub2002meta,
  title={Meta-analysis of the functional neuroanatomy of single-word reading: method and validation},
  author={Turkeltaub, Peter E and Eden, Guinevere F and Jones, Karen M and Zeffiro, Thomas A},
  journal={Neuroimage},
  volume={16},
  number={3},
  pages={765--780},
  year={2002},
  publisher={Elsevier},
  url={https://doi.org/10.1006/nimg.2002.1131},
  doi={10.1006/nimg.2002.1131}
}
@article{turkeltaub2012minimizing,
  title={Minimizing within-experiment and within-group effects in activation likelihood estimation meta-analyses},
  author={Turkeltaub, Peter E and Eickhoff, Simon B and Laird, Angela R and Fox, Mick and Wiener, Martin and Fox, Peter},
  journal={Human brain mapping},
  volume={33},
  number={1},
  pages={1--13},
  year={2012},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1002/hbm.21186},
  doi={10.1002/hbm.21186}
}