Add badges and citations for Aperture Neuro article (#834)

* Add badge for Aperture Neuro paper. * Update citations in code.
neurostuff · Sep 14, 2023 · 210d551 · 210d551
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diff --git a/README.md b/README.md
@@ -12,7 +12,8 @@ A Python library for coordinate- and image-based meta-analysis.
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 [![Join the chat at https://mattermost.brainhack.org/brainhack/channels/nimare](https://img.shields.io/badge/mattermost-join_chat%20%E2%86%92-brightgreen.svg)](https://mattermost.brainhack.org/brainhack/channels/nimare)
 [![RRID:SCR_017398](https://img.shields.io/badge/RRID-SCR__017398-blue.svg)](https://scicrunch.org/scicrunch/Resources/record/nlx_144509-1/SCR_017398/resolver?q=nimare&l=nimare)
-[![DOI](https://neurolibre.org/papers/10.55458/neurolibre.00007/status.svg)](https://doi.org/10.55458/neurolibre.00007)
+[![Paper](https://img.shields.io/badge/Aperture-10.52294/001c.87681-darkblue.svg)](https://doi.org/10.52294/001c.87681)
+[![Preprint](https://neurolibre.org/papers/10.55458/neurolibre.00007/status.svg)](https://doi.org/10.55458/neurolibre.00007)
 
 Currently, NiMARE implements a range of image- and coordinate-based meta-analytic algorithms, as well as several methods for advanced meta-analytic methods, like automated annotation and functional decoding.
 
@@ -34,22 +35,20 @@ pip install git+https://github.com/neurostuff/NiMARE.git
 ## Citing NiMARE
 
 If you use NiMARE in your research, we recommend citing the Zenodo DOI associated with the NiMARE version you used,
-as well as the NeuroLibre preprint for the NiMARE Jupyter book.
+as well as the Aperture Neuro journal article for the NiMARE Jupyter book.
 You can find the Zenodo DOI associated with each NiMARE release at https://zenodo.org/record/6642243#.YqiXNy-B1KM.
 
 ```BibTeX
-# This is the NeuroLibre preprint.
-@article{Salo2022,
-  doi = {10.55458/neurolibre.00007},
-  url = {https://doi.org/10.55458/neurolibre.00007},
-  year = {2022},
-  publisher = {The Open Journal},
-  volume = {1},
-  number = {1},
-  pages = {7},
+# This is the Aperture Neuro paper.
+@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 = {NeuroLibre}
+  journal = {Aperture Neuro}
 }
 
 # This is the Zenodo citation for version 0.0.11.

diff --git a/docs/index.rst b/docs/index.rst
@@ -52,6 +52,10 @@ To install NiMARE check out our `installation guide`_.
    :target: https://scicrunch.org/scicrunch/Resources/record/nlx_144509-1/SCR_017398/resolver?q=nimare&l=nimare
    :alt: RRID:SCR_017398
 
+.. image:: https://img.shields.io/badge/Aperture-10.52294/001c.87681-darkblue.svg
+   :target: https://doi.org/10.52294/001c.87681
+   :alt: Aperture paper
+
 .. image:: https://neurolibre.org/papers/10.55458/neurolibre.00007/status.svg
    :target: https://doi.org/10.55458/neurolibre.00007
    :alt: NeuroLibre preprint
@@ -65,24 +69,22 @@ Citing NiMARE
 -------------
 
 If you use NiMARE in your research, we recommend citing the Zenodo DOI associated with the NiMARE version you used,
-as well as the NeuroLibre preprint for the NiMARE Jupyter book.
+as well as the Aperture Neuro journal article for the NiMARE Jupyter book.
 You can find the Zenodo DOI associated with each NiMARE release at https://zenodo.org/record/6642243#.YqiXNy-B1KM.
 
 .. code-block:: bibtex
    :caption: BibTeX entries for NiMARE version 0.0.11.
 
-   # This is the NeuroLibre preprint.
-   @article{Salo2022,
-   doi = {10.55458/neurolibre.00007},
-   url = {https://doi.org/10.55458/neurolibre.00007},
-   year = {2022},
-   publisher = {The Open Journal},
-   volume = {1},
-   number = {1},
-   pages = {7},
-   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 = {NeuroLibre}
+   # This is the Aperture Neuro paper.
+   @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}
    }
 
    # This is the Zenodo citation for version 0.0.11.

diff --git a/nimare/meta/cbma/ale.py b/nimare/meta/cbma/ale.py
@@ -177,7 +177,7 @@ def _generate_description(self):
             "An activation likelihood estimation (ALE) meta-analysis "
             "\\citep{turkeltaub2002meta,turkeltaub2012minimizing,eickhoff2012activation} was "
             f"performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), using a(n) "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), using a(n) "
             f"{self.kernel_transformer.__class__.__name__.replace('Kernel', '')} kernel. "
             f"{self.kernel_transformer._generate_description()} "
             f"ALE values were converted to p-values using {null_method_str}. "
@@ -415,11 +415,11 @@ def _generate_description(self):
             "An activation likelihood estimation (ALE) subtraction analysis "
             "\\citep{laird2005ale,eickhoff2012activation} was performed with NiMARE "
             f"v{__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), "
             f"using a(n) {self.kernel_transformer.__class__.__name__.replace('Kernel', '')} "
             "kernel. "
             f"{self.kernel_transformer._generate_description()} "
-            "The subtraction analysis was implemented according to NiMARE's \\citep{Salo2022} "
+            "The subtraction analysis was implemented according to NiMARE's \\citep{Salo2023} "
             "approach, which differs from the original version. "
             "In this version, ALE-difference scores are calculated between the two datasets, "
             "for all voxels in the mask, rather than for voxels significant in the main effects "
@@ -695,7 +695,7 @@ def _generate_description(self):
             "A specific coactivation likelihood estimation (SCALE) meta-analysis "
             "\\citep{langner2014meta} was performed with NiMARE "
             f"{__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), with "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), with "
             f"{self.n_iters} iterations. "
             f"The input dataset included {self.inputs_['coordinates'].shape[0]} foci from "
             f"{len(self.inputs_['id'])} experiments{sample_size_str}."

diff --git a/nimare/meta/cbma/mkda.py b/nimare/meta/cbma/mkda.py
@@ -164,7 +164,7 @@ def _generate_description(self):
             "A multilevel kernel density (MKDA) meta-analysis \\citep{wager2007meta} was "
             "performed was performed with NiMARE "
             f"{__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), using a(n) "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), using a(n) "
             f"{self.kernel_transformer.__class__.__name__.replace('Kernel', '')} kernel. "
             f"{self.kernel_transformer._generate_description()} "
             f"Summary statistics (OF values) were converted to p-values using {null_method_str}. "
@@ -372,7 +372,7 @@ def _generate_description(self):
             "A multilevel kernel density chi-squared analysis \\citep{wager2007meta} was "
             "performed according to the same procedure as implemented in Neurosynth with NiMARE "
             f"{__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), "
             f"using a(n) {self.kernel_transformer.__class__.__name__.replace('Kernel', '')} "
             "kernel. "
             f"{self.kernel_transformer._generate_description()} "
@@ -1157,7 +1157,7 @@ def _generate_description(self):
             "A kernel density (KDA) meta-analysis \\citep{wager2007meta} was "
             "performed was performed with NiMARE "
             f"{__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), "
             f"using a(n) {self.kernel_transformer.__class__.__name__.replace('Kernel', '')} "
             "kernel. "
             f"{self.kernel_transformer._generate_description()} "

diff --git a/nimare/meta/ibma.py b/nimare/meta/ibma.py
@@ -167,7 +167,7 @@ class Fishers(IBMAEstimator):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}) on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}) on "
             f"{len(self.inputs_['id'])} z-statistic images using the Fisher "
             "combined probability method \\citep{fisher1946statistical}."
         )
@@ -252,7 +252,7 @@ def __init__(self, use_sample_size=False, **kwargs):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}) on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}) on "
             f"{len(self.inputs_['id'])} z-statistic images using the Stouffer "
             "method \\citep{stouffer1949american}"
         )
@@ -367,7 +367,7 @@ def __init__(self, tau2=0, **kwargs):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta images using the Weighted Least Squares approach "
             "\\citep{brockwell2001comparison}, "
             f"with an a priori tau-squared value of {self.tau2} defined across all voxels."
@@ -460,7 +460,7 @@ class DerSimonianLaird(IBMAEstimator):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta and variance images using the "
             "DerSimonian-Laird method \\citep{dersimonian1986meta}, in which tau-squared is "
             "estimated on a voxel-wise basis using the method-of-moments approach "
@@ -552,7 +552,7 @@ class Hedges(IBMAEstimator):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta and variance images using the Hedges "
             "method \\citep{hedges2014statistical}, in which tau-squared is estimated on a "
             "voxel-wise basis."
@@ -660,7 +660,7 @@ def __init__(self, method="ml", **kwargs):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta images using sample size-based "
             "maximum likelihood estimation, in which tau-squared and sigma-squared are estimated "
             "on a voxel-wise basis."
@@ -772,7 +772,7 @@ def __init__(self, method="ml", **kwargs):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta and variance images using "
             "variance-based maximum likelihood estimation, in which tau-squared is estimated on a "
             "voxel-wise basis."
@@ -869,7 +869,7 @@ def __init__(self, two_sided=True, **kwargs):
     def _generate_description(self):
         description = (
             f"An image-based meta-analysis was performed with NiMARE {__version__} "
-            "(RRID:SCR_017398; \\citealt{Salo2022}), on "
+            "(RRID:SCR_017398; \\citealt{Salo2023}), on "
             f"{len(self.inputs_['id'])} beta images using Nilearn's "
             "\\citep{10.3389/fninf.2014.00014} permuted ordinary least squares method."
         )

diff --git a/nimare/resources/references.bib b/nimare/resources/references.bib
@@ -342,6 +342,17 @@ @article{Salo2022
   journal = {NeuroLibre}
 }
 
+@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{shaffer1995multiple,
   title={Multiple hypothesis testing},
   author={Shaffer, Juliet Popper},