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Neurosynth Compose: New frontiers in neuroimaging Meta-Analyses

Presented During:

Neuroinformatics and Data Sharing

Friday, June 27, 2025: 11:30 AM - 12:45 PM

Brisbane Convention & Exhibition Centre

Room: M3 (Mezzanine Level)

Poster No:

1827

Submission Type:

Abstract Submission

Authors:

James Kent¹, Nicholas Lee², Julio Peraza³, Taylor Salo⁴, Katherine Bottenhorn⁵, Jérôme Dockès⁶, Ross Blair⁷, Kendra Oudyk², Yifan Yu⁸, Thomas Nichols⁹, Angela Laird³, Jean-Baptiste Poline¹⁰, Alejandro de la Vega¹¹

Institutions:

¹UT Austin, Austin, TX, ²Mcgill University, Montreal, Quebec, ³Florida International University, Miami, FL, ⁴University of Pennsylvania, Philadelphia, PA, ⁵Keck School of Medicine of USC, Los Angeles, CA, ⁶INRIA Saclay, Paris, Ile-de-France, ⁷Stanford University, Stanford, CA, ⁸Big data institute, University of Oxford, Oxford, Oxfordshire, ⁹University of Oxford, Oxford, Oxfordshire, ¹⁰McGill University, Montreal, Quebec, ¹¹University of Texas at Austin, Austin, TX

First Author:

James Kent
UT Austin
Austin, TX

Co-Author(s):

Nicholas Lee
Mcgill University
Montreal, Quebec

Julio Peraza
Florida International University
Miami, FL

Taylor Salo, PhD
University of Pennsylvania
Philadelphia, PA

Katherine Bottenhorn, PhD
Keck School of Medicine of USC
Los Angeles, CA

Jérôme Dockès
INRIA Saclay
Paris, Ile-de-France

Ross Blair
Stanford University
Stanford, CA

Kendra Oudyk
Mcgill University
Montreal, Quebec

Yifan Yu
Big data institute, University of Oxford
Oxford, Oxfordshire

Thomas Nichols, PhD
University of Oxford
Oxford, Oxfordshire

Angela Laird
Florida International University
Miami, FL

Jean-Baptiste Poline
McGill University
Montreal, Quebec

Alejandro de la Vega
University of Texas at Austin
Austin, TX

Introduction:

Meta-analyses play an instrumental role in the field of neuroimaging to summarize and generate consensus (or lack thereof!) across studies. The outcomes of these meta-analyses can inform clinicians about a subfield of neuroscience and help researchers generate novel hypotheses. Following the standards of Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), meta-analyses are both time and resource intensive. However, this does not need to be the case. By leveraging automation and crowdsourcing the work of active users, we've created a platform that makes running a meta-analysis open, reproducible, and efficient. Here, we present Neurosynth Compose, a powerful and intuitive platform for curating and annotating studies as well as specifying and executing meta-analyses openly and reproducibly.

Methods:

Neurosynth Compose is a modular platform connecting an ecosystem of tools to curate, ingest, and annotate data, as well as specify and execute meta-analyses. The original NeuroSynth and NeuroQuery databases are pre-ingested into NeuroStore, the main data source for Neurosynth Compose. Neurostore is an independent backend that users can query directly or build additional tools around. Neurosynth Compose functions primarily as a powerful and intuitive frontend for the curation of studies stored on NeuroStore. Once the studies are curated, Neurosynth Compose creates a reproducible bundle, containing the data and the analysis specification in order to run the meta-analysis. Neuroimaging Meta-Analysis Research Environment (NiMARE) is used to execute the meta-analysis. NiMARE is a well documented and comprehensive python package to run a variety of meta-analyses and related functions. The execution of the meta-analysis can then either be run through google colab or any cloud/personal hardware that can run NiMARE. To demonstrate the workflow, we replicated the Witt (2008) coordinate-based meta-analysis investigating finger tapping using Neurosynth Compose.

Results:

There are over 1000 unique users on Neurosynth Compose, who have contributed 5,749 new studies to the platform, as well as edited 5,403 existing studies on the platform. These studies were used in 849 meta-analyses to date. With the replication, the published images from the original paper are qualitatively similar to the replication run using Neurosynth Compose and NiMARE (Figure 2). Execution of the meta-analysis can be found on a google colab notebook (https://bit.ly/ns-notebook).

Conclusions:

The replication illustrates the openness and reproducibility of the entire workflow from data curation to execution of the meta-analysis. Because the workflow is open, reproducible, and clonable, the original research group can test different parameters to determine the robustness of their result or another research group can critically examine the analysis choices made in the original meta-analysis. Another benefit is the ease of updating the meta-analysis over time. Benchmark meta-analyses can evolve over time as new relevant research is ingested and annotated. Finally, this is only one example workflow, NeuroSynth Compose supports coordinates and images for both conventional and semi-automated meta-analyses, covering an unprecedented range of use cases for meta-analyses. Neurosynth Compose provides a platform for the open curating, executing, sharing, and updating meta-analyses with an intuitive user interface.

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI)

Methods Development

Neuroinformatics and Data Sharing:

Databasing and Data Sharing ¹

Workflows ²

Informatics Other

Keywords:

Data Organization

Open Data

Open-Source Code

Open-Source Software

Workflows

^1|2Indicates the priority used for review

Abstract Information

By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.

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Please indicate below if your study was a "resting state" or "task-activation” study.

Other

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was this research conducted in the United States?

Yes

Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.

Not applicable

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Not applicable

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

PET

Functional MRI

Which processing packages did you use for your study?

Other, Please list - NiMARE

Provide references using APA citation style.

Witt, S. T., Laird, A. R., & Meyerand, M. E. (2008). Functional neuroimaging correlates of finger-tapping task variations: an ALE meta-analysis. NeuroImage, 42(1), 343–356. https://doi.org/10.1016/j.neuroimage.2008.04.025

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