Neuroimaging Meta-Analyses #42
Description
Authors
James Kent [email protected]
Yifan Yu [email protected]
Max Korbmacher [email protected]
Bernd Taschler [email protected]
Lea Waller [email protected]
Kendra Oudyk [email protected]
Summary
Introduction
Neuroimaging Meta-Analyses serve an important role in cognitive neuroscience (and beyond) to create consensus and generate new hypotheses. However, tools for neuroimaging meta-analyses only implement a small selection of analytical options, pigeon-holing researchers to particular analytical choices. Additionally, many niche tools are created and abandoned as the graduate student who was working on the project graduated and moved on. Neurosynth-Compose/NiMARE are part of a python ecosystem that provides a wide range of analytical options (with reasonable defaults), so that researchers can make analytical choices based on their research questions, not the tool.
To help improve and expand this ecosystem, we worked on several projects:
- Make Coordinate Based Meta-Regression more efficient/friendly
- Goal: Increase adoption of a more flexible and sensitive model approach of coordinate-based meta-analysis
- Improve the tutorial outlining how to use Neurosynth-Compose
- Goal: Tutorial to increase usage of the website Neurosynth-Compose
- Change the masking process for Image Based Meta-Analysis
- Goal: Use more voxels/data during Image Based Meta-Analysis
- Run topic modeling of abstracts of papers associated with NeuroVault collections
- Identify groupings of images that are amenable for meta-analysis
Results
Progress was made on all projects.
- Several bugs and areas of inefficient code were found for Coordinate Based Meta Regression, as well as notebooks demonstrating usage and issues.
- Feedback was given to the tutorial to improve clarity and conciseness
- An outline of a solution for including more voxels was drafted with a plan for implementation
- topic modeling identified how images on neurovault were distributed
The improvements made to NiMARE and related tools provide more accessibility to neuroimaging meta-analyses making it easier to perform crucial analyses in our field.
References (Bibtex)
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