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Contents:

  • About NiMARE
  • Installation
  • Getting help and contacting us
  • API
  • Examples
  • Contributing to NiMARE
  • NiMARE Developer Guide
  • Command Line Interface
  • Outputs of NiMARE
  • NiMARE Methods
    • Coordinate-based meta-analysis in NiMARE
    • Meta-analytic functional decoding
    • Machine learning with Studysets
    • Fetching resources from the internet
  • What’s New
  • Glossary
NiMARE
  • NiMARE: Neuroimaging Meta-Analysis Research Environment
  • View page source

NiMARE Methods

Methods Pages:

  • Coordinate-based meta-analysis in NiMARE
    • Kernels
    • Estimators
    • Multiple comparisons correction
    • Reproducible results
    • References
  • Meta-analytic functional decoding
    • Continuous decoding
    • Discrete decoding
    • Encoding
  • Machine learning with Studysets
    • What is a bunch?
    • Turning peaks into Modeled Activation maps
    • Choosing what to model
    • Handling missing data
    • Finding the fields worth using
    • Splitting without leaking a study
    • Reducing the voxel features
    • Letting nilearn transform the voxels
    • Reading a model back to the brain
    • Working at release scale
    • References
  • Fetching resources from the internet
    • Where should coordinate data come from?
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✉ Contact us

Need help with NiMARE?

  • Ask on NeuroStars Public Q&A with the nimare tag. Best for usage questions.
  • Email neurosynthorg@gmail.com Best for consulting, collaboration, or private inquiries.
  • Report a bug on GitHub Bug reports and feature requests.
  • Chat on Mattermost Informal chat with users and developers.
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