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0.0.3

Contents:

  • About NiMARE
  • Installation
  • Command Line Interface
  • Examples
    • Working with datasets
      • Download and convert the Neurosynth database
      • Load and work with a Dataset
    • Performing meta-analyses
      • Generate modeled activation maps with peaks2maps
      • Run a meta-analytic coactivation modeling analysis
      • Generate modeled activation maps
      • Run image-based meta-analyses on 21 pain studies
      • Run coordinate-based meta-analyses on 21 pain studies
    • Automated annotation
      • Train an LDA model and use it
      • Train a GCLDA model and use it
      • Work with the Cognitive Atlas
    • Functional characterization analysis
      • Decode regions of interest and subsets of Datasets
  • Contributing to NiMARE
  • NiMARE Developer Guide
  • Our Roadmap
  • API
NiMARE
  • Docs »
  • NiMARE: Neuroimaging Meta-Analysis Research Environment
  • Edit on GitHub

Examples¶

Working with datasets¶

Download and convert the Neurosynth database

Download and convert the Neurosynth database¶

Load and work with a Dataset

Load and work with a Dataset¶

Performing meta-analyses¶

Generate modeled activation maps with peaks2maps

Generate modeled activation maps with peaks2maps¶

Run a meta-analytic coactivation modeling analysis

Run a meta-analytic coactivation modeling analysis¶

Generate modeled activation maps

Generate modeled activation maps¶

Run image-based meta-analyses on 21 pain studies

Run image-based meta-analyses on 21 pain studies¶

Run coordinate-based meta-analyses on 21 pain studies

Run coordinate-based meta-analyses on 21 pain studies¶

Automated annotation¶

Train an LDA model and use it

Train an LDA model and use it¶

Train a GCLDA model and use it

Train a GCLDA model and use it¶

Work with the Cognitive Atlas

Work with the Cognitive Atlas¶

Functional characterization analysis¶

Decode regions of interest and subsets of Datasets

Decode regions of interest and subsets of Datasets¶

Download all examples in Python source code: auto_examples_python.zip

Download all examples in Jupyter notebooks: auto_examples_jupyter.zip

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