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LAION-fMRI | Documentation
LAION-fMRI | Documentation

Getting Started

  • Home
  • Quickstart
  • Dataset at a Glance
  • Data Access

Python Package

  • laion_fmri
    • Initialize the data directory
    • License acceptance
    • Discover what’s in the bucket
    • Download
    • Load
    • API Reference
      • laion_fmri.brain
      • laion_fmri.config
      • laion_fmri.discovery
      • laion_fmri.download
      • laion_fmri.group
      • laion_fmri.io
      • laion_fmri.subject
      • laion_fmri.torch_data
  • Examples gallery
    • Quick Start
    • Dataset Initialization
    • Querying the Dataset
    • Loading Data

Core Data

  • Anatomical Data
  • fMRI Data
  • ROIs
  • Functional Localizers
  • GLMsingle Beta Estimates

Stimuli & Splits

  • Stimulus Data
  • Train / Test Splits

Methods

  • Experimental Design
  • MRI Acquisition
  • Preprocessing
  • Quality Control
  • Stimulus Selection
  • Metadata Acquisition

Reference

  • FAQ
  • Example Methods Text
  • Contributing
  • Release History
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Examples gallery¶

Hands-on walkthroughs of the laion_fmri Python package. Each example is a runnable script that you can copy-paste or download as a Jupyter notebook from the link at the bottom of its page.

Recommended reading order:

  1. Quick Start – end-to-end: initialize, query, download one session, load it.

  2. Dataset Initialization – focused walk-through of the one-time setup: data directory and license acceptance.

  3. Querying the Dataset – discover what is in the bucket and inspect per-subject data.

  4. Loading Data – the full load API: betas, noise-ceiling maps, ROI masks, brain-space mapping, group loading, and PyTorch.

For a complete reference of the package’s public API, see laion_fmri.

Quick Start

Quick Start

Dataset Initialization

Dataset Initialization

Querying the Dataset

Querying the Dataset

Loading Data

Loading Data

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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