Brainana Lite

Brainana Lite is a notebook-based workflow for volumetric T1w preprocessing on macaque MRI. Run it in Jupyter or Google Colab—no Docker or Nextflow.

When to use Brainana Lite

  • Single subject, T1w only — one macaque, anatomical T1w

  • No BIDS dataset required — you only need nifti file(s) in a folder

  • No local system setup — On Colab, a browser is enough

  • Quick, interactive runs — trying a scan, teaching, or a one-off preprocess

Use the full Brainana Docker pipeline (Installation, Usage notes) for production batch work, multiple modalities, surfaces, and the complete HTML QC suite.

What you get

After Run All, derivatives are written in a BIDS-styled layout. In practice you receive:

  • Preprocessed T1w in individual (T1w) space and in your chosen template space (skull-stripped brain volumes included)

  • Brain mask and atlas-based tissue segmentation in individual space (e.g. ARM2), with a color lookup table

  • Standard macaque atlases backprojected into individual spaces (T1w and scanner)

  • QC snapshot figures (conformation, skull stripping, bias correction, segmentation, registration, and related checks)

Exact filenames and the output tree are printed in the notebook when preprocessing finishes. For the full Docker pipeline’s canonical layout, see Outputs.

How to run

For setup, folder layout, settings, GPU and Drive notes, and the full run-through, follow the notebook below.

Open the notebook, edit WORKING_DIR in the USER SETTINGS cell, then Run All. Colab vs local Jupyter is detected automatically.

Lite outputs are related to but not identical to the full pipeline layout; see Outputs for the canonical Docker derivative structure.

See also