Brainana Lite

Brainana Lite is a notebook-based workflow for volumetric T1w preprocessing of a single macaque subject, in Jupyter or Google Colab—no Docker or Nextflow. For production batch work, multiple modalities, surfaces, and the full HTML QC suite, use the full Docker pipeline (Installation, Usage notes).

Run it

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

When to use it

  • 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

What you get

After Run All, derivatives are written in a BIDS-styled layout (exact filenames and the output tree are printed when preprocessing finishes):

  • 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)

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

See also