engram
Categories
All (7)
fmri (2)
neuralset (1)
neuroai (1)
nilearn (2)
preprocessing (1)
quarto (1)
reference (1)

An engram is the physical trace a memory leaves in the brain — so this is where I store what I learn.


%pip install --upgrade braindecode -q --progress-bar off
print('Hello, Brain!')
Events
1 min
print('Hello, brain!')
Minimal PyTorch neural network
1 min
Ref: https://docs.pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
FmriCleaner — nilearn.signal.clean, wrapped
3 min
fmri
nilearn
neuralset
neuroai

neuralset’s FmriCleaner silently drops ensure_finite when detrend/standardize/filters are all off — a walkthrough of facebookresearch/neuroai#130.

Jun 19, 2026
nilearn.signal.clean — the five knobs
4 min
fmri
nilearn
preprocessing

What nilearn.signal.clean actually does — detrend, standardize, filters, and ensure_finite — one knob at a time on a synthetic fMRI signal.

Jun 19, 2026
engram Cookbook
9 min
reference
quarto

The handbook for this repo - how it’s structured, the publishing workflow, and the Quarto authoring patterns I use, each shown as source + rendered output.

Jun 16, 2026
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