Many of you asked how we create those pretty whole-brain plots with the cortical outline.
We just made it available as a Python package:
pni-lab.github.io/quickbrain/
Thanks! This package was really meant to be a one-trick pony, and I thought it was important to make that clear from the start.
The brain’s “default mode” and “action mode” networks are two sides of the same attractor.
Encoding a macro-scale Bayesian prior that biases processing toward internal or external drive.
To me, what’s especially compelling is the scale-free nature of the framework:
The same functional form applies across:
• single neurons
• microcircuits
• large-scale brain networks
Different substrates, different implementations, same computational imperative.
Looking forward to the colloquium in Bochum next Wednesday!
www.ini.rub.de/events/
Thanks a lot, that’s a great suggestion!
With sequential input, expected free energy minimization induces a solenoidal (rotational) flow component:
flow moves along the landscape, not just downhill.
This supports:
• metastable dynamics (NESS)
• efficient inference
• sequence storage
• "planning as inference"