Thalamo-Cortical Alpha
Cortex and thalamus drive each other. Fitted to sleep, it finds spindles at 13.45 Hz in people it never saw (p = 7.2e-11).
The Implicit Brain Model is a multimodal foundation model of whole-brain state and dynamics. One parameter set is declared once, and task-specific models are materialized out of it on demand. Because the representation is tied to the brain rather than to an instrument, film, MEG, EEG and motion capture all constrain the same parameters — data that could not otherwise be combined at all.
Specify a specific region, resolution, or bandwidth and only the processes and variables that actually matter materialize. The same brain can be coarse everywhere and fine around a single electrode.
M = materialize(R, r, B, F, A, T, P)
A brain's rhythms are not decoration laid over its anatomy — they are what a loop with a delay and a gain does. IBM-1 declares the loops themselves: which structures, in which order, with what conduction delay. A band is then a consequence to be checked, not a spectrum to be fitted.
Cortex and thalamus drive each other. Fitted to sleep, it finds spindles at 13.45 Hz in people it never saw (p = 7.2e-11).
Each slow theta cycle is cut into fast gamma slots, so an episode's order is carried by timing.
Visual cortex proposes, parietal cortex maps, frontal cortex picks one place to look.
Basal ganglia, cerebellum, default mode, arousal, valuation, hearing, vision and movement, each declared as a loop.
Each figure lights the structures the substrate declares for that loop and runs a wave around it. The on-screen rate is a depiction, not a measured frequency.
Every system the atlas carries — skeleton, muscle, vessels, viscera and the skin over them — on one driven skeleton, with the cortex closing the loop out to the muscle and back.
Control: scramble what the cortex learned and it still stands. The cortex owns the muscles; that is not the same as it knowing how to walk.
!pip install git+https://github.com/JacobFV/IBM-1
import ibm
from ibm.materialize import library
ibm.load_all(seal=True, strict=True)
print(ibm.REGISTRY.summary())
13 fields · 113 components · 22 supports · 20 anatomical systems 17 topologies · 30 processes · 115 implementations
m = library.MODELS["eeg_forward"]
print(m.request.describe())
request 'eeg-forward' subject=template frame=subject_t1 targets device.contact_potential, electromagnetic.potential regions cortex, conductor r(q) 3 rules, default 6 mm B(q) default Band(0.5-100Hz), 3 overrides window n=2048 dt=0.001s (2.048s, nyquist 500 Hz)
# one kernel carries the parameters for any materialization
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download("jacob-valdez/ibm-1",
"implicit/ibm1.implicit.s30k.e128.fused34.pt")