Turning neural complexity into a standardized cognitive infrastructure
Neural signals are high-dimensional, unstable, and individual-specific.
HABS extracts invariant latent cognitive dimensions from neural ground truth.
Projects chaotic neural activity into a shared latent cognitive space
Aligns individuals into a universal cognitive coordinate system
Enables cross-human comparability without recalibration
A standardized cognitive state vector derived from neural ground truth and aligned across populations.
"Neuromarkers are to cognition what embeddings are to language."
They transform biological signals into machine-readable cognitive primitives.
Powering the Human Cognitive State Infrastructure Layer
Projects unstable, high dimensional neural signals into a stable, shared latent cognitive space.
Aligns individuals into the same cognitive reference space — without per-user recalibration.
Transforms invariant cognitive embeddings into standardized, deployable state vectors.
Together, these three layers form the first invariant, population-aligned cognitive reference architecture.
Replicating HABS requires rebuilding the full embedding, alignment, and recoding stack.