ICSAC · The Science of Consciousness 2026 · San Diego

Brain, or language model?
Tell them apart by their dynamics.

The unfolding argument says a recurrent brain could be matched by a feedforward network with identical behaviour. If behaviour can't separate them, the internal dynamics have to. Here is what that separation looks like when you can measure it — on real recordings and real models.

Specimen 1 / 7 · next-state variance partition score 0/0

What drives the next state?

input-driven share
0%external input explains…100%
recurrence-generated share
0%its own past state explains, beyond input…100%

Schematic phase portrait — a moving point under input drive (blue) vs. its own recurrence (amber). Illustrative; the measured quantity is the readout at left.

Which substrate produced this?

score 0/0

Every number here is the real measured value. Brains: rat orbitofrontal cortex (164 sessions, 31 rats) and primate entorhinal cortex (14 sessions, 2 monkeys). Models: five instruct transformers, 1.5B–9B parameters, three families.

Rat frontal cortex · commitment to a perceptual decision · dominant autonomous eigenvalue |λ|

Trace reconstructed to the reported statistics of the frontal-cortex result (Luo et al. 2025; demix, Huang et al. 2025): baseline |λ|≈0.90 rising to ≈0.93 by +250 ms — median +0.016, p = 2.2×10⁻⁵, in 75 of 115 sessions; stimulus-aligned +0.002 (n.s.). Illustrative of the published curve, not a re-plot of raw session data.