ICSAC · The Science of Consciousness 2026 · San Diego

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

The unfolding argument says a recurrent brain could be matched by a feedforward network with identical behavior. If behavior can’t separate them, the internal dynamics have to. Every number in the game is measured.

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

What drives the next state?

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

Schematic phase portrait: a moving point, blending a path dictated from outside with the population’s own dynamics. Drawn in neutral until you answer. Illustrative; the measured quantity is the readout.

Which system produced this?

score 0/0

Read the preprint · · Email Nathan

Every number here is the real measured value. Brains: rat orbitofrontal cortex (Schiereck et al. 2026; 164 sessions, 31 rats) and primate entorhinal cortex (Neupane et al. 2024; 14 sessions, 2 monkeys). The commitment result on the poster comes from a third, separate recording set (Luo et al. 2025; 115 sessions, 12 rats). Models: five instruction-tuned AI models, 1.5B–9B parameters, three families.

Rat frontal cortex and striatum · commitment to a perceptual decision · dominant autonomous eigenvalue |λ| · mean ± SEM, Luo et al. 2025

Curves: the per-time-point mean ± SEM of the dominant autonomous eigenvalue |λ| across the 115 sessions of the rat frontal and striatal recordings (Luo et al. 2025; demix, Huang et al. 2026), as deposited with the preprint and drawn on the poster: flat near 0.90 before commitment, about 0.93 by +250 ms. Per session, the rise between windows centered at −150 and +200 ms is a median +0.016, p = 2.2×10⁻⁵, in 75 of 115 sessions and, by rat mean, 10 of 12 rats; animal-nested 95% interval for the mean rise +0.005 to +0.044, while a mixed-effects fit over rats gives p = 0.098. Aligned to the stimulus (zero at 100 ms after onset, as on the poster), a smaller and more gradual rise: +0.002 in the primary windows (n.s.), up to +0.010 with the window spacing matched. Specificity to commitment is supported, not established. The naive-DMD view is an illustrative sketch of the paper’s description of that estimator’s read-out on the same data (flat and noisy); its curve is not deposited.