SOURCE-LINKED INTELLIGENCE
Formal Properties of Language as Constraints on Neural Dynamics
What must a neural system be capable of to implement language? Current research annotates stimuli with linguistic variables and tests which electrodes, voxels, or language-model layers predict neural activity. Yet predictive success leaves mechanisms under-constrained. Here, we show that algebraic properties of language specify invariants that mechanisms must preserve: non-associative hierarchical grouping, commutativity, recursive closure, access to substructures, and structured workspace transitions. We term this the Neural Admissibility Program (NAP). Syntactic structure building is analyze
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T08:41:56.000Z
First collected: 2026-09-20T12:41:04.663Z. This is not the publication date.