New Theoretical Framework Unifies Learning, Memory, and Cognition Through Cognitive Field Theory
A new theoretical framework called Cognitive Field Theory (CFT) has been proposed on arXiv, modeling cognition as a collective nonequilibrium phenomenon governed by a learned geometric manifold. The theory draws on concepts from physics — including Riemannian geometry, nonlocal memory kernels, and relaxation spectra — to describe learning, memory, inference, and selfhood within a single formalism. If validated, it could offer a unified mathematical language bridging neuroscience and artificial intelligence research.
Submitted to arXiv's quantitative biology (neurons and cognition) section, the paper introduces a stochastic cognitive-field equation defined on an adaptive Riemannian manifold, from which the authors derive a 'memory-dressed' cognitive field equation incorporating retarded self-energy feedback. A central construct is the time-scale density of states (TDOS), which characterizes the distribution of collective relaxation modes and is presented as a fundamental dynamical descriptor of cognition. The accumulation of weakly damped modes is argued to suppress a 'cognitive forgetting gap,' enhance collective susceptibility, and push the system toward a near-critical regime associated with long-time contextual persistence and cognitive coherence. The framework is intended to apply to both biological neural systems and artificial learning systems, offering a common theoretical vocabulary for phenomena that have historically been treated with separate models. The paper is 41 pages with 3 figures and is currently in its fifth revision as of June 2026, suggesting ongoing refinement.
What's missing
As a theoretical preprint, the paper has not yet undergone formal peer review. Key open questions include whether the proposed TDOS and cognitive manifold constructs yield experimentally testable predictions distinguishable from existing models, and whether the near-critical regime described has empirical correlates in neuroscience or AI benchmarks. No empirical validation or simulation results are described in the abstract.
What different sources said
- arXiv q-bioCenter
Cognitive Field Theory of Learning, Inference, and Emergence
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