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Research PaperResearchia:202602.24020

Critical Scaling and Metabolic Regulation in a Ginzburg--Landau Theory of Cognitive Dynamics

Gunn Kim

Abstract

We formulate a phenomenological effective field theory in which biological intelligence emerges as a macroscopic order parameter sustained by continuous metabolic flux. By modeling cognition as a coarse-grained neural activity field governed by a variational free energy, we derive closed-form expressions for information capacity and structural susceptibility using a Gaussian maximum entropy approximation. The theory predicts a universal algebraic divergence of the susceptibility, $χ\sim K^{-3/2}...

Submitted: February 24, 2026Subjects: Neuroscience; Neuroscience

Description / Details

We formulate a phenomenological effective field theory in which biological intelligence emerges as a macroscopic order parameter sustained by continuous metabolic flux. By modeling cognition as a coarse-grained neural activity field governed by a variational free energy, we derive closed-form expressions for information capacity and structural susceptibility using a Gaussian maximum entropy approximation. The theory predicts a universal algebraic divergence of the susceptibility, χK3/2χ\sim K^{-3/2}, as the structural stiffness KK approaches the instability threshold. The exponent γ=3/2γ= 3/2 is consistent with the mean-field branching process universality class, thereby providing a theoretical rationale for the observed avalanche size exponent τ3/2τ\approx 3/2 in cortical dynamics without invoking microscopic equivalence. We identify adult cognition as a metabolically pinned non-equilibrium steady state maintained near the critical regime ΓK/α1Γ\equiv K/α\approx 1 by continuous metabolic regulation, while pathological decline corresponds to a delocalization transition triggered by the violation of structural stability conditions. The framework generates concrete, falsifiable predictions for attention scaling, altered states of consciousness, and transcranial magnetic stimulation responses, each of which can be tested against existing neuroimaging and electrophysiological datasets.


Source: arXiv:2602.19023v1 - http://arxiv.org/abs/2602.19023v1 PDF: https://arxiv.org/pdf/2602.19023v1 Original Link: http://arxiv.org/abs/2602.19023v1

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Date:
Feb 24, 2026
Topic:
Neuroscience
Area:
Neuroscience
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