.. meta::
   :description: Hesse, J. and T. Gross (2014). Self-organized criticality as a fundamental property of neural systems --- a review of the neural criticality hypothesis and its implications for complex systems at phase-transition boundaries.
   :keywords: self-organized criticality, phase transition, neural systems, critical state, avalanche, power law, complex systems, ax19, causal concentration, h-star

.. TODO AA: Page maturity --- update StayC when reviewed
   Page status: MMv0r1_draft_2026m04d10


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Hesse & Gross (2014): *Self-organized criticality*
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.. rubric:: Full citation

Hesse, J. and T. Gross (2014). "Self-organized criticality as a
fundamental property of neural systems." *Frontiers in Systems
Neuroscience* 8: 166.

- `Full text (open access, PDF)
  <https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2014.00166/full>`__
- DOI: `10.3389/fnsys.2014.00166
  <https://doi.org/10.3389/fnsys.2014.00166>`__


Abstract (from the original)
===============================

The neural criticality hypothesis states that the brain may be poised
in a critical state at a boundary between different types of dynamics.
Theoretical and experimental studies show that critical systems often
exhibit optimal computational properties, suggesting the possibility
that criticality has been evolutionarily selected as a useful trait for
our nervous system. Evidence for criticality has been found in cell
cultures, brain slices, and anesthetized animals. Yet, inconsistent
results were reported for recordings in awake animals and humans, and
current results point to open questions about the exact nature and
mechanism of criticality, as well as its functional role. Therefore,
the criticality hypothesis has remained a controversial proposition.
Here, we provide an account of the mathematical and physical
foundations of criticality. In the light of this conceptual framework,
we then review and discuss recent experimental studies with the aim of
identifying important next steps to be taken and connections to other
fields that should be explored.


Why this paper matters
========================

Phase transitions are moments when a small perturbation has outsized
effect on the entire system. A system poised at the boundary between
two dynamical regimes --- the critical point --- exhibits precisely
the kind of causal concentration that ax19 (Probabilistic Causal
Concentration) formalizes: **at the critical point, a single event
can cascade through the entire system, producing effects
disproportionate to its apparent cause.**

Hesse and Gross review the evidence that biological neural systems
may be self-organized to operate near such critical points, where
computational properties are optimal. The relevance to the HEAVEN
series is threefold:

1. **Mechanism for h* concentration.** ax19 asserts that at any
   moment, one individual has maximal causal influence. Phase
   transitions provide a *physical mechanism* by which such
   concentration can arise naturally: when a complex system is near
   criticality, the perturbation that triggers the cascade has
   outsized influence, and the identity of that perturbation is
   contingent (it depends on timing and position in the network, not
   on inherent importance). This is precisely the h* phenomenon ---
   not that h* is inherently special, but that h* happens to be at the
   right node at the right time.

2. **Empirical testability.** The neural criticality hypothesis is
   itself testable and contested, providing a model for how ax19's
   testability should work: look for power-law distributions in
   cascading effects, long-range correlations, and sensitivity to
   initial conditions at specific moments.

3. **Self-organization.** The "self-organized" aspect is relevant to
   the ZION framework: systems that maintain themselves near
   criticality through internal feedback (not external tuning) exhibit
   the kind of self-correcting dynamics that the ZION cycle
   (Zoning, Investigating, Organizing, Navigating) attempts to
   formalize at the civilizational level.

The paper does not prove ax19. It provides a well-studied physical
framework from a different domain (neuroscience) that exhibits the
same structural phenomenon ax19 describes: causal concentration at
phase-transition boundaries. If the brain self-organizes toward
criticality because that is where computation is optimal, the
question arises: does civilization self-organize toward criticality
too --- and if so, what happens at the critical point?
