ReviewFrontiers in network physiology2026
Self-organisation of complex dynamical systems: from synergetics to neuromorphic systems.
Review in Frontiers in network physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The intuitive idea of self-organisation in complex dynamical systems is that global patterns and structures emerge from locally interacting elements like atoms in laser beams, molecules in chemical reactions, proteins in cells, cells in organs, neurons in brains, agents in markets, etc. Hermann Haken introduced a mathematically precise and rigorous formalism of synergetics. In this framework we define local activity as the cause of self-organizing complexity which can be tested in an explicit and constructive manner. This principle of local activity can also be defined in the theory of nonlinear electronic circuits. It is not restricted to a certain domain, but can be generalized and proven for the class of nonlinear reaction-diffusion systems in physics, chemistry, biology, and brain research. An example is an improved Hodgkin-Huxley axon circuit model of the brain as network of physiology. It turns out that neuromorphic computing approximates the energetic efficiency of human brains and avoids the enormous increase of energy consumption with traditional digital computing. Obviously, traditional digitalization is closely connected with one of the most challenging problems of mankind-the increasing demand for energy with all its consequences for environmental and climate problems. Thus, synergetics with the local activity principle strongly supports the request for sustainable computing inspired by network physiology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.