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. 1991 Dec 15;88(24):10983–10987. doi: 10.1073/pnas.88.24.10983

Chemical implementation of neural networks and Turing machines.

A Hjelmfelt 1, E D Weinberger 1, J Ross 1
PMCID: PMC53057  PMID: 1763012

Abstract

We propose a reversible reaction mechanism with a single stationary state in which certain concentrations assume either high or low values dependent on the concentration of a catalyst. The properties of this mechanism are those of a McCulloch-Pitts neuron. We suggest a mechanism of interneuronal connections in which the stationary state of a chemical neuron is determined by the state of other neurons in a homogeneous chemical system and is thus a "hardware" chemical implementation of neural networks. Specific connections are determined for the construction of logic gates: AND, NOR, etc. Neural networks may be constructed in which the flow of time is continuous and computations are achieved by the attainment of a stationary state of the entire chemical reaction system, or in which the flow of time is discretized by an oscillatory reaction. In another article, we will give a chemical implementation of finite state machines and stack memories, with which in principle the construction of a universal Turing machine is possible.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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