Implementing and morphing Boolean gates with adaptive synchronization: The case of spiking neurons
Boolean logic is the paradigm through which modern computation is performed in silica. When nonlinear dynamical systems are interacting in a directed graph, we show that computation abilities emerge spontaneously from adaptive synchronization, which actually can emulate Boolean logic. Precisely, we...
| Autores: | , , , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2022 |
| País: | España |
| Recursos: | Universidad Rey Juan Carlos |
| Repositório: | BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos |
| OAI Identifier: | oai:burjcdigital.urjc.es:10115/31563 |
| Acesso em linha: | https://hdl.handle.net/10115/31563 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Boolean logical gates Synchronization Dynamical systems Spiking neurons |
| Resumo: | Boolean logic is the paradigm through which modern computation is performed in silica. When nonlinear dynamical systems are interacting in a directed graph, we show that computation abilities emerge spontaneously from adaptive synchronization, which actually can emulate Boolean logic. Precisely, we demonstrate that a single dynamical unit, a spiking neuron modeled by the Hodgkin-Huxley model, can be used as the basic computational unit for realizing all the 16 Boolean logical gates with two inputs and one output, when it is coupled adaptively in a way that depends on the synchronization level between the two input signals. This is realized by means of a set of parameters, whose tuning offers even the possibility of constructing a morphing gate, i.e., a logical gate able to switch efficiently from one to another of such 16 Boolean gates. Extensive simulations demonstrate the efficiency and the accuracy of the proposed computational paradigm. |
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