Engineering reaction-diffusion networks with properties of neural tissue

Abstract

We present an experimental system of networks of coupled non-linear chemical reactors, which we theoretically model within a reaction-diffusion framework. The networks consist of patterned arrays of diffusively coupled nanoliter-scale reactors containing the Belousov- Zhabotinsky (BZ) reaction. Microfluidic fabrication techniques are developed that provide the ability to vary the network topology, the reactor coupling strength and offer the freedom to choose whether an arbitrary reactor is inhibitory or excitatory coupled to its neighbor. This versatile experimental and theoretical framework can be used to create a wide variety of chemical networks. Here we design, construct and characterize chemical networks that achieve the complexity of central pattern generators (CPGs), which are found in the autonomic nervous system of a variety of organisms.

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Cited by in corpus (6)

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• Dynamics of Reaction-Diffusion Oscillators in Star Networks
• Diffusive coupling of two well-mixed compartments elucidates elementary principles of protein-based pattern formation
• Quantifying Rare Events in Stochastic Reaction-Diffusion Dynamics Using Tensor Networks
• Dynamics of Minimal Networks of Limit Cycle Oscillators
• Adiabatic soliton management: Controlling solitary wave motion while keeping the wave envelope unchanged