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Optical Communication among Oscillatory Reactions and Photo-Excitable Systems: UV and Visible Radiation Can
Pier Luigi Gentili1, Maria Sole Giubila1, Raimondo Germani1
1Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di sotto 8, 06123, Perugia, Italy.
Angewandte Chemie (International Ed. in English)
|June 1, 2017
Summary
Chemically powered artificial neurons (ANs) utilize light signals to mimic real neuron communication. These ANs exhibit synchronized behaviors like in-phase and anti-phase firing, advancing neuromorphic engineering.
Area of Science:
- Neuromorphic Engineering
- Chemical Systems Biology
- Biophysics
Background:
- Neuromorphic engineering aims to create artificial systems that mimic the human brain.
- Oscillatory and excitable chemical systems offer a promising route for developing artificial neurons (ANs).
- Optical signals can be used to modulate chemical reactions for information processing.
Purpose of the Study:
- To develop artificial neurons (ANs) using oscillatory and excitable chemical systems.
- To investigate the use of UV and visible radiation as communication signals for ANs.
- To explore emergent network behaviors in ANs, mimicking neuronal communication.
Main Methods:
- Utilized Belousov-Zhabotinsky and Orban transformations as oscillatory chemical systems.
- Employed photochromic and fluorescent species as photo-excitable components.
- Experimentally and computationally modeled communication between pairs and triads of ANs using optical signals.
- Investigated feed-forward and recurrent network architectures.
Main Results:
- Demonstrated ANs communicating via one or two optical signals.
- Observed emergent properties including in-phase, out-of-phase, and anti-phase synchronizations.
- Achieved phase-locking behaviors dynamically mimicking real neuronal communication.
- ANs were powered by chemical energy and/or electromagnetic radiation.
Conclusions:
- Chemically powered ANs can effectively mimic neuronal communication through optical signaling.
- The developed ANs exhibit complex synchronized dynamics, crucial for neuromorphic applications.
- This approach provides a novel pathway for creating advanced artificial neural networks.
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