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Pattern phase diagram of spiking neurons on spatial networks
Dionysios Georgiadis1, Didier Sornette2
1Future Resilient Systems, Singapore and Department of Management, Technology and Economics, ETH Zurich, Switzerland.
Physical Review. E
|May 22, 2019
Summary
Researchers simulated neuronal activity, revealing spatiotemporal patterns and critical-like dynamics. Network structure influences these dynamics, leading to phenomena like neuronal avalanches following Zipf's law.
Area of Science:
- Computational neuroscience
- Complex systems
Background:
- Neuronal networks exhibit complex dynamics.
- Understanding emergent phenomena in neural systems is crucial.
Purpose of the Study:
- To investigate spatiotemporal pattern formation in an abstracted neuronal model.
- To explore the influence of network topology on neural dynamics.
Main Methods:
- Numerical simulation of pulse-coupled, discretized relaxation oscillators.
- Systematic variation of network edge density and spatial embeddedness.
Main Results:
- Observed a unique spatiotemporal pattern resembling a frothing liquid at intermediate edge density and high spatial embeddedness.
- Identified neuronal avalanche size distributions following Zipf's law (power law with exponent one) with increasing edge density.
- Documented a transition from pattern formation to metastability and finally to full synchrony as edge density increased.
Conclusions:
- Network topology significantly shapes emergent neuronal dynamics.
- The model exhibits critical-like behavior and phase transitions relevant to neural function.
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