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Communication through resonance in spiking neuronal networks
Gerald Hahn1, Alejandro F Bujan2, Yves Frégnac1
1Unité de Neuroscience, Information et Complexité (UNIC), CNRS, Gif-sur-Yvette, France.
Plos Computational Biology
|August 29, 2014
Summary
This study introduces "communication through resonance," a novel mechanism for neuronal signal propagation across weakly connected brain areas. It explains how brain oscillations amplify weak signals, enabling information processing in distributed cortical networks.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- The brain's cortex processes information via distributed networks.
- Efficient neuronal communication across weakly connected regions is crucial for complex cognitive functions.
- Existing models struggle to explain signal propagation across sparse cortical connections.
Purpose of the Study:
- To propose a novel mechanism for routing neuronal activity across weakly connected cortical areas.
- To explain how synchronous spiking activity can propagate and be supported by oscillations.
- To investigate the role of network resonance in signal amplification and propagation.
Main Methods:
- Development of a theoretical model for neuronal signal propagation.
- Simulation of synchronous spiking activity in weakly connected networks.
- Analysis of the role of oscillatory activity and network resonance.
Main Results:
- Proposed a "communication through resonance" mechanism where oscillations amplify weak synchronous signals.
- Demonstrated that coherent oscillations emerge as a consequence of signal propagation, not a prerequisite.
- Showed that ongoing brain activity states modulate the efficiency of communication through resonance.
Conclusions:
- The proposed model offers a unified explanation for signal propagation and oscillation coherence in cortical networks.
- Communication through resonance provides a mechanism for information processing in distributed brain systems.
- Modulating ongoing brain activity may offer a way to influence information flow in cortical networks.
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