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A Model for Evolutionary Structural Plasticity and Synchronization of a Network of Neurons
Gualberto Solís-Perales1, Jairo Sánchez Estrada1
1Depto. de Electrónica, CUCEI, Universidad de Guadalajara, Av. Revolución No. 1500, Guadalajara, Jal. C.P. 44430, Mexico.
Computational and Mathematical Methods in Medicine
|July 5, 2021
Summary
This study presents a model for neuron network synchronization, demonstrating time-dependent structural plasticity. The model shows how neuron connections adapt, mimicking biological neural networks for enhanced synchronization.
Area of Science:
- Computational Neuroscience
- Network Science
Background:
- Synchronized oscillations in neuron networks are crucial for structured communities.
- This synchronization is transient, capable of being enhanced or suppressed.
Purpose of the Study:
- To present a novel model of time-dependent structural plasticity for neuron network synchronization.
- To investigate the evolutionary behavior of neuronal couplings and their adaptive control mechanisms.
Main Methods:
- Modeling the physical connections (axons and dendrites) in a structural network.
- Developing a coupling force function based on membrane potential deviations and a threshold.
- Analyzing changes in node degree to demonstrate structural plasticity.
Main Results:
- The proposed model successfully reproduces transient synchronization characteristics.
- Neuronal coupling evolution parallels that of biological neuron networks.
- The coupling force acts as an adaptive controller, guiding neurons toward synchronization.
Conclusions:
- The model exhibits time-dependent structural plasticity through adaptive changes in coupling force.
- Neuron connections evolve based on membrane potential, regulating network structure over time.
- This framework offers insights into the dynamic nature of neural network organization.
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