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Adaptation-dependent synchronization transitions and burst generations in electrically coupled neural networks
Lei Wang1, Pei-Ji Liang, Pu-Ming Zhang
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
International Journal of Neural Systems
|November 20, 2014
Summary
Spike frequency adaptation (SFA) in neurons impacts population synchronization nonmonotonically. Increased adaptation can also induce bursting in single neurons, suggesting adaptation influences both synchronous activity and burst firing.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Neurons encode information dynamically via spike frequency adaptation (SFA).
- Previous research focused on SFA's effect on pairwise neuronal synchronization, leaving population synchronization unclear.
- Understanding population synchronization with SFA is crucial for neural network dynamics.
Purpose of the Study:
- To numerically explore the influence of SFA on neuron population synchronization.
- To investigate SFA's effects across different network connectivities (regular, small-world, random).
- To analyze the relationship between adaptation degree and population synchronization patterns.
Main Methods:
- Numerical simulations of electrically coupled neuron networks.
- Exploration of networks with regular, small-world, and random connectivity.
- Analysis of cross-correlation indices and synchronization strength under varying adaptation levels.
Main Results:
- Cross-correlation indices significantly decreased with SFA, aligning with experimental findings.
- Population synchronization strength exhibited nonmonotonic changes dependent on the degree of adaptation.
- Single neurons transitioned from regular spiking to bursting as adaptation increased.
- Connection probability influenced population synchronization but not single-neuron burst generation.
Conclusions:
- Neuronal population synchronization is complex and adaptation-dependent.
- Burst firing in neuronal populations is also influenced by adaptation.
- SFA plays a critical role in shaping both individual neuron behavior and network-level dynamics.
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