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Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
Tanguy Fardet1, Mathieu Ballandras1, Samuel Bottani1
1Laboratoire Matière et Systèmes Complexes, UMR 7057, Université Paris Diderot, USPC, Paris, France.
Frontiers in Neuroscience
|February 23, 2018
Summary
Network bursting in neurons is driven by excitatory populations with spike-driven adaptation. This study models this behavior, showing adaptation is key for synchronized intermittent bursting in neural networks.
Area of Science:
- Computational Neuroscience
- Neural Dynamics
- Systems Neuroscience
Background:
- Isolated neuronal populations can exhibit spontaneous synchronization and network bursting.
- This phenomenon is observed in cultured rodent cortical and hippocampal neurons.
- The precise conditions driving network bursting require further elucidation.
Purpose of the Study:
- To identify a sufficient condition for network bursting in oscillatory neuronal populations.
- To develop an analytical model for understanding network bursts in coupled adaptive neurons.
- To investigate the role of spike-driven adaptation in generating synchronized bursting.
Main Methods:
- Development of an analytical model using coupled adaptive exponential integrate-and-fire neurons.
- Analysis of network dynamics under strong synaptic coupling.
- Investigation of the role of after-hyperpolarization currents in bursting termination.
Main Results:
- A sufficient condition for network bursting is the presence of an excitatory population with spike-driven adaptation.
- Intrinsically tonic spiking neurons synchronize into intermittent bursting states with strong synaptic coupling.
- After-hyperpolarization currents are sufficient to terminate network bursts.
Conclusions:
- Spike-driven adaptation in excitatory neurons is a key mechanism for network bursting.
- The developed model provides an intuitive tool for understanding bursting dynamics.
- Experimental predictions are proposed regarding the effects of blocking specific after-hyperpolarization channels.
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