Effects of neuronal adaptation currents on network-based spike rate oscillations
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KeywordsExternal Input Spike Rate Synaptic Inhibition Recurrent Inhibition Neuronal Adaptation
Local field potential in-vivo recordings often show oscillations with frequencies ranging from < 1 Hz to 100 Hz. The underlying mechanism could change across frequency bands but likely involves network interactions such as recurrent synaptic excitation-inhibition loops. Particularly fast rhythmic activity in the beta and gamma range is thought to be caused by synaptic inhibition . Although these oscillations primarily depend on synaptic properties, their frequency is significantly influenced by the passive membrane characteristics of single cells . In addition, neuronal membranes typically contain slowly deactivating voltage-dependent as well as calcium-activated potassium channels both which mediate spike rate adaptation.
Here we investigate how the dynamics of such neuronal adaptation currents contribute to synaptically generated spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely delay-coupled adapting spiking model neurons we take a mean-field approach using the Fokker-Planck equation to analyze oscillatory network activity. In the limit of slow adaptation timescales we obtain population spike rates and membrane potential distributions . To allow for a linear stability analysis we derive a low-dimensional system of ordinary differential equations from the Fokker-Planck mean-field model. This system effectively describes the activity of the network while retaining the features of the spiking neurons (i.e. the model parameters).
This work was supported by the DFG Collaborative Research Center SFB910.
- 3.Augustin M, Ladenbauer J, Obermayer K: How adaptation shapes spike rate oscillations in recurrent neuronal networks. Front Comp Neurosci.Google Scholar
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