Firing rate equations require a spike synchrony mechanism to correctly describe fast oscillations in inhibitory networks
arXiv:1705.09205 · doi:10.1371/journal.pcbi.1005881
Abstract
Recurrently coupled networks of inhibitory neurons robustly generate oscillations in the gamma band. Nonetheless, the corresponding Wilson-Cowan type firing rate equation for such an inhibitory population does not generate such oscillations without an explicit time delay. We show that this discrepancy is due to a voltage-dependent spike-synchronization mechanism inherent in networks of spiking neurons which is not captured by standard firing rate equations. Here we investigate an exact low-dimensional description for a network of heterogeneous canonical type-I inhibitory neurons which includes the sub-threshold dynamics crucial for generating synchronous states. In the limit of slow synaptic kinetics the spike-synchrony mechanism is suppressed and the standard Wilson-Cowan equations are formally recovered as long as external inputs are also slow. However, even in this limit synchronous spiking can be elicited by inputs which fluctuate on a time-scale of the membrane time-constant of the neurons. Our meanfield equations therefore represent an extension of the standard Wilson-Cowan equations in which spike synchrony is also correctly described.
References in corpus (18)
- Low Dimensional Behavior of Large Systems of Globally Coupled Oscillators
- Long Time Evolution of Phase Oscillator Systems
- Macroscopic description for networks of spiking neurons
- Mathematical frameworks for oscillatory network dynamics in neuroscience
- Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size
- Slow Switching in Globally Coupled Oscillators: Robustness and Occurrence through Delayed Coupling
- Comment on "Long Time Evolution of Phase Oscillator Systems" [Chaos 19,023117 (2009), arXiv:0902.2773]
- Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation
- From quasiperiodic partial synchronization to collective chaos in populations of inhibitory neurons with delay
- Ott-Antonsen attractiveness for parameter-dependent oscillatory networks
- How effective delays shape oscillatory dynamics in neuronal networks
- On the equivalence of phase-oscillator and integrate-and-fire models
- Synchrony-induced modes of oscillation of a neural field model
- Modeling the Network Dynamics of Pulse-Coupled Neurons
- A minimal model of partial synchrony
- Dynamics of a population of oscillatory and excitable elements
- Average activity of excitatory and inhibitory neural populations
- Low-dimensional firing rate dynamics of spiking neuron networks
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