Purkinje neuron network (Zang et al. 2020)

Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. PRCs exhibit strong firing-rate adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model we demonstrate that the rate adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na+ channels. Then we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. The changes in PRC cause oscillations and spike correlations only at high firing rates. The causal role of the PRC is confirmed using a simpler coupled oscillator network model. This mechanism enables transient oscillations between fast-spiking neurons that thereby form PC assemblies. Our work demonstrates that rate adaptation of PRCs can spatio-temporally organize the PC input to cerebellar nuclei.

Model Type: Neuron or other electrically excitable cell; Realistic Network

Region(s) or Organism(s): Cerebellum

Cell Type(s): Cerebellum Purkinje GABA cell

Model Concept(s): Phase Response Curves; Action Potentials; Spatio-temporal Activity Patterns; Synchronization; Action Potential Initiation; Oscillations

Simulation Environment: NEURON; MATLAB

Implementer(s): Zang, Yunliang ; Hong, Sungho [shhong at oist.jp]


Zang Y, Hong S, De Schutter E. (2020). Firing rate-dependent phase responses of Purkinje cells support transient oscillations. eLife. 9 [PubMed]

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