We show, in a simplified network consisting of an oscillator inhibiting a follower neuron, how the interaction between synaptic depression and a transient potassium current in the follower neuron determines the activity phase of this neuron. We derive a mathematical expression to determine at what phase of the oscillation the follower neuron becomes active. This expression can be used to understand which parameters determine the phase of activity of the follower as the frequency of the oscillator is changed. See paper for more.
Model Type: Realistic Network
Region(s) or Organism(s): Stomatogastric ganglion
Cell Type(s): Abstract Morris-Lecar neuron
Currents: I A
Model Concept(s): Activity Patterns; Bursting; Temporal Pattern Generation; Oscillations; Simplified Models
Simulation Environment: XPPAUT; MATLAB
Implementer(s): Nadim, Farzan [Farzan at andromeda.Rutgers.edu]; Bose, Amitabha [bose at njit.edu]; Lewis, Timothy [tlewis at cns.nyu.edu]
References:
Bose A, Manor Y, Nadim F. (2004). The activity phase of postsynaptic neurons in a simplified rhythmic network. Journal of computational neuroscience. 17 [PubMed]