This model was developed using voltage clamp data and existing LP models to assemble an initial set of currents which were then adjusted by extensive fitting to a long data set of an isolated LP neuron. The main points of the work are a) automatic fitting is difficult but works when the method is carefully adjusted to the problem (and the initial guess is good enough). b) The resulting model (in this case) made reasonable predictions for manipulations not included in the original data set, e.g., blocking some of the ionic currents. c) The model is reasonably robust against changes in parameters but the different parameters vary a lot in this respect. d) The model is suitable for use in a network and has been used for this purpose (Ivanchenko et al. 2008)
Model Type: Neuron or other electrically excitable cell
Cell Type(s): Hodgkin-Huxley neuron; Stomatogastric Ganglion (STG) Lateral Pyloric (LP) cell
Currents: I A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium
Model Concept(s): Activity Patterns; Bursting; Parameter Fitting; Invertebrate; Methods; Parameter sensitivity
Simulation Environment: C or C++ program
Implementer(s): Nowotny, Thomas [t.nowotny at sussex.ac.uk]
References:
Nowotny T, Levi R, Selverston AI. (2008). Probing the dynamics of identified neurons with a data-driven modeling approach. PloS one. 3 [PubMed]
Ivanchenko MV, Thomas Nowotny, Selverston AI, Rabinovich MI. (2008). Pacemaker and network mechanisms of rhythm generation: cooperation and competition. Journal of theoretical biology. 253 [PubMed]