"In this study, we developed a general description of parameter combinations for which specified characteristics of neuronal or network activity are constant. Our approach is based on the implicit function theorem and is applicable to activity characteristics that smoothly depend on parameters. Such smoothness is often intrinsic to neuronal systems when they are in stable functional states. The conclusions about how parameters compensate each other, developed in this study, can thus be used even without regard to the specific mathematical model describing a particular neuron or neuronal network. ..."

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

Cell Type(s): Leech heart interneuron

Currents: I T low threshold; I h; I Calcium

Model Concept(s): Methods

Simulation Environment: MATLAB (web link to model)

References:

Olypher AV, Calabrese RL. (2007). Using constraints on neuronal activity to reveal compensatory changes in neuronal parameters. Journal of neurophysiology. 98 [PubMed]