Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)

Help downloading and running models
"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. ..."
1 . Olypher AV, Calabrese RL (2007) Using constraints on neuronal activity to reveal compensatory changes in neuronal parameters. J Neurophysiol 98:3749-58 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Leech heart interneuron;
Channel(s): I T low threshold; I h; I Calcium;
Gap Junctions:
Simulation Environment: MATLAB (web link to model);
Model Concept(s): Methods;
Search NeuronDB for information about:  I T low threshold; I h; I Calcium;
(located via links below)