|
SpikingNeuron [ModelLib] [EPhys Plugins]Base class for a spiking (point-) neuron
Each model of a spiking neuron has a name(). The model is implemented as a set of differential equations
The state of the model is described by the state vector While integrating the model, the current values of the ionic currents and their corresponding conductances can be retrieved by the currents(double*) const and conductances(double*) const functions. The corresponding names of the currents and conductances are returned by conductances(vector<string>&) const and currents(vector<string>&) const, respectively. The unit of the conductances is conductanceUnit() and the the one of the currents is currentUnit(). Parameter values of the model can be made accessible by adding them to the Options in add(). Changed parameter values are read out from the Options by notify(). The parameter values are classified as either scalingFlag(), modelFlag(), or descriptionFlag(). SpikingNeuron defines two parameters offset() and gain() with default values 0 and 1, respectively, that should be applied to whatever input before it is passed on as the stimulus s for computing the derivatives via operator()(). |
![[ left( begin{array}{c} frac{dx_1}{dt} \ frac{dx_2}{dt} \ vdots \ frac{dx_n}{dt} end{array} right) = left( begin{array}{c} f_1(x_1, x_2, ldots, x_n, s) \ f_2(x_1, x_2, ldots, x_n, s) \ vdots \ f_n(x_1, x_2, ldots, x_n, s) end{array} right) ]](ephys-form_0.png)
of dimension n = 
with respect to time t for the current state x and the stimulus s. The