Neural adaptation refers to the change over time in the responsiveness of a cell to a sustained current injection. In many neurons, the firing rate decreases throughout the spike train, when a constant stimulus is injected. Such behaviour can be incorporated into the Integrate-and-fire model by adding an extra conductance \(I_{\mathrm{adapt}}\) that depends on the neuronal spiking. This additional term has a quasi-ohmic form:

\[ I_{\mathrm{adapt}} = g_{\mathrm{adapt}}(V - E_m),\]

where the adaptive conductance \(g_{\mathrm{adapt}}\) is incremented by an amount \(\Delta g_{\mathrm{adapt}}\) whenever the neuron spikes, and otherwise it decays with a time constant of \( \tau_{\mathrm{adapt}}\):

\[\frac{\mathrm{d}}{\mathrm{d}t} g_{\mathrm{adapt}}= -\frac{g_{\mathrm{adapt}}}{\tau_{\mathrm{adapt}}}.\]

In Neuronify, both excitatory and inhibitory adaptive neurons are implemented. These can be chosen from the catagory menu with the following icons:

In option menu for these neurons, both the time constant \(\tau_{\mathrm{adapt}}\) and \(\Delta g_{\mathrm{adapt}}\) can be varied.