The examples described above consider conditions in which the excitatory input that drives the neuron varies independently of the inhibition received by that same neuron. We know, however, this is not generally the case, as excitation and inhibition appear tightly coupled in cortical networks. Under this condition, gain modulation may be a natural consequence of scaling inhibition with excitation (Pouille et al., 2009; Shadlen and Newsome, 1998). Thus with increasing input strength, it becomes progressively harder for any given quantity of excitation to reach spike threshold because of the concomitant increase in inhibition. If the relationship between excitation and inhibition are chosen properly, models show that the interaction between these two opposing conductances can lead to pure changes in gain (Shadlen and Newsome, 1998).
