Figure 5. Some networks and mechanisms that have been proposed for normalization.

a | The connections underlying normalization can be arranged in a feedforward manner, in which signals contributing to the denominator have not been normalized themselves. b | An alternative configuration involves feedback. The function f performs the appropriate transformation of signals so that they can be multiplied by the input, giving rise to division in steady state^43,44. c | A resistor–capacitor (C) circuit and its transformation of an impulse into an exponential response. Conductance g determines both response gain and time constant. d | Effect of stimulus contrast on impulse responses of a lateral geniculate nucleus (LGN) neuron. Increasing contrast (left part) causes impulse responses to be weaker and faster, both in the model (middle part) and in the data (right part). e | Synaptic depression as a mechanism for normalization. Depression changes the relationship between presynaptic current and postsynaptic current (arbitrary units) in a divisive way. f,g | Noise as a mechanism for normalization (arbitrary units). The transformation between stimulus-driven membrane potential (g) and firing rate (f) depends on signals originating from the rest of the brain in the form of `ongoing activity', modelled from the point of view of a single neuron as noise added to the membrane potential (shown by the inset Gaussian curve in g). Data in part d from REF. 35; data in part e from REF. 84; data in parts f and g from REF. 143.