Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions.

Ultimately, whether or not a neuron produces a spike determines its contribution to local computations. In response to brief stimuli the probability a neuron will fire can be described by its input-output function, which depends on the net balance and timing of excitatory and inhibitory currents. While excitatory and inhibitory synapses are plastic, most studies examine plasticity of subthreshold events. Thus, the effects of concerted regulation of excitatory and inhibitory synaptic strength on neuronal input-output functions are not well understood. Here, theoretical analyses reveal that excitatory synaptic strength controls the threshold of the neuronal input-output function, while inhibitory plasticity alters the threshold and gain. Experimentally, changes in the balance of excitation and inhibition in CA1 pyramidal neurons also altered their input-output function as predicted by the model. These results support the existence of two functional modes of plasticity that can be used to optimize information processing: threshold and gain plasticity.