Theoretical Neuroscience of Self-Organized Criticality: From Formal Approaches to Realistic Models

Transmission across neocortical synapses depends on the frequency of presynaptic activity (Thomson & Deuchars, 1994). Interpyramidal synapses in layer V exhibit fast depression of synaptic transmission, while other types of synapses exhibit facilitation of transmission. To study the role of dynamic synapses in network computation, we propose a unified phenomenological model that allows computation of the postsynaptic current generated by both types of synapses when driven by an arbitrary pattern of action potential (AP) activity in a presynaptic population. Using this formalism, we analyze different regimes of synaptic transmission and demonstrate that dynamic synapses transmit different aspects of the presynaptic activity depending on the average presynaptic frequency. The model also allows for derivation of mean-field equations, which govern the activity of large, interconnected networks. We show that the dynamics of synaptic transmission results in complex sets of regular and irregular regimes of network activity.

Experience-dependent potentiation and depression of synaptic strength has been proposed to subserve learning and memory by changing the gain of signals conveyed between neurons. Here we examine synaptic plasticity between individual neocortical layer-5 pyramidal neurons. We show that an increase in the synaptic response, induced by pairing action-potential activity in pre- and postsynaptic neurons, was only observed when synaptic input occurred at low frequencies. This frequency-dependent increase in synaptic responses arises because of a redistribution of the available synaptic efficacy and not because of an increase in the efficacy. Redistribution of synaptic efficacy could represent a mechanism to change the content, rather than the gain, of signals conveyed between neurons.