Topic: conductance-based synapses

A signature feature of cortical circuits is the irregularity of neuronal firing, which manifests itself in the high temporal variability of spiking and the broad distribution of rates. Theoretical works have shown that this feature emerges dynamically in network models if coupling between cells is strong, i.e. if the mean number of synapses per neuron K is large and synaptic efficacy is of order 1/\sqrt{K}. However, the degree to which these models capture the mechanisms underlying neuronal firing in cortical circuits is not fully understood. Results have been derived using neuron models with

Synaptic changes driven by Hebbian plasticity are unstable and require compensatory mechanisms to homeostatically control neuronal activity. Synaptic scaling regulates the synaptic efficacies to bring individual neurons to a set firing regime [1]. However, the timescales of synaptic scaling are too slow to counterbalance the rapid growth due to Hebbian mechanisms [2]. Heterosynaptic plasticity that operates on timescales similar to Hebbian processes can prevent runaway potentiation [3] but its ability to homeostatically control activity is uncertain. Here, we introduce aggregate scaling, a si