Breaking balance: how network architecture impacts spiking dynamics

Networks with strong recurrent excitation and inhibition that are roughly balanced to one another provide a model of cortex that accounts for a wide variety of observed dynamics. However, a formal adherence to balanced conditions often precludes the possibility for interesting macroscopic network dynamics.  I will review recent work that discusses how targeted deviations from a balanced state allow interesting macroscale dynamics, which capture rich cortical activity reported in experiments.  One deviation involves assembly structure within excitatory networks that promotes metastable population dynamics, capturing the reported distinction between spontaneous and evoked spiking dynamics.  These assemblies can be naturally embedded using a combination of spike timing dependent plasticity and homeostatic synaptic regulation.  A second deviation involves the extension of balanced networks to include a spatial dimension in cortical networks.  When input correlations are spatially broad then appreciable, yet moderate, noise correlations occur naturally and can match observed correlation distributions in a variety of cortical network.  The combination of these results show how structured architecture in balanced networks gives rise to important macroscopic cortical dynamics, yet nevertheless continues to provide the microscopic variability and rough asynchrony that are prominent feature of cortical spiking responses.