  Measured responses from visual cortical neurons show that spike times tend to
be correlated rather than exactly Poisson distributed. Fano factors vary and
are usually greater than 1 due to the tendency of spikes being clustered into
bursts. We show that this behavior emerges naturally in a balanced cortical
network model with random connectivity and conductance-based synapses. We
employ mean field theory with correctly colored noise to describe temporal
correlations in the neuronal activity. Our results illuminate the connection
between two independent experimental findings: high conductance states of
cortical neurons in their natural environment, and variable non-Poissonian
spike statistics with Fano factors greater than 1.
