  We study temporal correlations of interspike intervals (ISIs), quantified by
the network-averaged serial correlation coefficient (SCC), in networks of both
current- and conductance-based purely inhibitory integrate-and-fire neurons.
Numerical simulations reveal transitions to negative SCCs at intermediate
values of bias current drive and network size. As bias drive and network size
are increased past these values, the SCC returns to zero. The SCC is maximally
negative at an intermediate value of the network oscillation strength. The
dependence of the SCC on two canonical schemes for synaptic connectivity is
studied, and it is shown that the results occur robustly in both schemes. For
conductance-based synapses, the SCC becomes negative at the onset of both a
fast and slow coherent network oscillation. Finally, we devise a noise-reduced
diffusion approximation for current-based networks that accounts for the
observed temporal correlation transitions.
