We examine the effect of the phase-resetting curve (PRC) on the transfer of
correlated input signals into correlated output spikes in a class of neural
models receiving noisy, super-threshold stimulation. We use linear response
theory to approximate the spike correlation coefficient in terms of moments of
the associated exit time problem, and contrast the results for Type I vs. Type
II models and across the different timescales over which spike correlations can
be assessed. We find that, on long timescales, Type I oscillators transfer
correlations much more efficiently than Type II oscillators. On short
timescales this trend reverses, with the relative efficiency switching at a
timescale that depends on the mean and standard deviation of input currents.
This switch occurs over timescales that could be exploited by downstream
circuits