  The co-occurrence of action potentials of pairs of neurons within short time
intervals is known since long. Such synchronous events can appear time-locked
to the behavior of an animal and also theoretical considerations argue for a
functional role of synchrony. Early theoretical work tried to explain
correlated activity by neurons transmitting common fluctuations due to shared
inputs. This, however, overestimates correlations. Recently the recurrent
connectivity of cortical networks was shown responsible for the observed low
baseline correlations. Two different explanations were given: One argues that
excitatory and inhibitory population activities closely follow the external
inputs to the network, so that their effects on a pair of cells mutually
cancel. Another explanation relies on negative recurrent feedback to suppress
fluctuations in the population activity, equivalent to small correlations. In a
biological neuronal network one expects both, external inputs and recurrence,
to affect correlated activity. The present work extends the theoretical
framework of correlations to include both contributions and explains their
qualitative differences. Moreover the study shows that the arguments of fast
tracking and recurrent feedback are not equivalent, only the latter correctly
predicts the cell-type specific correlations.
