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The functional significance of correlations between action potentials ofneurons is still a matter of vivid debates. In particular it is presentlyunclear how much synchrony is caused by afferent synchronized events and howmuch is intrinsic due to the connectivity structure of cortex. The availableanalytical approaches based on the diffusion approximation do not allow tomodel spike synchrony, preventing a thorough analysis. Here we theoreticallyinvestigate to what extent common synaptic afferents and synchronized inputseach contribute to closely time-locked spiking activity of pairs of neurons. Weemploy direct simulation and extend earlier analytical methods based on thediffusion approximation to pulse-coupling, allowing us to introduce preciselytimed correlations in the spiking activity of the synaptic afferents. Weinvestigate the transmission of correlated synaptic input currents by pairs ofintegrate-and-fire model neurons, so that the same input covariance can berealized by common inputs or by spiking synchrony. We identify two distinctregimes: In the limit of low correlation linear perturbation theory accuratelydetermines the correlation transmission coefficient, which is typically smallerthan unity, but increases sensitively even for weakly synchronous inputs. Inthe limit of high afferent correlation, in the presence of synchrony aqualitatively new picture arises. As the non-linear neuronal response becomesdominant, the output correlation becomes higher than the total correlation inthe input. This transmission coefficient larger unity is a direct consequenceof non-linear neural processing in the presence of noise, elucidating howsynchrony-coded signals benefit from these generic properties present incortical networks.

Noise Suppression and Surplus Synchrony by Coincidence Detection