Spike synchrony, which occurs in various cortical areas in response to specific perception, action, and memory tasks, has sparked a long-standing debate on the nature of temporal organization in cortex. One prominent view is that this type of synchrony facilitates the binding or grouping of separate stimulus components. We argue instead for a more general function: a measure of the prior probability of incoming stimuli, implemented by long-range, horizontal, intracortical connections. We show that networks of this kind—pulse-coupled excitatory spiking networks in a noisy environment—can provide a sufficient substrate for a mechanism of stimulus-dependent spike synchrony. Their dynamics allow for a quick (few spikes) estimate of the match between inputs and the input history as encoded in the network structure. Given the ubiquity of small, strongly excitatory subnetworks in cortex, we thus propose that many experimental observations of spike synchrony can be viewed as signs of input patterns that resemble long-term experience—that is, of patterns with high prior probability.
Korndörfer, C., Ullner, E., Garcia-Ojalvo, J., & Pipa, G. (2017). Cortical Spike Synchrony as a Measure of Input Familiarity. Neural computation, 29(9), 2491-2510. https://doi.org/10.1162/NECO_a_00987