TY - JOUR
T1 - Cortical Spike Synchrony as a Measure of Input Familiarity
AU - Korndörfer, Clemens
AU - Ullner, Ekkehard
AU - Garcia-Ojalvo, Jordi
AU - Pipa, Gordon
N1 - J.G.O. was supported by the Ministerio de Economia y Competividad and FEDER
(Spain, project FIS2015-66503-C3-1-P) and the ICREA Academia programme.
E.U. acknowledges support from the Scottish Universities Life Sciences Alliance
(SULSA) and HPC-Europa2.
PY - 2017/9
Y1 - 2017/9
N2 - 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.
AB - 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.
U2 - 10.1162/NECO_a_00987
DO - 10.1162/NECO_a_00987
M3 - Article
VL - 29
SP - 2491
EP - 2510
JO - Neural computation
JF - Neural computation
SN - 0899-7667
IS - 9
ER -