Response variability and population coupling of cortical synaptic inputs are strongly influenced by network properties

The highly variable spiking of a cortical neuron is \"coupled\" to that of other neurons in the network. This has implications for sensory coding, and appears to represent a fundamental property of cortical sensory processing. To date, most studies of population coupling have focused on recorded spiking activity, an approach that suffers from several confounding issues. Moreover, the contributions of various network properties to population coupling are largely unexplored. To this end, we recorded the membrane potential (V) and the nearby LFP in the visual cortex of the turtle ex vivo wholebrain preparation during ongoing and visually-evoked activity. We used an algorithm to infer the excitatory conductance (g) from V, and calculated the g-LFP coupling. We found that g-LFP coupling was highly variable across neurons, and increased following visual stimulation before relaxing to intermediate values. To investigate the role of the network, we implemented a driven small-world network of leaky integrate-and-fire neurons. This model reproduces the large across-trial response variability and g-LFP coupling dynamic, and suggests crucial roles for anatomical and emergent network properties.