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

Abstract

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 integrateand-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.Cortical neuron sensory responses are remarkably variable across trials (Britten et al. 1993;Carandini 2004;Scholvinck et al. 2015). Because this variability tends to be correlated between pairs of nearby neurons (see Kohen, Cohn 2011 andDoiron, et al. 2016 for reviews), it likely influences population coding of sensory information (Abbott and Dayan 1999; Averbeck, Latham, and Pouget 2006;Shadlen and Newsome 1998).With advances in recording techniques, it has become increasingly obvious that singleneuron variability reflects fluctuations that are shared across large regions of cortex (Lin et al. 2015;Okun et al. 2015;Scholvinck et al. 2015). That is, sensory input interacts with intrinsic cortical activity, with global cortical fluctuations influencing single-neuron responses. Appropriately, a recent study has introduced the term "population coupling" to describe this relationship . This and other studies have shown that While spike-based studies have yielded many important insights, this approach has two inherent shortcomings. First, it excludes the vast majority neurons, which are sparse-spiking (Henze et al. 2015;O'Connor et al. 2010;Shoham, O'Connor, and Segev 2006;Thompson and Best 1989) and therefore yield unreliable statistics for the analysis of correlated variability(Cohen and Kohn 2011) (Figure 1a, b). Second, it involves sampling populations of neurons that are visible to the experimentalist, but which may not represent relevant or complete cortical microcircuits. Patch clamp recordings of synaptic inputs represent one solution to these two problems (Shoham, O'Connor, and Segev 2006). First, when the recorded neuron is viewed as a component member of the network, the subthreshold inputs provide a measure of activity that is agnostic to output spike rate. A second perspective, motivated by anatomical connectivity, recognizes th...