Single-cell membrane potential fluctuations evince network scale-freeness and quasicriticality

Abstract

What information single neurons receive about general neural circuit activity is a fundamental question for neuroscience. Somatic membrane potential (Vm) fluctuations are driven by the convergence of synaptic inputs from a diverse cross-section of upstream neurons. Furthermore, neural activity is often scale-free, implying that some measurements should be the same, whether taken at large or small scales. Together, convergence and scale-freeness support the hypothesis that single Vm recordings carry useful information about high-dimensional cortical activity. Conveniently, the theory of “critical branching networks” (one purported explanation for scale-freeness) provides testable predictions about scale-free measurements that are readily applied to Vm fluctuations. To investigate, we obtained whole-cell current-clamp recordings of pyramidal neurons in visual cortex of turtles with unknown genders. We isolated fluctuations in Vm below the firing threshold and analyzed them by adapting the definition of “neuronal avalanches” (i.e., spurts of population spiking). The Vm fluctuations which we analyzed were scale-free and consistent with critical branching. These findings recapitulated results from large-scale cortical population data obtained separately in complementary experiments using microelectrode arrays described previously (Shew et al., 2015). Simultaneously recorded single-unit local field potential did not provide a good match, demonstrating the specific utility of Vm. Modeling shows that estimation of dynamical network properties from neuronal inputs is most accurate when networks are structured as critical branching networks. In conclusion, these findings extend evidence of critical phenomena while also establishing subthreshold pyramidal neuron Vm fluctuations as an informative gauge of high-dimensional cortical population activity.