Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Understanding single neuron information processing is key to deciphering neural circuit activity.
• Neural activity often exhibits scale-free properties, suggesting self-similarity across scales.
• Somatic membrane potential (Vm) fluctuations integrate synaptic inputs, potentially reflecting network states.

Purpose of the Study:

• To investigate if subthreshold Vm fluctuations in single neurons contain information about high-dimensional cortical activity.
• To test the hypothesis that Vm fluctuations exhibit scale-free properties consistent with critical branching networks.
• To compare Vm fluctuation statistics with population-level neural activity measures.

Main Methods:

• Whole-cell current-clamp recordings from pyramidal neurons in turtle visual cortex.
• Analysis of subthreshold Vm fluctuations using adapted "neuronal avalanche" definitions.
• Comparison of Vm fluctuation statistics with simultaneously recorded local field potentials and previously published microelectrode array data.

Main Results:

• Subthreshold Vm fluctuations were found to be scale-free and consistent with critical branching.
• These Vm fluctuation statistics recapitulated findings from large-scale cortical population data.
• Simultaneously recorded local field potentials did not match population activity statistics as well as Vm fluctuations.
• Modeling indicated that critical branching networks optimize the estimation of network properties from neuronal inputs.

Conclusions:

• Subthreshold Vm fluctuations serve as an informative gauge of high-dimensional cortical population activity.
• The findings extend evidence for critical phenomena in neural systems to the microscale (Vm fluctuations).
• Single neurons, through synaptic convergence, effectively subsample network activity in a manner consistent with critical dynamics.