Resonance in neocortical neurons and networks

Abstract

Neocortical networks produce oscillations that often correspond to characteristic physiological or pathological patterns. However, the mechanisms underlying the generation of and the transitions between such oscillatory states remain poorly understood. In this study, we examined resonance in mouse layer V neocortical pyramidal neurons. To accomplish this, we employed standard electrophysiology to describe cellular resonance parameters. Bode plot analysis revealed a range of resonance magnitude values in layer V neurons and demonstrated that both magnitude and phase response characteristics of layer V neocortical pyramidal neurons are modulated by changes in the extracellular environment. Specifically, increased resonant frequencies and total inductive areas were observed at higher extracellular potassium concentrations and more hyperpolarised membrane potentials. Experiments using pharmacological agents suggested that current through hyperpolarization-activated cyclic nucleotide-gated channels (Ih) acts as the primary driver of resonance in these neurons, with other potassium currents, such as A-type potassium current and delayed-rectifier potassium current (Kv1.4 and Kv1.1, respectively), contributing auxiliary roles. The persistent sodium current was also shown to play a role in amplifying the magnitude of resonance without contributing significantly to the phase response. Although resonance effects in individual neurons are small, their properties embedded in large networks may significantly affect network behavior and may have potential implications for pathological processes. We examined resonance properties in mouse layer V neocortical pyramidal neurons. Our findings suggested that current through hyperpolarization-activated cyclic nucleotide-gated channels (HCN channels, Ih current) acts as the primary driver of resonance with other potassium currents contributing auxiliary roles. Although cellular resonance effects are small, their properties embedded in large networks may significantly affect network behavior and may have implications for pathological processes. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.