Spontaneous voltage oscillations and response dynamics of a Hodgkin-Huxley type model of sensory hair cells

Abstract

We employ a Hodgkin-Huxley-type model of basolateral ionic currents in bullfrog saccular hair cells for studying the genesis of spontaneous voltage oscillations and their role in shaping the response of the hair cell to external mechanical stimuli. Consistent with recent experimental reports, we find that the spontaneous dynamics of the model can be categorized using conductance parameters of calcium-activated potassium, inward rectifier potassium, and mechano-electrical transduction (MET) ionic currents. The model is demonstrated for exhibiting a broad spectrum of autonomous rhythmic activity, including periodic and quasi-periodic oscillations with two independent frequencies as well as various regular and chaotic bursting patterns. Complex patterns of spontaneous oscillations in the model emerge at small values of the conductance of Ca2+-activated potassium currents. These patterns are significantly affected by thermal fluctuations of the MET current. We show that self-sustained regular voltage oscillations lead to enhanced and sharply tuned sensitivity of the hair cell to weak mechanical periodic stimuli. While regimes of chaotic oscillations are argued to result in poor tuning to sinusoidal driving, chaotically oscillating cells do provide a high sensitivity to low-frequency variations of external stimuli.

Noise-induced chaos and signal detection by the nonisochronous Hopf oscillator

“…2 However, there is some evidence that the sensitivity to initial conditions that characterizes chaotic systems could be helpful for weak-signal detection. [3][4][5] In the current work, we demonstrate analytically that the instabilities which give rise to chaotic dynamics in the Hopf oscillator are responsible for enhanced temporal resolution and sensitivity to weak signals.…”

Tracking of Arbitrary Regimes for Spiking and Bursting in the Hodgkin-Huxley Neuron

“…For the extension of our approach to multi-neuron networks with an arbitrary topologySG and TA algorithms for the control of spiking in the network models should consider also the detailed mechanisms of synaptic transmission , spontaneous voltage oscillations (Neiman, et al, 2011) and different roles of neurons in controlling population (Bandopadhayay & Stiles, 2017). Their applications for the modeling of neural populations will provide:  An efficient tool for studying the mechanisms of spiking and bursting in biological neuronal networks;  A theoretical background for practical realization of real-time control in biological neuronal networks.…”

Effect of Voltage Oscillations on Response Properties in a Model of Sensory Hair Cell

“…where I K1 is the inwardly rectifier potassium (K) current, I BKS and I BKT are Ca-activated steady and transient K currents, I h is sodium / potassium h-type current, I DRK is the direct rectifier K current and (2) is accompanied by equations for kinetics of ionic currents listed and for intracellular [Ca 2+ ], totaling 12 differential equations. The detailed description of this system and parameters is provided in [34]. The control parameters of the electrical compartment are the maximal conductance of inwardly rectifier current, g K1 , and relative strength of Ca-activated currents, b K .…”