Dynamical instability determines the effect of ongoing noise on neural firing

A Model of Electrically Stimulated Auditory Nerve Fiber Responses with Peripheral and Central Sites of Spike Generation

A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike. A single ANF is modeled as a network of two exponential integrate-and-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects of facilitation, accommodation, refractoriness, and spike-rate adaptation in ANF. Although the model is parameterized using data for either single or paired pulse stimulation with monophasic rectangular pulses, it correctly predicts effects of various stimulus pulse shapes, stimulation pulse rates, and level on the neural response statistics. The model may serve as a framework to explore the effects of different stimulus parameters on psychophysical performance measured in cochlear implant listeners.

A biophysical model examining the role of low-voltage-activated potassium currents in shaping the responses of vestibular ganglion neurons

The vestibular nerve is characterized by two broad groups of neurons that differ in the timing of their interspike intervals; some fire at highly regular intervals, whereas others fire at highly irregular intervals. Heterogeneity in ion channel properties has been proposed as shaping these firing patterns (Highstein SM, Politoff AL. Brain Res 150: 182-187, 1978; Smith CE, Goldberg JM. Biol Cybern 54: 41-51, 1986). Kalluri et al. (J Neurophysiol 104: 2034-2051, 2010) proposed that regularity is controlled by the density of low-voltage-activated potassium currents (IKL). To examine the impact of IKL on spike timing regularity, we implemented a single-compartment model with three conductances known to be present in the vestibular ganglion: transient sodium (gNa), low-voltage-activated potassium (gKL), and high-voltage-activated potassium (gKH). Consistent with in vitro observations, removing gKL depolarized resting potential, increased input resistance and membrane time constant, and converted current step-evoked firing patterns from transient (1 spike at current onset) to sustained (many spikes). Modeled neurons were driven with a time-varying synaptic conductance that captured the random arrival times and amplitudes of glutamate-driven synaptic events. In the presence of gKL, spiking occurred only in response to large events with fast onsets. Models without gKL exhibited greater integration by responding to the superposition of rapidly arriving events. Three synaptic conductance were modeled, each with different kinetics to represent a variety of different synaptic processes. In response to all three types of synaptic conductance, models containing gKL produced spike trains with irregular interspike intervals. Only models lacking gKL when driven by rapidly arriving small excitatory postsynaptic currents were capable of generating regular spiking.

A point process framework for modeling electrical stimulation of the auditory nerve

Model-based studies of responses of auditory nerve fibers to electrical stimulation can provide insight into the functioning of cochlear implants. Ideally, these studies can identify limitations in sound processing strategies and lead to improved methods for providing sound information to cochlear implant users. To accomplish this, models must accurately describe spiking activity while avoiding excessive complexity that would preclude large-scale simulations of populations of auditory nerve fibers and obscure insight into the mechanisms that influence neural encoding of sound information. In this spirit, we develop a point process model of individual auditory nerve fibers that provides a compact and accurate description of neural responses to electric stimulation. Inspired by the framework of generalized linear models, the proposed model consists of a cascade of linear and nonlinear stages. We show how each of these stages can be associated with biophysical mechanisms and related to models of neuronal dynamics. Moreover, we derive a semianalytical procedure that uniquely determines each parameter in the model on the basis of fundamental statistics from recordings of single fiber responses to electric stimulation, including threshold, relative spread, jitter, and chronaxie. The model also accounts for refractory and summation effects that influence the responses of auditory nerve fibers to high pulse rate stimulation. Throughout, we compare model predictions to published physiological data of response to high and low pulse rate stimulation. We find that the model, although constructed to fit data from single and paired pulse experiments, can accurately predict responses to unmodulated and modulated pulse train stimuli. We close by performing an ideal observer analysis of simulated spike trains in response to sinusoidally amplitude modulated stimuli and find that carrier pulse rate does not affect modulation detection thresholds.

Bistability and resonance in the periodically stimulated Hodgkin-Huxley model with noise

We describe general characteristics of the Hodgkin-Huxley neuron's response to a periodic train of short current pulses with Gaussian noise. The deterministic neuron is bistable for antiresonant frequencies. When the stimuli arrive at the resonant frequency the firing rate is a continuous function of the current amplitude I(0) and scales as (I(0)-I(th))(1/2), characteristic of a saddle-node bifurcation at the threshold I(th). Intervals of continuous irregular response alternate with integer mode-locked regions with bistable excitation edge. There is an even-all multimodal transition between the 2 : 1 and 3 : 1 states in the vicinity of the main resonance, which is analogous to the odd-all transition discovered earlier in the high-frequency regime. For I(0)<I(th) and small noise the firing rate has a maximum at the resonant frequency. For larger noise and subthreshold stimulation the maximum firing rate initially shifts toward lower frequencies, then returns to higher frequencies in the limit of large noise. The stochastic coherence antiresonance, defined as a simultaneous occurrence of (i) the maximum of the coefficient of variation and (ii) the minimum of the firing rate vs the noise intensity, occurs over a wide range of parameter values, including monostable regions. Results of this work can be verified experimentally.

Noise enhances subthreshold oscillations in injured primary sensory neurons

Noise can play a constructive role in the detection of weak signals in various kinds of peripheral receptors and neurons. What the mechanism underlying the effect of noise is remains unclear. Here, the perforated patch-clamp technique was used on isolated cells from chronic compression of the dorsal root ganglion (DRG) model. Our data provided new insight indicating that, under conditions without external signals, noise can enhance subthreshold oscillations, which was observed in a certain type of neurons with high-frequency (20-100 Hz) intrinsic resonance from injured DRG neurons. The occurrence of subthreshold oscillation considerably decreased the threshold potential for generating repetitive firing. The above effects of noise can be abolished by blocking the persistent sodium current (I(Na, P)). Utilizing a mathematical neuron model we further simulated the effect of noise on subthreshold oscillation and firing, and also found that noise can enhance the electrical activity through autonomous stochastic resonance. Accordingly, we propose a new concept of the effects of noise on neural intrinsic activity, which suggests that noise may be an important factor for modulating the excitability of neurons and generation of chronic pain signals.

Auditory sensitivity may require dynamically unstable spike generators: evidence from a model of electrical stimulation

The response of the auditory nerve to electrical stimulation is highly sensitive to small modulations (<0.5%). This report demonstrates that dynamical instability (i.e., a positive Lyapunov exponent) can account for this sensitivity in a modified FitzHugh-Nagumo model of spike generation, so long as the input noise is not too large. This finding suggests both that spike generator instability is necessary to account for auditory nerve sensitivity and that the amplitude of physiological noise, such as that produced by the random behavior of voltage-gated sodium channels, is small. Based on these results with direct electrical stimulation, it is hypothesized that spike generator instability may be the mechanism that reconciles high sensitivity with the cross-fiber independence observed under acoustic stimulation.

Enhancement of neural stochastic firing in cochlear implant stimulation by the addition of noise: a computational study of the influence of stimulation settings and spontaneous activity

It is known that, in cochlear implants (CIs), the addition of noise to CI stimuli may enhance the stochastic firing in the auditory nerve (AN). The aim of this study was to investigate, by using a model of a fiber of the AN the influence of CI stimulation settings (i.e., stimulation rate and stimulus magnitude) and fiber spontaneous activity on the enhancement of stochastic firing when CI stimuli are combined with noise. Results showed that the stimulation rate had an effect on the enhancement of stochastic firing in the AN, whereas the stimulus magnitude and the spontaneous firing rate had no influence.