A Biophysical Model of Nonquantal Transmission at the Vestibular Hair Cell-Calyx Synapse: KLV currents Modulate Fast Electrical and Slow K+ potentials in the Synaptic Cleft

Vestibular hair cells transmit information about head position and motion across synapses to primary afferent neurons. At some of these synapses, the afferent neuron envelopes the hair cell, forming an enlarged synaptic terminal referred to as a calyx. The vestibular hair cell-calyx synapse supports nonquantal transmission (NQT), a neurotransmitter-independent mechanism that is exceptionally fast. The underlying biophysical mechanisms that give rise to NQT are not fully understood. Here we present a computational model of NQT that integrates morphological and electrophysiological data. The model predicts that NQT involves two processes: changes in cleft K+ concentration, as previously recognized, and very fast changes in cleft electrical potential. A significant finding is that changes in cleft electrical potential are faster than changes in [K+] or quantal transmission. The electrical potential mechanism thus provides a basis for the exceptional speed of neurotransmission between type I hair cells and primary neurons and explains experimental observations of fast postsynaptic currents. The [K+] mechanism increases the gain of NQT. Both processes are mediated by current flow through low-voltage-activated K+ (KLV) channels located in both pre-synaptic (hair cell) and post-synaptic (calyx inner face) membranes. The model further demonstrates that the calyx morphology is necessary for NQT; as calyx height is increased, NQT increases in size, speed and efficacy at depolarizing the afferent neuron. We propose that the calyx evolved to enhance NQT and speed up signals that drive vestibular reflexes essential for stabilizing the eyes and neck and maintaining balance during rapid and complex head motions.

Pathophysiology of neuropathic pain

Background: Neuropathic pain is notoriously difficult to manage properly, not only because of its varied nature and the absence of objective diagnostic tools but also because of extensive reciprocal neuronal interactive pathogenic mechanism from the molecular level to patient’s own psychophysical characteristics. This paper briefly reviews the pathophysiology of neuropathic pain to the level of clinicians’ interest and its potential in clinical practiceCurrent Concepts: Recent research progress now allows us to obtain a bird view of neuropathic pain pathophysiology: peripheral and central sensitization. For peripheral sensitization, a local inflammatory milieu of the injured nerve primarily drives sequential phenotypic changes, which are critical and shared by both neuropathic and inflammatory pain. Central sensitization is led either by the hyperexcitability of the second-order afferent neuron itself or loss of physiological inhibitory control of the transmission of pain signal to the higher nervous system. Peripheral and central sensitization work synergistically but can also introduce neuropathic pain alone.Discussion and Conclusion: The cause of neuropathic pain is diverse, and understanding of its pathophysiology is still insufficient to realize a mechanism-based approach to clinical phenotypes or therapeutic applications. In dealing with chronic neuropathic pain, it is highly desirable to assess key aspects of a patient’s pain based on a plausible mechanism and select the best management method accordingly.

Different Sensitivity of action potential generation to the rate of depolarization in vagal afferent A-fiber versus C-fiber neurons

The vagal afferent nerves innervate the visceral organs and convey sensory information from the internal environment to the central nervous system. A better understanding of the mechanisms controlling the activation of vagal afferent neurons bears physiological and pathological significance. Although it is generally believed that the magnitude and the rising rate of membrane depolarization are both critical for the action potential generation, no direct or quantitative evidence has been documented so far for the sensitivity of vagal afferent neuron activation to the rate of depolarization and for its underlying ionic mechanisms. Here, by measuring the response of mouse nodose neurons to the suprathreshold current stimuli of varying rising rates, the slowest depolarization capable of evoking action potentials, the rate-of-depolarization threshold (dV/dtthreshold), was determined and found to be ~20 fold higher in the A-fiber neurons compared to the C-fiber neurons classified based on the capsaicin responsiveness and characteristics of action potential waveforms. Moreover, although the dV/dtthreshold varied substantially among individual neurons it was not different in any one neuron in response to different intensities of current stimuli. Finally, inhibition of low-threshold activated D-type potassium current (IK.D) by α-dendrotoxin or low concentration of 4-aminopyrydine nearly abrogated the sensitivity of action potential generation to the depolarization rate. Thus, the depolarization rate is an important independent factor contributing to the control of action potential discharge, which is particularly effective in the vagal afferent A-fiber neurons. The IK.D channel may regulate the excitability of vagal sensory neurons by setting the dV/dtthreshold for action potential discharge.

Lamellar cells in Pacinian and Meissner corpuscles are touch sensors

The skin covering the human palm and other specialized tactile organs contains a high density of mechanosensory corpuscles tuned to detect transient pressure and vibration. These corpuscles comprise a sensory afferent neuron surrounded by lamellar cells. The neuronal afferent is thought to be the mechanical sensor, whereas the function of lamellar cells is unknown. We show that lamellar cells within Meissner and Pacinian corpuscles detect tactile stimuli. We develop a preparation of bill skin from tactile-specialist ducks that permits electrophysiological recordings from lamellar cells and demonstrate that they contain mechanically gated ion channels. We show that lamellar cells from Meissner corpuscles generate mechanically evoked action potentials using R-type voltage-gated calcium channels. These findings provide the first evidence for R-type channel-dependent action potentials in non-neuronal cells and demonstrate that lamellar cells actively detect touch. We propose that Meissner and Pacinian corpuscles use neuronal and non-neuronal mechanoreception to detect mechanical signals.

Lamellar cells in Pacinian and Meissner corpuscles are touch sensors

The skin covering the human palm and other specialized tactile organs contains a high density of mechanosensory corpuscles tuned to detect transient pressure and vibration. These corpuscles comprise a sensory afferent neuron surrounded by lamellar cells1-3. The neuronal afferent is thought to be the mechanical sensor within the corpuscle, whereas the function of lamellar cells is unknown2,4,5. Here we show that lamellar cells within Meissner and Pacinian corpuscles detect tactile stimuli. We develop a preparation of bill skin from tactile-specialist ducks that permits electrophysiological recordings from lamellar cells and demonstrate that they contain mechanically-gated ion channels. We also show that lamellar cells from Meissner corpuscles generate mechanically-evoked action potentials using R-type voltage-gated calcium channels. These findings provide the first evidence for R-type channel-dependent action potentials in non-neuronal cells and demonstrate that lamellar cells are active detectors of touch. We propose that Meissner and Pacinian corpuscles use both neuronal and non-neuronal mechanoreception to detect mechanical signals.

Ghrelin signaling regulates feeding behavior, metabolism, and memory through the vagus nerve

ABSTRACTVagal afferent neuron (VAN) signaling sends information from the gut to the brain and is fundamental in the neural control of feeding behavior and metabolism. Recent findings reveal that VAN signaling also plays a critical role in cognitive processes, including hippocampus (HPC)-dependent memory. VANs, located in nodose ganglia, express receptors for various gut-derived endocrine signals, however, the function of these receptors with regards to feeding behavior, metabolism, and memory control is poorly understood. We hypothesized that VAN-mediated processes are influenced by ghrelin, a stomach-derived orexigenic hormone, via communication to its receptor (growth hormone secretagogue receptor [GHSR]) expressed on gut-innervating VANs. To examine this hypothesis, rats received nodose ganglia injections of an adeno-associated virus (AAV) expressing short hairpin RNAs targeting GHSR (or a control AAV) for RNA interference-mediated VAN-specific GHSR knockdown. Results reveal that VAN GHSR knockdown induced various feeding and metabolic disturbances, including increased meal frequency, impaired glucose tolerance, delayed gastric emptying, and increased body weight compared to controls. Additionally, VAN-specific GHSR knockdown impaired HPC-dependent episodic contextual memory and reduced HPC brain-derived neurotrophic factor expression, but did not affect anxiety-like behavior or levels of general activity. A functional role for endogenous VAN GHSR signaling was further confirmed by results revealing that VAN signaling is required for the hyperphagic effects of ghrelin administered at dark onset, and that gut-restricted ghrelin-induced increases in VAN firing rate require intact VAN GHSR expression. Collective results reveal that VAN GHSR signaling is required for both normal feeding and metabolic function as well as HPC-dependent memory.

A Bayesian Generative Model of Vestibular Afferent Neuron Spiking

Using an information criterion to evaluate models fitted to spike train data from chinchilla semicircular canal afferent neurons, we found that the superficially complex functional organization of the canal nerve branch can be accurately quantified in an elegant mathematical model with only three free parameters. Spontaneous spike trains are samples from stationary renewal processes whose interval distributions are Exwald distributions, convolutions of Inverse Gaussian and Exponential distributions. We show that a neuronal membrane compartment is a natural computer for calculating parameter likelihoods given samples from a point process with such a distribution, which may facilitate fast, accurate, efficient Bayesian neural computation for estimating the kinematic state of the head. The model suggests that Bayesian neural computation is an aspect of a more general principle that has driven the evolution of nervous system design, the energy efficiency of biological information processing.Significance StatementNervous systems ought to have evolved to be Bayesian, because Bayesian inference allows statistically optimal evidence-based decisions and actions. A variety of circumstantial evidence suggests that animal nervous systems are indeed capable of Bayesian inference, but it is unclear how they could do this. We have identified a simple, accurate generative model of vestibular semicircular canal afferent neuron spike trains. If the brain is a Bayesian observer and a Bayes-optimal decision maker, then the initial stage of processing vestibular information must be to compute the posterior density of head kinematic state given sense data of this form. The model suggests how neurons could do this. Head kinematic state estimation given point-process inertial data is a well-defined dynamical inference problem whose solution formed a foundation for vertebrate brain evolution. The new model provides a foundation for developing realistic, testable spiking neuron models of dynamical state estimation in the vestibulo-cerebellum, and other parts of the Bayesian brain.