A model of synaptic vesicle-pool depletion and replenishment can account for the interspike interval distributions and nonrenewal properties of spontaneous spike trains of auditory-nerve fibers

Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA (over hundreds of seconds) with a single neuronal population, and, crucially, with vesicle depletion as one of the key mechanisms behind the ERNA frequency decay in our model. We further validate the proposed model against experimental data from Parkinson's disease patients, where it captures the variations in ERNA frequency and amplitude in response to variable stimulation frequency, amplitude, and to stimulation pulse bursting. We provide a series of predictions from the model that could be the subject of future studies for further validation.

Predicting early auditory evoked potentials using a computational model of auditory-nerve processing

Non-invasive electrophysiological measures, such as auditory evoked potentials (AEPs), play a crucial role in diagnosing auditory pathology. However, the relationship between AEP morphology and cochlear degeneration remains complex and not well understood. Dau [J. Acoust. Soc. Am. 113, 936-950 (2003)] proposed a computational framework for modeling AEPs that utilized a nonlinear auditory-nerve (AN) model followed by a linear unitary response function. While the model captured some important features of the measured AEPs, it also exhibited several discrepancies in response patterns compared to the actual measurements. In this study, an enhanced AEP modeling framework is presented, incorporating an improved AN model, and the conclusions from the original study were reevaluated. Simulation results with transient and sustained stimuli demonstrated accurate auditory brainstem responses (ABRs) and frequency-following responses (FFRs) as a function of stimulation level, although wave-V latencies remained too short, similar to the original study. When compared to physiological responses in animals, the revised model framework showed a more accurate balance between the contributions of auditory-nerve fibers (ANFs) at on- and off-frequency regions to the predicted FFRs. These findings emphasize the importance of cochlear processing in brainstem potentials. This framework may provide a valuable tool for assessing human AN models and simulating AEPs for various subtypes of peripheral pathologies, offering opportunities for research and clinical applications.

From the outer ear to the nerve: A complete computer model of the peripheral auditory system

Computer models of the individual components of the peripheral auditory system - the outer, middle, and inner ears and the auditory nerve - have been developed in the past, with varying level of detail, breadth, and faithfulness of the underlying parameters. Building on previous work, we advance the modeling of the ear by presenting a complete, physiologically justified, bottom-up computer model based on up-to-date experimental data that integrates all of these parts together seamlessly. The detailed bottom-up design of the present model allows for the investigation of partial hearing mechanisms and their defects, including genetic, molecular, and microscopic factors. Also, thanks to the completeness of the model, one can study microscopic effects in the context of their implications on hearing as a whole, enabling the correlation with neural recordings and non-invasive psychoacoustic methods. Such a model is instrumental for advancing quantitative understanding of the mechanism of hearing, for investigating various forms of hearing impairment, as well as for devising next generation hearing aids and cochlear implants.

Evidence That Ultrafast Nonquantal Transmission Underlies Synchronized Vestibular Action Potential Generation

Amniotes evolved a unique postsynaptic terminal in the inner ear vestibular organs called the calyx that receives both quantal and nonquantal (NQ) synaptic inputs from Type I sensory hair cells. The nonquantal synaptic current includes an ultrafast component that has been hypothesized to underlie the exceptionally high synchronization index (vector strength) of vestibular afferent neurons in response to sound and vibration. Here, we present three lines of evidence supporting the hypothesis that nonquantal transmission is responsible for synchronized vestibular action potentials of short latency in the guinea pig utricle of either sex. First, synchronized vestibular nerve responses are unchanged after administration of the AMPA receptor antagonist CNQX, while auditory nerve responses are completely abolished. Second, stimulus evoked vestibular nerve compound action potentials (vCAP) are shown to occur without measurable synaptic delay and three times shorter than the latency of auditory nerve compound action potentials (cCAP), relative to the generation of extracellular receptor potentials. Third, paired-pulse stimuli designed to deplete the readily releasable pool (RRP) of synaptic vesicles in hair cells reveal forward masking in guinea pig auditory cCAPs, but a complete lack of forward masking in vestibular vCAPs. Results support the conclusion that the fast component of nonquantal transmission at calyceal synapses is indefatigable and responsible for ultrafast responses of vestibular organs evoked by transient stimuli.SIGNIFICANCE STATEMENT The mammalian vestibular system drives some of the fastest reflex pathways in the nervous system, ensuring stable gaze and postural control for locomotion on land. To achieve this, terrestrial amniotes evolved a large, unique calyx afferent terminal which completely envelopes one or more presynaptic vestibular hair cells, which transmits mechanosensory signals mediated by quantal and nonquantal (NQ) synaptic transmission. We present several lines of evidence in the guinea pig which reveals the most sensitive vestibular afferents are remarkably fast, much faster than their auditory nerve counterparts. Here, we present neurophysiological and pharmacological evidence that demonstrates this vestibular speed advantage arises from ultrafast NQ electrical synaptic transmission from Type I hair cells to their calyx partners.

A Modelling Study on the Comparison of Predicted Auditory Nerve Firing Rates for the Personalized Indication of Cochlear Implantation

The decision of whether to perform cochlear implantation is crucial because implantation cannot be reversed without harm. The aim of the study was to compare model-predicted time–place representations of auditory nerve (AN) firing rates for normal hearing and impaired hearing with a view towards personalized indication of cochlear implantation. AN firing rates of 1024 virtual subjects with a wide variety of different types and degrees of hearing impairment were predicted. A normal hearing reference was compared to four hearing prosthesis options, which were unaided hearing, sole acoustic amplification, sole electrical stimulation, and a combination of the latter two. The comparisons and the fitting of the prostheses were based on a ‘loss of action potentials’ (LAP) score. Single-parameter threshold analysis suggested that cochlear implantation is indicated when more than approximately two-thirds of the inner hair cells (IHCs) are damaged. Second, cochlear implantation is also indicated when more than an average of approximately 12 synapses per IHC are damaged due to cochlear synaptopathy (CS). Cochlear gain loss (CGL) appeared to shift these thresholds only slightly. Finally, a support vector machine predicted the indication of a cochlear implantation from hearing loss parameters with a 10-fold cross-validated accuracy of 99.2%.

Optogenetics and electron tomography for structure-function analysis of cochlear ribbon synapses

Ribbon synapses of cochlear inner hair cells (IHCs) are specialized to indefatigably transmit sound information at high rates. To understand the underlying mechanisms, structure-function analysis of the active zone (AZ) of these synapses is essential. Previous electron microscopy studies of synaptic vesicle (SV) dynamics at the IHC AZ used potassium stimulation, which limited the temporal resolution to minutes. Here, we established optogenetic IHC stimulation followed by quick freezing within milliseconds and electron tomography to study the ultrastructure of functional synapse states with good temporal resolution in mice. We characterized optogenetic IHC stimulation by patch-clamp recordings from IHCs and postsynaptic boutons revealing robust IHC depolarization and neurotransmitter release. Ultrastructurally, the number of docked SVs increased upon short (17-25 ms) and long (48-76 ms) light stimulation paradigms. We did not observe enlarged SVs or other morphological correlates of homotypic fusion events. Our results indicate a rapid recruitment of SVs to the docked state upon stimulation and suggest that univesicular release prevails as the quantal mechanism of exocytosis at IHC ribbon synapses.

Interspike interval correlations in neuron models with adaptation and correlated noise

The generation of neural action potentials (spikes) is random but nevertheless may result in a rich statistical structure of the spike sequence. In particular, contrary to the popular renewal assumption of theoreticians, the intervals between adjacent spikes are often correlated. Experimentally, different patterns of interspike-interval correlations have been observed and computational studies have identified spike-frequency adaptation and correlated noise as the two main mechanisms that can lead to such correlations. Analytical studies have focused on the single cases of either correlated (colored) noise or adaptation currents in combination with uncorrelated (white) noise. For low-pass filtered noise or adaptation, the serial correlation coefficient can be approximated as a single geometric sequence of the lag between the intervals, providing an explanation for some of the experimentally observed patterns. Here we address the problem of interval correlations for a widely used class of models, multidimensional integrate-and-fire neurons subject to a combination of colored and white noise sources and a spike-triggered adaptation current. Assuming weak noise, we derive a simple formula for the serial correlation coefficient, a sum of two geometric sequences, which accounts for a large class of correlation patterns. The theory is confirmed by means of numerical simulations in a number of special cases including the leaky, quadratic, and generalized integrate-and-fire models with colored noise and spike-frequency adaptation. Furthermore we study the case in which the adaptation current and the colored noise share the same time scale, corresponding to a slow stochastic population of adaptation channels; we demonstrate that our theory can account for a nonmonotonic dependence of the correlation coefficient on the channel's time scale. Another application of the theory is a neuron driven by network-noise-like fluctuations (green noise). We also discuss the range of validity of our weak-noise theory and show that by changing the relative strength of white and colored noise sources, we can change the sign of the correlation coefficient. Finally, we apply our theory to a conductance-based model which demonstrates its broad applicability.

Resolution of subcomponents of synaptic release from postsynaptic currents in rat hair-cell/auditory-nerve fiber synapses

The synapse between inner hair cells and auditory nerve fiber dendrites shows large excitatory postsynaptic currents (EPSCs), which are either monophasic or multiphasic. Multiquantal or uniquantal (flickering) release of neurotransmitter has been proposed to underlie the unusual multiphasic waveforms. Here the nature of multiphasic waveforms is analyzed using EPSCs recorded in vitro in rat afferent dendrites. Spontaneous EPSCs were deconvolved into a sum of presumed release events having monophasic EPSC waveforms. Results include, first, the charge of EPSCs is about the same for multiphasic versus monophasic EPSCs. Second, EPSC amplitudes decline with the number of release events per EPSC. Third, there is no evidence of a mini-EPSC. Most results can be accounted for by versions of either uniquantal or multiquantal release. However, serial neurotransmitter release in multiphasic EPSCs shows properties that are not fully explained by either model, especially that the amplitudes of individual release events are established at the beginning of a multiphasic EPSC, constraining possible models of vesicle release.NEW & NOTEWORTHY How do monophasic and multiphasic waveshapes arise in auditory-nerve dendrites; mainly are they uniquantal, arising from release of a single vesicle, or multiquantal, requiring several vesicles? The charge injected by excitatory postsynaptic currents (EPSCs) is the same for monophasic or multiphasic EPSCs, supporting uniquantal release. Serial adaptation of responses to sequential EPSCs favors a multiquantal model. Finally, neurotransmitter partitioning into similar sized release boluses occurs at the first bolus in the EPSC, not easily explained with either model.

Encoding sound in the cochlea: from receptor potential to afferent discharge

Ribbon-class synapses in the ear achieve analog to digital transformation of a continuously graded membrane potential to all-or-none spikes. In mammals, several auditory nerve fibres (ANFs) carry information from each inner hair cell (IHC) to the brain in parallel. Heterogeneity of transmission among synapses contributes to the diversity of ANF sound-response properties. In addition to the place code for sound frequency and the rate code for sound level, there is also a temporal code. In series with cochlear amplification and frequency tuning, neural representation of temporal cues over a broad range of sound levels enables auditory comprehension in noisy multi-speaker settings. The IHC membrane time constant introduces a low-pass filter that attenuates fluctuations of the receptor potential above 1-2 kHz. The ANF spike generator adds a high-pass filter via its depolarization-rate threshold that rejects slow changes in the postsynaptic potential and its phasic response property that ensures one spike per depolarization. Synaptic transmission involves several stochastic subcellular processes between IHC depolarization and ANF spike generation, introducing delay and jitter that limits the speed and precision of spike timing. ANFs spike at a preferred phase of periodic sounds in a process called phase-locking that is limited to frequencies below a few kilohertz by both the IHC receptor potential and the jitter in synaptic transmission. During phase-locking to periodic sounds of increasing intensity, faster and facilitated activation of synaptic transmission and spike generation may be offset by presynaptic depletion of synaptic vesicles, resulting in relatively small changes in response phase. Here we review encoding of spike-timing at cochlear ribbon synapses.

A numerical method for computing interval distributions for an inhomogeneous Poisson point process modified by random dead times

The inhomogeneous Poisson point process is a common model for time series of discrete, stochastic events. When an event from a point process is detected, it may trigger a random dead time in the detector, during which subsequent events will fail to be detected. It can be difficult or impossible to obtain a closed-form expression for the distribution of intervals between detections, even when the rate function (often referred to as the intensity function) and the dead-time distribution are given. Here, a method is presented to numerically compute the interval distribution expected for any arbitrary inhomogeneous Poisson point process modified by dead times drawn from any arbitrary distribution. In neuroscience, such a point process is used to model trains of neuronal spikes triggered by the detection of excitatory events while the neuron is not refractory. The assumptions of the method are that the process is observed over a finite observation window and that the detector is not in a dead state at the start of the observation window. Simulations are used to verify the method for several example point processes. The method should be useful for modeling and understanding the relationships between the rate functions and interval distributions of the event and detection processes, and how these relationships depend on the dead-time distribution.

Phase Locking of Auditory Nerve Fibers: The Role of Lowpass Filtering by Hair Cells

Phase locking of auditory-nerve-fiber (ANF) responses to the temporal fine structure of acoustic stimuli, a hallmark of the auditory system's temporal precision, is important for many aspects of hearing. Previous work has shown that phase-locked period histograms are often well described by exponential transfer functions relating instantaneous stimulus pressure to instantaneous spike rate, with no observed clipping of the histograms. The operating points and slopes of these functions change with stimulus level. The mechanism underlying this apparent gain control is unclear but is distinct from mechanical compression, is independent of refractoriness and spike-rate adaptation, and is apparently instantaneous. Here we show that these findings can be accounted for by a model consisting of a static Boltzmann transducer function yielding a clipped output, followed by a lowpass filter and a static exponential transfer function. Using responses to tones of ANFs from cats of both sexes, we show that, for a given ANF, the period histograms obtained at all stimulus levels for a given stimulus frequency can be described using one set of level-independent model parameters. The model also accounts for changes in the maximum and minimum instantaneous spike rates with changes in stimulus level. Notably, the estimated cutoff frequency is lower for low- than for high-spontaneous-rate ANFs, implying a synapse-specific contribution to lowpass filtering. These findings advance our understanding of ANF phase locking by highlighting the role of peripheral filtering mechanisms in shaping responses of individual ANFs.SIGNIFICANCE STATEMENT Phase locking of auditory-nerve-fiber responses to the temporal fine structure of acoustic stimuli is important for many aspects of hearing. Period histograms typically retain an approximately sinusoidal shape across stimulus levels, with the peripheral auditory system operating as though its overall transfer function is an exponential function whose slope decreases with increasing stimulus level. This apparent gain control can be accounted for by a static saturating transducer function followed by a lowpass filter. In addition to attenuating the AC component, the filter approximately recovers the sinusoidal waveform of the stimulus. The estimated cutoff frequency varies with spontaneous rate, revealing a synaptic contribution to lowpass filtering. These findings highlight the significant impact of peripheral filtering mechanisms on phase locking.

Interspike interval correlations in networks of inhibitory integrate-and-fire neurons

We study temporal correlations of interspike intervals, quantified by the network-averaged serial correlation coefficient (SCC), in networks of both current- and conductance-based purely inhibitory integrate-and-fire neurons. Numerical simulations reveal transitions to negative SCCs at intermediate values of bias current drive and network size. As bias drive and network size are increased past these values, the SCC returns to zero. The SCC is maximally negative at an intermediate value of the network oscillation strength. The dependence of the SCC on two canonical schemes for synaptic connectivity is studied, and it is shown that the results occur robustly in both schemes. For conductance-based synapses, the SCC becomes negative at the onset of both a fast and slow coherent network oscillation. We then show by means of offline simulations using prerecorded network activity that a neuron's SCC is highly sensitive to its number of presynaptic inputs. Finally, we devise a noise-reduced diffusion approximation for current-based networks that accounts for the observed temporal correlation transitions.

Phase Locking of Auditory-Nerve Fibers Reveals Stereotyped Distortions and an Exponential Transfer Function with a Level-Dependent Slope

Phase locking of auditory-nerve-fiber (ANF) responses to the fine structure of acoustic stimuli is a hallmark of the auditory system's temporal precision and is important for many aspects of hearing. Period histograms from phase-locked ANF responses to low-frequency tones exhibit spike-rate and temporal asymmetries, but otherwise retain an approximately sinusoidal shape as stimulus level increases, even beyond the level at which the mean spike rate saturates. This is intriguing because apical cochlear mechanical vibrations show little compression, and mechanoelectrical transduction in the receptor cells is thought to obey a static sigmoidal nonlinearity, which might be expected to produce peak clipping at moderate and high stimulus levels. Here we analyze phase-locked responses of ANFs from cats of both sexes. We show that the lack of peak clipping is due neither to ANF refractoriness nor to spike-rate adaptation on time scales longer than the stimulus period. We demonstrate that the relationship between instantaneous pressure and instantaneous rate is well described by an exponential function whose slope decreases with increasing stimulus level. Relatively stereotyped harmonic distortions in the input to the exponential can account for the temporal asymmetry of the period histograms, including peak splitting. We show that the model accounts for published membrane-potential waveforms when assuming a power-of-three, but not a power-of-one, relationship to exocytosis. Finally, we demonstrate the relationship between the exponential transfer functions and the sigmoidal pseudotransducer functions obtained in the literature by plotting the maxima and minima of the voltage responses against the maxima and minima of the stimuli.SIGNIFICANCE STATEMENT Phase locking of auditory-nerve-fiber responses to the temporal fine structure of acoustic stimuli is important for many aspects of hearing, but the mechanisms underlying phase locking are not fully understood. Intriguingly, period histograms retain an approximately sinusoidal shape across sound levels, even when the mean rate has saturated. We find that neither refractoriness nor spike-rate adaptation is responsible for this behavior. Instead, the peripheral auditory system operates as though it contains an exponential transfer function whose slope changes with stimulus level. The underlying mechanism is distinct from the comparatively weak cochlear mechanical compression in the cochlear apex, and likely resides in the receptor cells.

Mathematical Modeling and Analyses of Interspike-Intervals of Spontaneous Activity in Afferent Neurons of the Zebrafish Lateral Line

Without stimuli, hair cells spontaneously release neurotransmitter leading to spontaneous generation of action potentials (spikes) in innervating afferent neurons. We analyzed spontaneous spike patterns recorded from the lateral line of zebrafish and found that distributions of interspike intervals (ISIs) either have an exponential shape or an "L" shape that is characterized by a sharp decay but wide tail. ISI data were fitted to renewal-process models that accounted for the neuron refractory periods and hair-cell synaptic release. Modeling the timing of synaptic release using a mixture of two exponential distributions yielded the best fit for our ISI data. Additionally, lateral line ISIs displayed positive serial correlation and appeared to exhibit switching between faster and slower modes of spike generation. This pattern contrasts with previous findings from the auditory system where ISIs tended to have negative serial correlation due to synaptic depletion. We propose that afferent neuron innervation with multiple and heterogenous hair-cells synapses, each influenced by changes in calcium domains, can serve as a mechanism for the random switching behavior. Overall, our analyses provide evidence of how physiological similarities and differences between synapses and innervation patterns in the auditory, vestibular, and lateral line systems can lead to variations in spontaneous activity.

The effects of the activation of the inner-hair-cell basolateral K+ channels on auditory nerve responses

The basolateral membrane of the mammalian inner hair cell (IHC) expresses large voltage and Ca²⁺ gated outward K⁺ currents. To quantify how the voltage-dependent activation of the K⁺ channels affects the functionality of the auditory nerve innervating the IHC, this study adopts a model of mechanical-to-neural transduction in which the basolateral K⁺ conductances of the IHC can be made voltage-dependent or not. The model shows that the voltage-dependent activation of the K⁺ channels (i) enhances the phase-locking properties of the auditory fiber (AF) responses; (ii) enables the auditory nerve to encode a large dynamic range of sound levels; (iii) enables the AF responses to synchronize precisely with the envelope of amplitude modulated stimuli; and (iv), is responsible for the steep offset responses of the AFs. These results suggest that the basolateral K⁺ channels play a major role in determining the well-known response properties of the AFs and challenge the classical view that describes the IHC membrane as an electrical low-pass filter. In contrast to previous models of the IHC-AF complex, this study ascribes many of the AF response properties to fairly basic mechanisms in the IHC membrane rather than to complex mechanisms in the synapse.

Maturation of Spontaneous Firing Properties after Hearing Onset in Rat Auditory Nerve Fibers: Spontaneous Rates, Refractoriness, and Interfiber Correlations

Auditory nerve fibers (ANFs) exhibit a range of spontaneous firing rates (SRs) that are inversely correlated with threshold for sounds. To probe the underlying mechanisms and time course of SR differentiation during cochlear maturation, loose-patch extracellular recordings were made from ANF dendrites using acutely excised rat cochlear preparations of different ages after hearing onset. Diversification of SRs occurred mostly between the second and the third postnatal week. Statistical properties of ANF spike trains showed developmental changes that approach adult-like features in older preparations. Comparison with intracellularly recorded EPSCs revealed that most properties of ANF spike trains derive from the characteristics of presynaptic transmitter release. Pharmacological tests and waveform analysis showed that endogenous firing produces some fraction of ANF spikes, accounting for their unusual properties; the endogenous firing diminishes gradually during maturation. Paired recordings showed that ANFs contacting the same inner hair cell could have different SRs, with no correlation in their spike timing.

SIGNIFICANCE STATEMENT

The inner hair cell (IHC)/auditory nerve fiber (ANF) synapse is the first synapse of the auditory pathway. Remarkably, each IHC is the sole partner of 10-30 ANFs with a range of spontaneous firing rates (SRs). Low and high SR ANFs respond to sound differently, and both are important for encoding sound information across varying acoustical environments. Here we demonstrate SR diversification after hearing onset by afferent recordings in acutely excised rat cochlear preparations. We describe developmental changes in spike train statistics and endogenous firing in immature ANFs. Dual afferent recordings provide the first direct evidence that fibers with different SRs contact the same IHCs and do not show correlated spike timing at rest. These results lay the groundwork for understanding the differential sensitivity of ANFs to acoustic trauma.

Model-based estimation of the frequency tuning of the inner-hair-cell stereocilia from neural tuning curves

This study proposes that the frequency tuning of the inner-hair-cell (IHC) stereocilia in the intact organ of Corti can be derived from the responses of the auditory fibers (AFs) using computational tools. The frequency-dependent relationship between the AF threshold and the amplitude of the stereocilia vibration is estimated using a model of the IHC-mediated mechanical to neural transduction. Depending on the response properties of the considered AF, the amplitude of stereocilia deflection required to drive the simulated AF above threshold is 1.4 to 9.2 dB smaller at low frequencies (≤500 Hz) than at high frequencies (≥4 kHz). The estimated frequency-dependent relationship between ciliary deflection and neural threshold is employed to derive constant-stereocilia-deflection contours from previously published AF recordings from the chinchilla cochlea. This analysis shows that the transduction process partially accounts for the observed differences between the tuning of the basilar membrane and that of the AFs.

Physiological recordings from the zebrafish lateral line

During sensory transduction, external physical stimuli are translated into an internal biological signal. In vertebrates, hair cells are specialized mechanosensory receptors that transduce sound, gravitational forces, and head movements into electrical signals that are transmitted with remarkable precision and efficiency to afferent neurons. Hair cells have a conserved structure between species and are also found in the lateral line system of fish, including zebrafish, which serve as an ideal animal model to study sensory transmission in vivo. In this chapter, we describe the methods required to investigate the biophysical properties underlying mechanosensation in the lateral line of the zebrafish in vivo from microphonic potentials and single hair cell patch-clamp recordings to single afferent neuron recordings. These techniques provide real-time measurements of hair-cell transduction and transmission following delivery of controlled and defined stimuli and their combined use on the intact zebrafish provides a powerful platform to investigate sensory encoding in vivo.

Disruption of adaptor protein 2μ (AP-2μ) in cochlear hair cells impairs vesicle reloading of synaptic release sites and hearing

Active zones (AZs) of inner hair cells (IHCs) indefatigably release hundreds of vesicles per second, requiring each release site to reload vesicles at tens per second. Here, we report that the endocytic adaptor protein 2μ (AP-2μ) is required for release site replenishment and hearing. We show that hair cell-specific disruption of AP-2μ slows IHC exocytosis immediately after fusion of the readily releasable pool of vesicles, despite normal abundance of membrane-proximal vesicles and intact endocytic membrane retrieval. Sound-driven postsynaptic spiking was reduced in a use-dependent manner, and the altered interspike interval statistics suggested a slowed reloading of release sites. Sustained strong stimulation led to accumulation of endosome-like vacuoles, fewer clathrin-coated endocytic intermediates, and vesicle depletion of the membrane-distal synaptic ribbon in AP-2μ-deficient IHCs, indicating a further role of AP-2μ in clathrin-dependent vesicle reformation on a timescale of many seconds. Finally, we show that AP-2 sorts its IHC-cargo otoferlin. We propose that binding of AP-2 to otoferlin facilitates replenishment of release sites, for example, via speeding AZ clearance of exocytosed material, in addition to a role of AP-2 in synaptic vesicle reformation.

Molecularly and structurally distinct synapses mediate reliable encoding and processing of auditory information

Hearing impairment is the most common human sensory deficit. Considering the sophisticated anatomy and physiology of the auditory system, disease-related failures frequently occur. To meet the demands of the neuronal circuits responsible for processing auditory information, the synapses of the lower auditory pathway are anatomically and functionally specialized to process acoustic information indefatigably with utmost temporal precision. Despite sharing some functional properties, the afferent synapses of the cochlea and of auditory brainstem differ greatly in their morphology and employ distinct molecular mechanisms for regulating synaptic vesicle release. Calyceal synapses of the endbulb of Held and the calyx of Held profit from a large number of release sites that project onto one principal cell. Cochlear inner hair cell ribbon synapses exhibit a unique one-to-one relation of the presynaptic active zone to the postsynaptic cell and use hair-cell-specific proteins such as otoferlin for vesicle release. The understanding of the molecular physiology of the hair cell ribbon synapse has been advanced by human genetics studies of sensorineural hearing impairment, revealing human auditory synaptopathy as a new nosological entity.

Contrasting developmental axon regrowth and neurite sprouting of Drosophila mushroom body neurons reveals shared and unique molecular mechanisms

The molecular mechanisms regulating intrinsic axon growth potential during development or following injury remain largely unknown despite their vast importance. Here, we have established a neurite sprouting assay of primary cultured mushroom body (MB) neurons. We used the MARCM technique to both mark and manipulate MB neurons, enabling us to quantify the sprouting abilities of single WT and mutant neurons originating from flies at different developmental stages. Sprouting of dissociated MB neurons was dependent on wnd, the DLK ortholog, a conserved gene that is required for axon regeneration. Next, and as expected, we found that the sprouting ability of adult MB neurons was significantly decreased. In contrast, and to our surprise, we found that pupal-derived neurons exhibit increased sprouting compared with neurons derived from larvae, suggesting the existence of an elevated growth potential state. We then contrasted the molecular requirements of neurite sprouting to developmental axon regrowth of MB ɣ neurons, a process that we have previously shown requires the nuclear receptor UNF acting via the target of rapamycin (TOR) pathway. Strikingly, we found that while TOR was required for neurite sprouting, UNF was not. In contrast, we found that PTEN inhibits sprouting in adult neurons, suggesting that TOR is regulated by the PI3K/PTEN pathway during sprouting and by UNF during developmental regrowth. Interestingly, the PI3K pathway as well as Wnd were not required for developmental regrowth nor for initial axon outgrowth suggesting that axon growth during circuit formation, remodeling, and regeneration share some molecular components but differ in others.

Statistical structure of neural spiking under non-Poissonian or other non-white stimulation

Nerve cells in the brain generate sequences of action potentials with a complex statistics. Theoretical attempts to understand this statistics were largely limited to the case of a temporally uncorrelated input (Poissonian shot noise) from the neurons in the surrounding network. However, the stimulation from thousands of other neurons has various sorts of temporal structure. Firstly, input spike trains are temporally correlated because their firing rates can carry complex signals and because of cell-intrinsic properties like neural refractoriness, bursting, or adaptation. Secondly, at the connections between neurons, the synapses, usage-dependent changes in the synaptic weight (short-term plasticity) further shape the correlation structure of the effective input to the cell. From the theoretical side, it is poorly understood how these correlated stimuli, so-called colored noise, affect the spike train statistics. In particular, no standard method exists to solve the associated first-passage-time problem for the interspike-interval statistics with an arbitrarily colored noise. Assuming that input fluctuations are weaker than the mean neuronal drive, we derive simple formulas for the essential interspike-interval statistics for a canonical model of a tonically firing neuron subjected to arbitrarily correlated input from the network. We verify our theory by numerical simulations for three paradigmatic situations that lead to input correlations: (i) rate-coded naturalistic stimuli in presynaptic spike trains; (ii) presynaptic refractoriness or bursting; (iii) synaptic short-term plasticity. In all cases, we find severe effects on interval statistics. Our results provide a framework for the interpretation of firing statistics measured in vivo in the brain.

Basic response properties of auditory nerve fibers: a review

All acoustic information from the periphery is encoded in the timing and rates of spikes in the population of spiral ganglion neurons projecting to the central auditory system. Considerable progress has been made in characterizing the physiological properties of type-I and type-II primary auditory afferents and understanding the basic properties of type-I afferents in response to sounds. Here, we review some of these properties, with emphasis placed on issues such as the stochastic nature of spike timing during spontaneous and driven activity, frequency tuning curves, spike-rate-versus-level functions, dynamic-range and spike-rate adaptation, and phase locking to stimulus fine structure and temporal envelope. We also review effects of acoustic trauma on some of these response properties.