Adaptation reduces spike-count reliability, but not spike-timing precision, of auditory nerve responses

Adaptation in auditory processing

Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recurring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by continually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the auditory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adaptation to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.

Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding

Synchronization of neuronal discharges on the millisecond scale has long been recognized as a prevalent and functionally important attribute of neural activity. In this article, I review classical concepts and corresponding evidence of the mechanisms that govern the synchronization of distributed discharges in cortical networks and relate those mechanisms to their possible roles in coding and cognitive functions. To accommodate the need for a selective, directed synchronization of cells, I propose that synchronous firing of distributed neurons is a natural consequence of spike-timing-dependent plasticity (STDP) that associates cells repetitively receiving temporally coherent input: the “synchrony through synaptic plasticity” hypothesis. Neurons that are excited by a repeated sequence of synaptic inputs may learn to selectively respond to the onset of this sequence through synaptic plasticity. Multiple neurons receiving coherent input could thus actively synchronize their firing by learning to selectively respond at corresponding temporal positions. The hypothesis makes several predictions: first, the position of the cells in the network, as well as the source of their input signals, would be irrelevant as long as their input signals arrive simultaneously; second, repeating discharge patterns should get compressed until all or some part of the signals are synchronized; and third, this compression should be accompanied by a sparsening of signals. In this way, selective groups of cells could emerge that would respond to some recurring event with synchronous firing. Such a learned response pattern could further be modulated by synchronous network oscillations that provide a dynamic, flexible context for the synaptic integration of distributed signals. I conclude by suggesting experimental approaches to further test this new hypothesis.

Phase-Locking Requires Efficient Ca2+ Extrusion at the Auditory Hair Cell Ribbon Synapse

Proper perception of sounds in the environment requires auditory signals to be encoded with extraordinary temporal precision up to tens of microseconds, but how it originates from the hearing organs in the periphery is poorly understood. In particular, sound-evoked spikes in auditory afferent fibers in vivo are phase-locked to sound frequencies up to 5 kHz, but it is not clear how hair cells can handle intracellular Ca²⁺ changes with such high speed and efficiency. In this study, we combined patch-clamp recording and two-photon Ca²⁺ imaging to examine Ca²⁺ dynamics in hair cell ribbon synapses in the bullfrog amphibian papilla of both sexes. We found that Ca²⁺ clearance from single synaptic ribbons followed a double exponential function, and the weight of the fast component, but not the two time constants, was significantly reduced for prolonged stimulation, and during inhibition of the plasma membrane Ca²⁺ ATPase (PMCA), the mitochondrial Ca²⁺ uptake (MCU), or the sarcolemma/endoplasmic reticulum Ca²⁺ ATPase (SERCA), but not the Na⁺/Ca²⁺ exchanger (NCX). Furthermore, we found that both the basal Ca²⁺ level and the Ca²⁺ rise during sinusoidal stimulation were significantly increased by inhibition of PMCA, MCU, or SERCA. Consistently, phase-locking of synaptic vesicle releases from hair cells was also significantly reduced by blocking PMCA, MCU, or SERCA, but not NCX. We conclude that, in addition to fast diffusion mediated by mobile Ca²⁺ buffer, multiple Ca²⁺ extrusion pumps are required for phase-locking at the auditory hair cell ribbon synapse.SIGNIFICANCE STATEMENT Hair cell synapses can transmit sound-driven signals precisely in the kHz range. However, previous studies of Ca²⁺ handling in auditory hair cells have often been conducted in immature hair cells, with elevated extracellular Ca²⁺ concentration, or through steady-state stimulation that may not be physiologically relevant. Here we examine Ca²⁺ clearance from hair cell synaptic ribbons in a fully mature preparation at physiological concentration of external Ca²⁺ and at physiological temperature. By stimulating hair cells with sinusoidal voltage commands that mimic pure sound tones, we recapitulated the phase-locking of hair cell exocytosis with an in vitro approach. This allowed us to reveal the Ca²⁺ extrusion mechanisms that are required for phase-locking at auditory hair cell ribbon synapses.

Foreground stimuli and task engagement enhance neuronal adaptation to background noise in the inferior colliculus of macaques

Auditory neuronal responses are modified by background noise. Inferior colliculus (IC) neuronal responses adapt to the most frequent sound level within an acoustic scene (adaptation to stimulus statistics), a mechanism that may preserve neuronal and behavioral thresholds for signal detection. However, it is still unclear whether the presence of foreground stimuli and/or task involvement can modify neuronal adaptation. To investigate how task engagement interacts with this mechanism, we compared the response of IC neurons to background noise, which caused adaptation to stimulus statistics, while macaque monkeys performed a masked tone detection task (task-driven condition) with responses recorded when the same background noise was presented alone (passive listening condition). In the task-dependent condition, monkeys performed a Go/No-Go task while 50-ms tones were embedded within an adaptation-inducing continuous background noise whose levels changed every 50 ms and were drawn from a probability distribution. The adaptation to noise stimulus statistics in IC neuronal responses was significantly enhanced in the task-driven condition compared with the passive listening condition, showing that foreground stimuli and/or task-engagement can modify IC neuronal responses. Additionally, the response of IC neurons to noise was significantly affected by the preceding sensory information (history effect) regardless of task involvement. These studies show that dynamic range adaptation in IC preserves behavioral and neurometric thresholds irrespective of noise type and a dependence of neuronal activity on task-related factors at subcortical levels of processing.NEW & NOTEWORTHY Auditory neuronal responses are influenced by maskers and distractors. However, it is still unclear whether the neuronal sensitivity to the masker stimulus is influenced by task-dependent factors. Our study represents one of the first attempts to investigate how task involvement influences the neural representation of background sounds in the subcortical, midbrain auditory neurons of behaving animals.

The Impact of Frequency Scale on the Response Sensitivity and Reliability of Cortical Neurons to 1/fβ Input Signals

What type of principle features intrinsic inside of the fluctuated input signals could drive neurons with the maximal excitations is one of the crucial neural coding issues. In this article, we examined both experimentally and theoretically the cortical neuronal responsivity (including firing rate and spike timing reliability) to input signals with different intrinsic correlational statistics (e.g., white-type noise, showed 1/f0 power spectrum, pink noise 1/f, and brown noises 1/f2) and different frequency ranges. Our results revealed that the response sensitivity and reliability of cortical neurons is much higher in response to 1/f noise stimuli with long-term correlations than 1/f0 with short-term correlations for a broad frequency range, and also higher than 1/f2 for all frequency ranges. In addition, we found that neuronal sensitivity diverges to opposite directions for 1/f noise comparing with 1/f0 white noise as a function of cutoff frequency of input signal. As the cutoff frequency is progressively increased from 50 to 1,000 Hz, the neuronal responsiveness increased gradually for 1/f noise, while decreased exponentially for white noise. Computational simulations of a general cortical model revealed that, neuronal sensitivity and reliability to input signal statistics was majorly dominated by fast sodium inactivation, potassium activation, and membrane time constants.

Intrinsic physiological properties underlie auditory response diversity in the avian cochlear nucleus

Sensory systems exploit parallel processing of stimulus features to enable rapid, simultaneous extraction of information. Mechanisms that facilitate this differential extraction of stimulus features can be intrinsic or synaptic in origin. A subdivision of the avian cochlear nucleus, nucleus angularis (NA), extracts sound intensity information from the auditory nerve and contains neurons that exhibit diverse responses to sound and current injection. NA neurons project to multiple regions ascending the auditory brain stem including the superior olivary nucleus, lateral lemniscus, and avian inferior colliculus, with functional implications for inhibitory gain control and sound localization. Here we investigated whether the diversity of auditory response patterns in NA can be accounted for by variation in intrinsic physiological features. Modeled sound-evoked auditory nerve input was applied to NA neurons with dynamic clamp during in vitro whole cell recording at room temperature. Temporal responses to auditory nerve input depended on variation in intrinsic properties, and the low-threshold K⁺ current was implicated as a major contributor to temporal response diversity and neuronal input-output functions. An auditory nerve model of acoustic amplitude modulation produced synchrony coding of modulation frequency that depended on the intrinsic physiology of the individual neuron. In Primary-Like neurons, varying low-threshold K⁺ conductance with dynamic clamp altered temporal modulation tuning bidirectionally. Taken together, these data suggest that intrinsic physiological properties play a key role in shaping auditory response diversity to both simple and more naturalistic auditory stimuli in the avian cochlear nucleus. NEW & NOTEWORTHY This article addresses the question of how the nervous system extracts different information in sounds. Neurons in the cochlear nucleus show diverse responses to acoustic stimuli that may allow for parallel processing of acoustic features. The present studies suggest that diversity in intrinsic physiological features of individual neurons, including levels of a low voltage-activated K⁺ current, play a major role in regulating the diversity of auditory responses.

Phase-locking precision is enhanced by multiquantal release at an auditory hair cell ribbon synapse

Sound-evoked spikes in the auditory nerve can phase-lock with submillisecond precision for prolonged periods of time. However, the synaptic mechanisms that enable this accurate spike firing remain poorly understood. Using paired recordings from adult frog hair cells and their afferent fibers, we show here that during sine-wave stimuli, synaptic failures occur even during strong stimuli. However, exclusion of these failures leads to mean excitatory postsynaptic current (EPSC) amplitudes that are independent of Ca(2+) current. Given the intrinsic jitter in spike triggering, evoked synaptic potentials and spikes had surprisingly similar degrees of synchronization to a sine-wave stimulus. This similarity was explained by an unexpected finding: large-amplitude evoked EPSCs have a significantly larger synchronization index than smaller evoked EPSCs. Large EPSCs therefore enhance the precision of spike timing. The hair cells' unique capacity for continuous, large-amplitude, and highly synchronous multiquantal release thus underlies its ability to trigger phase-locked spikes in afferent fibers.

Why do forward maskers affect auditory intensity discrimination? Evidence from "molecular psychophysics"

Nonsimultaneous maskers can strongly impair performance in an auditory intensity discrimination task. Using methods of molecular psychophysics, we quantified the extent to which (1) a masker-induced impairment of the representation of target intensity (i.e., increase in internal noise) and (2) a systematic influence of the masker intensities on the decision variable contribute to these effects. In a two-interval intensity discrimination procedure, targets were presented in quiet, and combined with forward maskers. The lateralization of the maskers relative to the targets was varied via the interaural time difference. Intensity difference limens (DLs) were strongly elevated under forward masking but less with contralateral than with ipsilateral maskers. For most listeners and conditions, perceptual weights measuring the relation between the target and masker levels and the response in the intensity discrimination task were positive and significant. Higher perceptual weights assigned to the maskers corresponded to stronger elevations of the intensity DL. The maskers caused only a weak increase in internal noise, unrelated to target level and masker lateralization. The results indicate that the effects of forward masking on intensity discrimination are determined by an inclusion of the masker intensities in the decision variable, compatible with the hypothesis that the impairment in performance is to a large part caused by difficulties in directing selective attention to the targets. The effects of masker lateralization are evidence for top-down influences, and the observed positive signs of the masker weights suggest that the relevant mechanisms are located at higher processing stages rather than in the auditory periphery.

The meaning of spikes from the neuron's point of view: predictive homeostasis generates the appearance of randomness

The conventional interpretation of spikes is from the perspective of an external observer with knowledge of a neuron's inputs and outputs who is ignorant of the contents of the "black box" that is the neuron. Here we consider a neuron to be an observer and we interpret spikes from the neuron's perspective. We propose both a descriptive hypothesis based on physics and logic, and a prescriptive hypothesis based on biological optimality. Our descriptive hypothesis is that a neuron's membrane excitability is "known" and the amplitude of a future excitatory postsynaptic conductance (EPSG) is "unknown". Therefore excitability is an expectation of EPSG amplitude and a spike is generated only when EPSG amplitude exceeds its expectation ("prediction error"). Our prescriptive hypothesis is that a diversity of synaptic inputs and voltage-regulated ion channels implement "predictive homeostasis", working to insure that the expectation is accurate. The homeostatic ideal and optimal expectation would be achieved when an EPSP reaches precisely to spike threshold, so that spike output is exquisitely sensitive to small variations in EPSG input. To an external observer who knows neither EPSG amplitude nor membrane excitability, spikes would appear random if the neuron is making accurate predictions. We review experimental evidence that spike probabilities are indeed maintained near an average of 0.5 under natural conditions, and we suggest that the same principles may also explain why synaptic vesicle release appears to be "stochastic". Whereas the present hypothesis accords with principles of efficient coding dating back to Barlow (1961), it contradicts decades of assertions that neural activity is substantially "random" or "noisy". The apparent randomness is by design, and like many other examples of apparent randomness, it corresponds to the ignorance of external macroscopic observers about the detailed inner workings of a microscopic system.

Neural adaptation and behavioral measures of temporal processing and speech perception in cochlear implant recipients

The objective was to determine if one of the neural temporal features, neural adaptation, can account for the across-subject variability in behavioral measures of temporal processing and speech perception performance in cochlear implant (CI) recipients. Neural adaptation is the phenomenon in which neural responses are the strongest at the beginning of the stimulus and decline following stimulus repetition (e.g., stimulus trains). It is unclear how this temporal property of neural responses relates to psychophysical measures of temporal processing (e.g., gap detection) or speech perception. The adaptation of the electrical compound action potential (ECAP) was obtained using 1000 pulses per second (pps) biphasic pulse trains presented directly to the electrode. The adaptation of the late auditory evoked potential (LAEP) was obtained using a sequence of 1-kHz tone bursts presented acoustically, through the cochlear implant. Behavioral temporal processing was measured using the Random Gap Detection Test at the most comfortable listening level. Consonant nucleus consonant (CNC) word and AzBio sentences were also tested. The results showed that both ECAP and LAEP display adaptive patterns, with a substantial across-subject variability in the amount of adaptation. No correlations between the amount of neural adaptation and gap detection thresholds (GDTs) or speech perception scores were found. The correlations between the degree of neural adaptation and demographic factors showed that CI users having more LAEP adaptation were likely to be those implanted at a younger age than CI users with less LAEP adaptation. The results suggested that neural adaptation, at least this feature alone, cannot account for the across-subject variability in temporal processing ability in the CI users. However, the finding that the LAEP adaptive pattern was less prominent in the CI group compared to the normal hearing group may suggest the important role of normal adaptation pattern at the cortical level in speech perception.

Predicting spike timing in highly synchronous auditory neurons at different sound levels

A challenge for sensory systems is to encode natural signals that vary in amplitude by orders of magnitude. The spike trains of neurons in the auditory system must represent the fine temporal structure of sounds despite a tremendous variation in sound level in natural environments. It has been shown in vitro that the transformation from dynamic signals into precise spike trains can be accurately captured by simple integrate-and-fire models. In this work, we show that the in vivo responses of cochlear nucleus bushy cells to sounds across a wide range of levels can be precisely predicted by deterministic integrate-and-fire models with adaptive spike threshold. Our model can predict both the spike timings and the firing rate in response to novel sounds, across a large input level range. A noisy version of the model accounts for the statistical structure of spike trains, including the reliability and temporal precision of responses. Spike threshold adaptation was critical to ensure that predictions remain accurate at different levels. These results confirm that simple integrate-and-fire models provide an accurate phenomenological account of spike train statistics and emphasize the functional relevance of spike threshold adaptation.

Proportional spike-timing precision and firing reliability underlie efficient temporal processing of periodicity and envelope shape cues

Temporal sound cues are essential for sound recognition, pitch, rhythm, and timbre perception, yet how auditory neurons encode such cues is subject of ongoing debate. Rate coding theories propose that temporal sound features are represented by rate tuned modulation filters. However, overwhelming evidence also suggests that precise spike timing is an essential attribute of the neural code. Here we demonstrate that single neurons in the auditory midbrain employ a proportional code in which spike-timing precision and firing reliability covary with the sound envelope cues to provide an efficient representation of the stimulus. Spike-timing precision varied systematically with the timescale and shape of the sound envelope and yet was largely independent of the sound modulation frequency, a prominent cue for pitch. In contrast, spike-count reliability was strongly affected by the modulation frequency. Spike-timing precision extends from sub-millisecond for brief transient sounds up to tens of milliseconds for sounds with slow-varying envelope. Information theoretic analysis further confirms that spike-timing precision depends strongly on the sound envelope shape, while firing reliability was strongly affected by the sound modulation frequency. Both the information efficiency and total information were limited by the firing reliability and spike-timing precision in a manner that reflected the sound structure. This result supports a temporal coding strategy in the auditory midbrain where proportional changes in spike-timing precision and firing reliability can efficiently signal shape and periodicity temporal cues.

Refractoriness enhances temporal coding by auditory nerve fibers

A universal property of spiking neurons is refractoriness, a transient decrease in discharge probability immediately following an action potential (spike). The refractory period lasts only one to a few milliseconds, but has the potential to affect temporal coding of acoustic stimuli by auditory neurons, which are capable of submillisecond spike-time precision. Here this possibility was investigated systematically by recording spike times from chicken auditory nerve fibers in vivo while stimulating with repeated pure tones at characteristic frequency. Refractory periods were tightly distributed, with a mean of 1.58 ms. A statistical model was developed to recapitulate each fiber's responses and then used to predict the effect of removing the refractory period on a cell-by-cell basis for two largely independent facets of temporal coding: faithful entrainment of interspike intervals to the stimulus frequency and precise synchronization of spike times to the stimulus phase. The ratio of the refractory period to the stimulus period predicted the impact of refractoriness on entrainment and synchronization. For ratios less than ∼0.9, refractoriness enhanced entrainment and this enhancement was often accompanied by an increase in spike-time precision. At higher ratios, little or no change in entrainment or synchronization was observed. Given the tight distribution of refractory periods, the ability of refractoriness to improve temporal coding is restricted to neurons responding to low-frequency stimuli. Enhanced encoding of low frequencies likely affects sound localization and pitch perception in the auditory system, as well as perception in nonauditory sensory modalities, because all spiking neurons exhibit refractoriness.

Transmitter release from cochlear hair cells is phase locked to cyclic stimuli of different intensities and frequencies

The auditory system processes time and intensity through separate brainstem pathways to derive spatial location as well as other salient features of sound. The independent coding of time and intensity begins in the cochlea, where afferent neurons can fire action potentials at constant phase throughout a wide range of stimulus intensities. We have investigated time and intensity coding by simultaneous presynaptic and postsynaptic recording at the hair cell-afferent synapse from rats. Trains of depolarizing steps to the hair cell were used to elicit postsynaptic currents that occurred at constant phase for a range of membrane potentials over which release probability varied significantly. To probe the underlying mechanisms, release was examined using single steps to various command voltages. As expected for vesicular release, first synaptic events occurred earlier as presynaptic calcium influx grew larger. However, synaptic depression produced smaller responses with longer first latencies. Thus, during repetitive hair cell stimulation, as the hair cell is more strongly depolarized, increased calcium channel gating hurries transmitter release, but the resulting vesicular depletion produces a compensatory slowing. Quantitative simulation of ribbon function shows that these two factors varied reciprocally with hair cell depolarization (stimulus intensity) to produce constant synaptic phase. Finally, we propose that the observed rapid vesicle replenishment would help maintain the vesicle pool, which in turn would equilibrate with the stimulus intensity (and therefore the number of open Ca(2+) channels), so that for trains of different levels the average phase will be conserved.

Vestibular hair cells and afferents: two channels for head motion signals

Vestibular epithelia of the inner ear detect head motions over a wide range of amplitudes and frequencies. In mammals, afferent nerve fibers from central and peripheral zones of vestibular epithelia form distinct populations with different response dynamics and spike timing. Central-zone afferents are large, fast conduits for phasic signals encoded in irregular spike trains. The finer afferents from peripheral zones conduct more slowly and encode more tonic, linear signals in highly regular spike trains. The hair cells are also of two types, I and II, but the two types do not correspond directly to the two afferent populations. Zonal differences in afferent response dynamics may arise at multiple stages, including mechanoelectrical transduction, voltage-gated channels in hair cells and afferents, afferent transmission at calyceal and bouton synapses, and spike generation in regular and irregular afferents. In contrast, zonal differences in spike timing may depend more simply on the selective expression of low-voltage-activated ion channels by irregular afferents.

Modulation of temporal precision in thalamic population responses to natural visual stimuli

Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise - on a time scale of 10-25 ms - both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment.

Neuronal precision and the limits for acoustic signal recognition in a small neuronal network

Recognition of acoustic signals may be impeded by two factors: extrinsic noise, which degrades sounds before they arrive at the receiver’s ears, and intrinsic neuronal noise, which reveals itself in the trial-to-trial variability of the responses to identical sounds. Here we analyzed how these two noise sources affect the recognition of acoustic signals from potential mates in grasshoppers. By progressively corrupting the envelope of a female song, we determined the critical degradation level at which males failed to recognize a courtship call in behavioral experiments. Using the same stimuli, we recorded intracellularly from auditory neurons at three different processing levels, and quantified the corresponding changes in spike train patterns by a spike train metric, which assigns a distance between spike trains. Unexpectedly, for most neurons, intrinsic variability accounted for the main part of the metric distance between spike trains, even at the strongest degradation levels. At consecutive levels of processing, intrinsic variability increased, while the sensitivity to external noise decreased. We followed two approaches to determine critical degradation levels from spike train dissimilarities, and compared the results with the limits of signal recognition measured in behaving animals.

On population encoding and decoding of auditory information for bat echolocation

In this article, we study the neural encoding of acoustic information for FM-bats (such as Eptesicus fuscus) in simulation. In echolocation research, the frequency-time sound representation as expressed by the spectrogram is often considered as input. The rationale behind this is that a similar representation is present in the cochlea, i.e. the receptor potential of the inner hair cells (IHC) along the length of the cochlea, and hence similar acoustic information is relayed to the brain. In this article, we study to what extent the latter assumption is true. The receptor potential is converted into neural activity of the synapting auditory nerve cells (ANC), and information might be lost in this conversion process. Especially for FM-bats, this information transmission is not trivial: in contrast to other mammals, they detect short transient signals, and consequently neural activity can only be integrated over very limited time intervals. To quantify the amount of information transmitted we design a neural network-based algorithm to reconstruct the IHC receptor potentials from the spiking activity of the synapting auditory neurons. Both the receptor potential and the resulting neural activity are simulated using Meddis' peripheral model. Comparing the reconstruction to the IHC receptor potential, we quantify the information transmission of the bat hearing system and investigate how this depends on the intensity of the incoming signal, the distribution of auditory neurons, and previous masking stimulation (adaptation). In addition, we show how this approach allows to inspect which spectral features survive neural encoding and hence can be relevant for echolocation.

Spontaneous activity of auditory nerve fibers in the barn owl (Tyto alba): analyses of interspike interval distributions

In vertebrate auditory systems, the conversion from graded receptor potentials across the hair-cell membrane into stochastic spike trains of the auditory nerve (AN) fibers is performed by ribbon synapses. The statistics underlying this process constrain auditory coding but are not precisely known. Here, we examine the distributions of interspike intervals (ISIs) from spontaneous activity of AN fibers of the barn owl (Tyto alba), a nocturnal avian predator whose auditory system is specialized for precise temporal coding. The spontaneous activity of AN fibers, with the exception of those showing preferred intervals, is commonly thought to result from excitatory events generated by a homogeneous Poisson point process, which lead to spikes unless the fiber is refractory. We show that the ISI distributions in the owl are better explained as resulting from the action of a brief refractory period ( approximately 0.5 ms) on excitatory events generated by a homogeneous stochastic process where the distribution of interevent intervals is a mixture of an exponential and a gamma distribution with shape factor 2, both with the same scaling parameter. The same model was previously shown to apply to AN fibers in the cat. However, the mean proportions of exponentially versus gamma-distributed intervals in the mixture were different for cat and owl. Furthermore, those proportions were constant across fibers in the cat, whereas they covaried with mean spontaneous rate and with characteristic frequency in the owl. We hypothesize that in birds, unlike in mammals, more than one ribbon may provide excitation to most fibers, accounting for the different proportions, and that variation in the number of ribbons may underlie the variation in the proportions.

The origin of adaptation in the auditory pathway of locusts is specific to cell type and function

We investigated the origin of spike frequency adaptation within a layered sensory network: the auditory pathway of locusts. Spike frequency adaptation as observed in an individual neuron may arise because of intrinsic or presynaptic adaptation mechanisms. To separate the contribution of different mechanisms, we recorded from the same cell during acoustic and intracellular current stimulation. We studied three identified neuron types that are representative for each network layer and participate in processing auditory patterns and localizing sound sources. By comparing current and acoustic stimulation, three distinct patterns of the distribution of adaptation mechanisms within the sensory network emerged: (1) balanced influence of both intrinsic and presynaptic adaptation mechanisms in an interneuron that summates over several receptor afferents (TN1), (2) predominantly inhibiting input as the source for spike frequency adaptation in a cell that transmits both pattern representation and directional information (BSN1), (3) primarily intrinsic, spike-triggered adaptation currents within an interneuron coding exclusively for direction (AN2). The time courses of spike frequency adaptation differed significantly between the cells types. Using the adaptation time constants, we were able to predict signal transmission properties for the different cells. We conclude that the adaptation mechanisms differ greatly among interneurons within this sensory pathway and are a function of their role in information processing.

Timing precision in population coding of natural scenes in the early visual system

The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ∼10-ms resolution is a crucial property of the neural code entering cortex.

Neurons convey information about the world in the form of trains of action potentials (spikes). These trains are highly repeatable when the same stimulus is presented multiple times, and this temporal precision across repetitions can be as fine as a few milliseconds. It is usually assumed that this time scale also corresponds to the timing precision of several neighboring neurons firing in concert. However, the relative timing of spikes emitted by different neurons in a local population is not necessarily as fine as the temporal precision across repetitions within a single neuron. In the visual system of the brain, the level of contrast in the image entering the retina can affect single-neuron temporal precision, but the effects of contrast on the neural population code are unknown. Here we show that the temporal scale of the population code entering visual cortex is on the order of 10 ms and is largely insensitive to changes in visual contrast. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary in representing the more slowly varying natural environment, preserving relative spike timing at a ∼10-ms resolution may be a crucial property of the neural code entering cortex.

Early neural representation of visual scenes occurs with a temporal precision on the order of 10 ms, which is precise enough to strongly drive downstream neurons in the visual pathway. Unlike individual neurons, the neural population code is largely insensitive to pronounced changes in visual contrast.

Adaptation of firing rate and spike-timing precision in the avian cochlear nucleus

Adaptation is commonly defined as a decrease in response to a constant stimulus. In the auditory system such adaptation is seen at multiple levels. However, the first-order central neurons of the interaural time difference detection circuit encode information in the timing of spikes rather than the overall firing rate. We investigated adaptation during in vitro whole-cell recordings from chick nucleus magnocellularis neurons. Injection of noisy, depolarizing current caused an increase in firing rate and a decrease in spike time precision that developed over approximately 20 s. This adaptation depends on sustained depolarization, is independent of firing, and is eliminated by alpha-dendrotoxin (0.1 microM), implicating slow inactivation of low-threshold voltage-activated K+ channels as its mechanism. This process may alter both firing rate and spike-timing precision of phase-locked inputs to coincidence detector neurons in nucleus laminaris and thereby adjust the precision of sound localization.

Synaptic ribbon enables temporal precision of hair cell afferent synapse by increasing the number of readily releasable vesicles: a modeling study

Synaptic ribbons are classically associated with mediating indefatigable neurotransmitter release by sensory neurons that encode persistent stimuli. Yet when hair cells lack anchored ribbons, the temporal precision of vesicle fusion and auditory nerve discharges are degraded. A rarified statistical model predicted increasing precision of first-exocytosis latency with the number of readily releasable vesicles. We developed an experimentally constrained biophysical model to test the hypothesis that ribbons enable temporally precise exocytosis by increasing the readily releasable pool size. Simulations of calcium influx, buffered calcium diffusion, and synaptic vesicle exocytosis were stochastic (Monte Carlo) and yielded spatiotemporal distributions of vesicle fusion consistent with experimental measurements of exocytosis magnitude and first-spike latency of nerve fibers. No single vesicle could drive the auditory nerve with requisite precision, indicating a requirement for multiple readily releasable vesicles. However, plasmalemma-docked vesicles alone did not account for the nerve's precision--the synaptic ribbon was required to retain a pool of readily releasable vesicles sufficiently large to statistically ensure first-exocytosis latency was both short and reproducible. The model predicted that at least 16 readily releasable vesicles were necessary to match the nerve's precision and provided insight into interspecies differences in synaptic anatomy and physiology. We confirmed that ribbon-associated vesicles were required in disparate calcium buffer conditions, irrespective of the number of vesicles required to trigger an action potential. We conclude that one of the simplest functions ascribable to the ribbon--the ability to hold docked vesicles at an active zone--accounts for the synapse's temporal precision.