Summation of spatiotemporal input patterns in leaky integrate-and-fire neurons: application to neurons in the cochlear nucleus receiving converging auditory nerve fiber input

Age-related reduction in frequency-following responses as a potential marker of cochlear neural degeneration

Healthy aging may be associated with neural degeneration in the cochlea even before clinical hearing loss emerges. Reduction in frequency-following responses (FFRs) to tonal carriers in older clinically normal-hearing listeners has previously been reported, and has been argued to reflect an age-dependent decline in temporal processing in the central auditory system. Alternatively, age-dependent loss of auditory nerve fibers (ANFs) may have little effect on audiometric sensitivity and yet compromise the precision of neural phase-locking relying on joint activity across populations of fibers. This peripheral loss may, in turn, contribute to reduced neural synchrony in the brainstem as reflected in the FFR. Here, we combined human electrophysiology and auditory nerve (AN) modeling to investigate whether age-related changes in the FFR would be consistent with peripheral neural degeneration. FFRs elicited by pure tones and frequency sweeps at carrier frequencies between 200 and 1200 Hz were obtained in older (ages 48-76) and younger (ages 20-30) listeners, both groups having clinically normal audiometric thresholds up to 6 kHz. The same stimuli were presented to a computational model of the AN in which age-related loss of hair cells or ANFs was modelled using human histopathological data. In the older human listeners, the measured FFRs to both sweeps and pure tones were found to be reduced across the carrier frequencies examined. These FFR reductions were consistent with model simulations of age-related ANF loss. In model simulations, the phase-locked response produced by the population of remaining fibers decreased proportionally with increasing loss of the ANFs. Basal-turn loss of inner hair cells also reduced synchronous activity at lower frequencies, albeit to a lesser degree. Model simulations of age-related threshold elevation further indicated that outer hair cell dysfunction had no negative effect on phase-locked AN responses. These results are consistent with a peripheral source of the FFR reductions observed in older normal-hearing listeners, and indicate that FFRs at lower carrier frequencies may potentially be a sensitive marker of peripheral neural degeneration.

Neuronal population model of globular bushy cells covering unit-to-unit variability

Computations of acoustic information along the central auditory pathways start in the cochlear nucleus. Bushy cells in the anteroventral cochlear nucleus, which innervate monaural and binaural stations in the superior olivary complex, process and transfer temporal cues relevant for sound localization. These cells are categorized into two groups: spherical and globular bushy cells (SBCs/GBCs). Spontaneous rates of GBCs innervated by multiple auditory nerve (AN) fibers are generally lower than those of SBCs that receive a small number of large AN synapses. In response to low-frequency tonal stimulation, both types of bushy cells show improved phase-locking and entrainment compared to AN fibers. When driven by high-frequency tones, GBCs show primary-like-with-notch or onset-L peristimulus time histograms and relatively irregular spiking. However, previous in vivo physiological studies of bushy cells also found considerable unit-to-unit variability in these response patterns. Here we present a population of models that can simulate the observed variation in GBCs. We used a simple coincidence detection model with an adaptive threshold and systematically varied its six parameters. Out of 567000 parameter combinations tested, 7520 primary-like-with-notch models and 4094 onset-L models were selected that satisfied a set of physiological criteria for a GBC unit. Analyses of the model parameters and output measures revealed that the parameters of the accepted model population are weakly correlated with each other to retain major GBC properties, and that the output spiking patterns of the model are affected by a combination of multiple parameters. Simulations of frequency-dependent temporal properties of the model GBCs showed a reasonable fit to empirical data, supporting the validity of our population modeling. The computational simplicity and efficiency of the model structure makes our approach suitable for future large-scale simulations of binaural information processing that may involve thousands of GBC units.

In the auditory system, specialized neuronal circuits process various types of acoustic information. A group of neurons, called globular bushy cells (GBCs), faithfully transfer timing information of acoustic signals to their downstream neurons responsible for the perception of sound location. Previous physiological studies found representative activity patterns of GBCs, but with substantial individual variations among them. In this study, we present a population of models, instead of creating one best model, to account for the observed variations of GBCs. We varied all six parameters of a simple auditory neuron model and selected the combinations of parameters that led to acceptable activity patterns of GBCs. In total, we tested more than half a million combinations and accepted ~11600 GBC models. Temporal spiking patterns of real GBCs depend on the sound frequency, and our model population was able to replicate this trend. The model used here is computationally efficient and can thus serve as a building block for future large-scale simulations of auditory information processing.

Effect of Phase Response Curve Shape and Synaptic Driving Force on Synchronization of Coupled Neuronal Oscillators

The role of the phase response curve (PRC) shape on the synchrony of synaptically coupled oscillating neurons is examined. If the PRC is independent of the phase, because of the synaptic form of the coupling, synchrony is found to be stable for both excitatory and inhibitory coupling at all rates, whereas the antisynchrony becomes stable at low rates. A faster synaptic rise helps extend the stability of antisynchrony to higher rates. If the PRC is not constant but has a profile like that of a leaky integrate-and-fire model, then, in contrast to the earlier reports that did not include the voltage effects, mutual excitation could lead to stable synchrony provided the synaptic reversal potential is below the voltage level the neuron would have reached in the absence of the interaction and threshold reset. This level is controlled by the applied current and the leakage parameters. Such synchrony is contingent on significant phase response (that would result, for example, by a sharp PRC jump) occurring during the synaptic rising phase. The rising phase, however, does not contribute significantly if it occurs before the voltage spike reaches its peak. Then a stable near-synchronous state can still exist between type 1 PRC neurons if the PRC shows a left skewness in its shape. These results are examined comprehensively using perfect integrate-and-fire, leaky integrate-and-fire, and skewed PRC shapes under the assumption of the weakly coupled oscillator theory applied to synaptically coupled neuron models.

Activity-dependent modulation of inhibitory synaptic kinetics in the cochlear nucleus

Spherical bushy cells (SBCs) in the anteroventral cochlear nucleus respond to acoustic stimulation with discharges that precisely encode the phase of low-frequency sound. The accuracy of spiking is crucial for sound localization and speech perception. Compared to the auditory nerve input, temporal precision of SBC spiking is improved through the engagement of acoustically evoked inhibition. Recently, the inhibition was shown to be less precise than previously understood. It shifts from predominantly glycinergic to synergistic GABA/glycine transmission in an activity-dependent manner. Concurrently, the inhibition attains a tonic character through temporal summation. The present study provides a comprehensive understanding of the mechanisms underlying this slow inhibitory input. We performed whole-cell voltage clamp recordings on SBCs from juvenile Mongolian gerbils and recorded evoked inhibitory postsynaptic currents (IPSCs) at physiological rates. The data reveal activity-dependent IPSC kinetics, i.e., the decay is slowed with increased input rates or recruitment. Lowering the release probability yielded faster decay kinetics of the single- and short train-IPSCs at 100 Hz, suggesting that transmitter quantity plays an important role in controlling the decay. Slow transmitter clearance from the synaptic cleft caused prolonged receptor binding and, in the case of glycine, spillover to nearby synapses. The GABAergic component prolonged the decay by contributing to the asynchronous vesicle release depending on the input rate. Hence, the different factors controlling the amount of transmitters in the synapse jointly slow the inhibition during physiologically relevant activity. Taken together, the slow time course is predominantly determined by the receptor kinetics and transmitter clearance during short stimuli, whereas long duration or high frequency stimulation additionally engage asynchronous release to prolong IPSCs.

Dynamic fidelity control to the central auditory system: synergistic glycine/GABAergic inhibition in the cochlear nucleus

GABA and glycine are the major inhibitory transmitters that attune neuronal activity in the CNS of mammals. The respective transmitters are mostly spatially separated, that is, synaptic inhibition in the forebrain areas is mediated by GABA, whereas glycine is predominantly used in the brainstem. Accordingly, inhibition in auditory brainstem circuits is largely mediated by glycine, but there are few auditory synapses using both transmitters in maturity. Little is known about physiological advantages of such a two-transmitter inhibitory mechanism. We explored the benefit of engaging both glycine and GABA with inhibition at the endbulb of Held-spherical bushy cell synapse in the auditory brainstem of juvenile Mongolian gerbils. This model synapse enables selective in vivo activation of excitatory and inhibitory neuronal inputs through systemic sound stimulation and precise analysis of the input (endbulb of Held) output (spherical bushy cell) function. The combination of in vivo and slice electrophysiology revealed that the dynamic AP inhibition in spherical bushy cells closely matches the inhibitory conductance profile determined by the glycine-R and GABAA-R. The slow and potent glycinergic component dominates the inhibitory conductance, thereby primarily accounting for its high-pass filter properties. GABAergic transmission enhances the inhibitory strength and shapes its duration in an activity-dependent manner, thus increasing the inhibitory potency to suppress the excitation through the endbulb of Held. Finally, in silico modeling provides a strong link between in vivo and slice data by simulating the interactions between the endbulb- and the synergistic glycine-GABA-conductances during in vivo-like spontaneous and sound evoked activities.

Large somatic synapses on neurons in the ventral lateral lemniscus work in pairs

In the auditory system, large somatic synapses convey strong excitation that supports temporally precise information transfer. The information transfer of such synapses has predominantly been investigated in the endbulbs of Held in the anterior ventral cochlear nucleus and the calyx of Held in the medial nucleus of the trapezoid body. These large synapses either work as relays or integrate over a small number of inputs to excite the postsynaptic neuron beyond action potential (AP) threshold. In the monaural system, another large somatic synapse targets neurons in the ventral nucleus of the lateral lemniscus (VNLL). Here, we comparatively analyze the mechanisms of synaptic information transfer in endbulbs in the VNLL and the calyx of Held in juvenile Mongolian gerbils. We find that endbulbs in the VNLL are functionally surface-scaled versions of the calyx of Held with respect to vesicle availability, release efficacy, and synaptic peak currents. This functional scaling is achieved by different calcium current kinetics that compensate for the smaller AP in VNLL endbulbs. However, the average postsynaptic current in the VNLL fails to elicit APs in its target neurons, even though equal current suffices to generate APs in neurons postsynaptic to the calyx of Held. In the VNLL, a postsynaptic A-type outward current reduces excitability and prevents AP generation upon a single presynaptic input. Instead, coincidence detection of inputs from two converging endbulbs is ideal to reliably trigger APs. Thus, even large endbulbs do not guarantee one-to-one AP transfer. Instead, information flow appears regulated by circuit requirements.

Theoretical foundations of the sound analog membrane potential that underlies coincidence detection in the barn owl

A wide variety of neurons encode temporal information via phase-locked spikes. In the avian auditory brainstem, neurons in the cochlear nucleus magnocellularis (NM) send phase-locked synaptic inputs to coincidence detector neurons in the nucleus laminaris (NL) that mediate sound localization. Previous modeling studies suggested that converging phase-locked synaptic inputs may give rise to a periodic oscillation in the membrane potential of their target neuron. Recent physiological recordings in vivo revealed that owl NL neurons changed their spike rates almost linearly with the amplitude of this oscillatory potential. The oscillatory potential was termed the sound analog potential, because of its resemblance to the waveform of the stimulus tone. The amplitude of the sound analog potential recorded in NL varied systematically with the interaural time difference (ITD), which is one of the most important cues for sound localization. In order to investigate the mechanisms underlying ITD computation in the NM-NL circuit, we provide detailed theoretical descriptions of how phase-locked inputs form oscillating membrane potentials. We derive analytical expressions that relate presynaptic, synaptic, and postsynaptic factors to the signal and noise components of the oscillation in both the synaptic conductance and the membrane potential. Numerical simulations demonstrate the validity of the theoretical formulations for the entire frequency ranges tested (1–8 kHz) and potential effects of higher harmonics on NL neurons with low best frequencies (<2 kHz).

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.

Presynaptic and postsynaptic origin of multicomponent extracellular waveforms at the endbulb of Held-spherical bushy cell synapse

Extracellular signals from the endbulb of Held-spherical bushy cell (SBC) synapse exhibit up to three component waves ('P', 'A' and 'B'). Signals lacking the third component (B) are frequently observed but as the origin of each of the components is uncertain, interpretation of this lack of B has been controversial: is it a failure to release transmitter or a failure to generate or propagate an action potential? Our aim was to determine the origin of each component. We combined single- and multiunit in vitro methods in Mongolian gerbils and Wistar rats and used pharmacological tools to modulate glutamate receptors or voltage-gated sodium channels. Simultaneous extra- and intracellular recordings from single SBCs demonstrated a presynaptic origin of the P-component, consistent with data obtained with multielectrode array recordings of local field potentials. The later components (A and B) correspond to the excitatory postsynaptic potential (EPSP) and action potential of the SBC, respectively. These results allow a clear interpretation of in vivo extracellular signals. We conclude that action potential failures occurring at the endbulb-SBC synaptic junction largely reflect failures of the EPSP to trigger an action potential and not failures of synaptic transmission. The data provide the basis for future investigation of convergence of excitatory and inhibitory inputs in modulating transmission at a fully functional neuronal system using physiological stimulation.

On the origin of the extracellular field potential in the nucleus laminaris of the barn owl (Tyto alba)

The neurophonic is a sound-evoked, frequency-following potential that can be recorded extracellularly in nucleus laminaris of the barn owl. The origin of the neurophonic, and thus the mechanisms that give rise to its exceptional temporal precision, has not yet been identified. Putative generators of the neurophonic are the activity of afferent axons, synaptic activation of laminaris neurons, or action potentials in laminaris neurons. To identify the generators, we analyzed the neurophonic in the high-frequency (>2.5 kHz) region of nucleus laminaris in response to monaural pure-tone stimulation. The amplitude of the neurophonic is typically in the millivolt range. The signal-to-noise ratio reaches values beyond 30 dB. To assess which generators could give rise to these large, synchronous extracellular potentials, we developed a computational model. Spike trains were produced by an inhomogeneous Poisson process and convolved with a spike waveform. The model explained the dependence of the simulated neurophonic on parameters such as the mean rate, the vector strength of phase locking, the number of statistically independent sources, and why the signal-to-noise ratio is independent of the spike waveform and subsequent filtering of the signal. We found that several hundred sources are needed to reach the observed signal-to-noise ratio. The summed coherent signal from the densely packed afferent axons and activation of their synapses on laminaris neurons are alone sufficient to explain the measured properties of the neurophonic.

On the use of dynamic Bayesian networks in reconstructing functional neuronal networks from spike train ensembles

Coordination among cortical neurons is believed to be a key element in mediating many high-level cortical processes such as perception, attention, learning, and memory formation. Inferring the structure of the neural circuitry underlying this coordination is important to characterize the highly nonlinear, time-varying interactions between cortical neurons in the presence of complex stimuli. In this work, we investigate the applicability of dynamic Bayesian networks (DBNs) in inferring the effective connectivity between spiking cortical neurons from their observed spike trains. We demonstrate that DBNs can infer the underlying nonlinear and time-varying causal interactions between these neurons and can discriminate between mono- and polysynaptic links between them under certain constraints governing their putative connectivity. We analyzed conditionally Poisson spike train data mimicking spiking activity of cortical networks of small and moderately large size. The performance was assessed and compared to other methods under systematic variations of the network structure to mimic a wide range of responses typically observed in the cortex. Results demonstrate the utility of DBN in inferring the effective connectivity in cortical networks.

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 volley theory and the spherical cell puzzle

Temporal coding in the auditory nerve is strikingly transformed in the cochlear nucleus. In contrast to fibers in the auditory nerve, some neurons in the cochlear nucleus can show "picket fence" phase-locking to low-frequency pure tones: they fire a precisely timed action potential at every cycle of the stimulus. Such synchronization enhancement and entrainment is particularly prominent in neurons with the spherical and globular morphology, described by Osen [Osen KK (1969) Cytoarchitecture of the cochlear nuclei in the cat. J Comp Neurol 136:453-483]. These neurons receive large axosomatic terminals from the auditory nerve--the end bulbs and modified end bulbs of Held--and project to binaural comparator nuclei in the superior olivary complex. The most popular model to account for picket fence phase-locking is monaural coincidence detection. This mechanism is plausible for globular neurons, which receive a large number of inputs. We draw attention to the existence of enhanced phase-locking and entrainment in spherical neurons, which receive too few end-bulb inputs from the auditory nerve to make a coincidence detection of end-bulb firings a plausible mechanism of synchronization enhancement.

Spontaneous activity of auditory-nerve fibers: insights into stochastic processes at ribbon synapses

In several sensory systems, the conversion of the representation of stimuli from graded membrane potentials into stochastic spike trains is performed by ribbon synapses. In the mammalian auditory system, the spiking characteristics of the vast majority of primary afferent auditory-nerve (AN) fibers are determined primarily by a single ribbon synapse in a single inner hair cell (IHC), and thus provide a unique window into the operation of the synapse. Here, we examine the distributions of interspike intervals (ISIs) of cat AN fibers under conditions when the IHC membrane potential can be considered constant and the processes generating AN fiber activity can be considered stationary, namely in the absence of auditory stimulation. Such spontaneous activity is commonly thought to result from an excitatory Poisson point process modified by the refractory properties of the fiber, but here we show that this cannot be the case. Rather, the ISI distributions are one to two orders of magnitude better and very accurately described as a result of a homogeneous stochastic process of excitation (transmitter release events) in which the distribution of interevent times is a mixture of an exponential and a gamma distribution with shape factor 2, both with the same scale parameter. Whereas the scale parameter varies across fibers, the proportions of exponentially and gamma distributed intervals in the mixture, and the refractory properties, can be considered constant. This suggests that all of the ribbon synapses operate in a similar manner, possibly just at different rates. Our findings also constitute an essential step toward a better understanding of the spike-train representation of time-varying stimuli initiated at this synapse, and thus of the fundamentals of temporal coding in the auditory pathway.

A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties

The integrate-and-fire neuron model describes the state of a neuron in terms of its membrane potential, which is determined by the synaptic inputs and the injected current that the neuron receives. When the membrane potential reaches a threshold, an action potential (spike) is generated. This review considers the model in which the synaptic input varies periodically and is described by an inhomogeneous Poisson process, with both current and conductance synapses. The focus is on the mathematical methods that allow the output spike distribution to be analyzed, including first passage time methods and the Fokker-Planck equation. Recent interest in the response of neurons to periodic input has in part arisen from the study of stochastic resonance, which is the noise-induced enhancement of the signal-to-noise ratio. Networks of integrate-and-fire neurons behave in a wide variety of ways and have been used to model a variety of neural, physiological, and psychological phenomena. The properties of the integrate-and-fire neuron model with synaptic input described as a temporally homogeneous Poisson process are reviewed in an accompanying paper (Burkitt in Biol Cybern, 2006).

Noise reduction of coincidence detector output by the inferior colliculus of the barn owl

A recurring theme in theoretical work is that integration over populations of similarly tuned neurons can reduce neural noise. However, there are relatively few demonstrations of an explicit noise reduction mechanism in a neural network. Here we demonstrate that the brainstem of the barn owl includes a stage of processing apparently devoted to increasing the signal-to-noise ratio in the encoding of the interaural time difference (ITD), one of two primary binaural cues used to compute the position of a sound source in space. In the barn owl, the ITD is processed in a dedicated neural pathway that terminates at the core of the inferior colliculus (ICcc). The actual locus of the computation of the ITD is before ICcc in the nucleus laminaris (NL), and ICcc receives no inputs carrying information that did not originate in NL. Unlike in NL, the rate-ITD functions of ICcc neurons require as little as a single stimulus presentation per ITD to show coherent ITD tuning. ICcc neurons also displayed a greater dynamic range with a maximal difference in ITD response rates approximately double that seen in NL. These results indicate that ICcc neurons perform a computation functionally analogous to averaging across a population of similarly tuned NL neurons.

Convergence of auditory-nerve fiber projections onto globular bushy cells

Globular bushy cells are a key element of brainstem circuits that mediate the early stages of sound localization. Many of their physiological properties have been attributed to convergence of inputs from the auditory nerve, many of which are large with complex geometry, but the number of these terminals contacting individual cells has not been measured directly. Herein we report, using cats as the experimental model, that this number ranged greatly (9-69) across a population of 12 cells, but over one-half of the cells (seven of 12) received between 15 and 23 inputs. In addition, we provide the first measurements of cell body surface area, which also varies considerably within this population and is uncorrelated with convergence. For one cell, we were able to document axonal structure over a distance greater than 100 microm, between the soma and the location where the axon expanded to its characteristic large diameter. These data were combined with accumulated physiological information on vesicle release, receptor kinetics and voltage-gated ionic conductances, and incorporated into computational models for four cells that are representative of the structural variation within our sample population. This predictive model reveals that basic physiological features, such as precise first spike latencies and peristimulus time histogram shapes, including primary-like with notch and onset-L, can be generated in these cells without including inhibitory inputs. However, phase-locking is not significantly enhanced over auditory-nerve fibers. These combined anatomical and computational approaches reveal additional parameters, such as active zone density, nerve terminal size, numbers and sources of inhibitory inputs and their activity patterns, that must be determined and incorporated into next-generation models to understand the physiology of globular bushy cells.

Response properties of an integrate-and-fire model that receives subthreshold inputs

A computational technique is described for calculation of the interspike interval and poststimulus time histograms for the responses of an integrate-and-fire model to arbitrary inputs. The effects of the model parameters on the response statistics were studied systematically. Specifically, the probability distribution of the membrane potential was calculated as a function of time, and the mean interspike interval and PST histogram were calculated for arbitrary inputs. For stationary inputs, the regularity of the output was studied in detail for various model parameters. For nonstationary inputs, the effects of the model parameters on the output synchronization index were explored. The results show that enhanced synchronization in response to low-frequency stimuli required a large number (n > 25) of weak inputs. Irregular responses and a linear input-output rate relationship required strong (but subthreshold) inputs with a small time constant. A model cell with mixed-amplitude synaptic inputs can respond to stationary inputs irregularly and have enhanced synchronization to nonstationary inputs that are phase-locked to low-frequency inputs. Both of these response properties have been reported for some cells in the ventral cochlear nucleus in the auditory brainstem.

Enhanced temporal response properties of anteroventral cochlear nucleus neurons to broadband noise

Compared with auditory nerve (AN) fibers, trapezoid body (TB) fibers of the cat show enhanced synchronization to low-frequency tones. This phenomenon probably contributes to the high temporal resolution of binaural processing. We examined whether enhanced synchronization also occurs to sustained broadband noise. We recorded responses to a reference Gaussian noise and its polarity-inverted version in the TB of barbiturate-anesthetized cats. From these we constructed shuffled autocorrelograms (SACs) and quantified spike timing by measuring the amplitude and width of their central peak. Many TB fibers with low characteristic frequency (CF) showed SACs with higher and narrower central peaks than ever observed in the AN, indicating better consistency and precision of temporal coding. Larger peaks were also observed in TB fibers with high CF, but this was mostly caused by higher average firing rates, resulting in a larger number of coincident spikes across stimulus repetitions. The results document monaural preprocessing of the temporal information delivered to binaural nuclei in the olivary complex, which likely contributes to the high sensitivity to interaural time differences.