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Sound localization requires comparison between the inputs to the left and right ears. One important aspect of this comparison is the differences in arrival time to each side, also called interaural time difference (ITD).A prevalent model of ITD detection, consisting of delay lines and coincidence-detector neurons, was proposed by Jeffress (J Comp Physiol Psychol 41:35–39, 1948). As an extension of the Jeffress model, the process of detecting and encoding ITD has been compared to an effective cross-correlation between the input signals to the two ears. Because the cochlea performs a spectrotemporal decomposition of the input signal, this cross-correlation takes place over narrow frequency bands. Since the cochlear tonotopy is arranged in series, sounds of different frequencies will trigger neural activity with different temporal delays. Thus, the matching of the frequency tuning of the left and right inputs to the cross-correlator units becomes a ‘timing’ issue. These properties of auditory transduction gave theoretical support to an alternative model of ITD-detection based on a bilateral mismatch in frequency tuning, called the ‘stereausis’ model. Here we first review the current literature on the owl’s nucleus laminaris, the equivalent to the medial superior olive of mammals, which is the site where ITD is detected. Subsequently, we use reverse correlation analysis and stimulation with uncorrelated sounds to extract the effective monaural inputs to the cross-correlator neurons. We show that when the left and right inputs to the cross-correlators are defined in this manner, the computation performed by coincidence-detector neurons satisfies conditions of cross-correlation theory. We also show that the spectra of left and right inputs are matched, which is consistent with predictions made by the classic model put forth by Jeffress.

Performing sound recognition is a task that requires an encoding of the time-varying spectral structure of the auditory stimulus. Similarly, computation of the interaural time difference (ITD) requires knowledge of the precise timing of the stimulus. Consistent with this, low-level nuclei of birds and mammals implicated in ITD processing encode the ongoing phase of a stimulus. However, the brain areas that follow the binaural convergence for the computation of ITD show a reduced capacity for phase locking. In addition, we have shown that in the barn owl there is a pooling of ITD-responsive neurons to improve the reliability of ITD coding. Here we demonstrate that despite two stages of convergence and an effective loss of phase information, the auditory system of the anesthetized barn owl displays a graceful transition to an envelope coding that preserves the spectrotemporal information throughout the ITD pathway to the neurons of the core of the central nucleus of the inferior colliculus.

The interaural time difference (ITD) is a major cue to sound localization along the horizontal plane. The maximum natural ITD occurs when a sound source is positioned opposite to one ear. We examined the ability of owls and humans to detect large ITDs in sounds presented through headphones. Stimuli consisted of either broad or narrow bands of Gaussian noise, 100 ms in duration. Using headphones allowed presentation of ITDs that are greater than the maximum natural ITD. Owls were able to discriminate a sound leading to the left ear from one leading to the right ear, for ITDs that are 5 times the maximum natural delay. Neural recordings from optic-tectum neurons, however, show that best ITDs are usually well within the natural range and are never as large as ITDs that are behaviorally discriminable. A model of binaural cross-correlation with short delay lines is shown to explain behavioral detection of large ITDs. The model uses curved trajectories of a cross-correlation pattern as the basis for detection. These trajectories represent side peaks of neural ITD-tuning curves and successfully predict localization reversals by both owls and human subjects.

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.

Space-specific neurons in the barn owl’s auditory space map gain spatial selectivity through tuning to combinations of the interaural time difference (ITD) and interaural level difference (ILD). The combination of ITD and ILD in the subthreshold responses of space-specific neurons in the external nucleus of the inferior colliculus (ICx) is well described by a multiplication of ITD- and ILD-dependent components. It is unknown, however, how ITD and ILD are combined at the site of ITD and ILD convergence in the lateral shell of the central nucleus of the inferior colliculus (ICcl) and therefore whether ICx is the first site in the auditory pathway where multiplicative tuning to ITD-and ILD-dependent signals occurs. We used extracellular re-cording of single neurons to determine how ITD and ILD are combined in ICcl of the anesthetized barn owl (Tyto alba). A comparison of additive, multiplicative, and linear-threshold models of neural responses shows that ITD and ILD are combined nonlinearly in ICcl, but the interaction of ITD and ILD is not uniformly multiplicative over the sample. A subset (61%) of the neural responses is well described by the multiplicative model, indicating that ICcl is the first site where multiplicative tuning to ITD- and ILD-dependent signals occurs. ICx, however, is the first site where multiplicative tuning is observed consistently. A network model shows that a linear combination of ICcl responses to ITD–ILD pairs is sufficient to produce the multiplicative subthreshold responses to ITD and ILD seen in ICx.

Understanding binaural perception requires detailed analyses of the neural circuitry responsible for the computation of interaural time differences (ITDs). In the avian brainstem, this circuit consists of internal axonal delay lines innervating an array of coincidence detector neurons that encode external ITDs. Nucleus magnocellularis (NM) neurons project to the dorsal dendritic field of the ipsilateral nucleus laminaris (NL) and to the ventral field of the contralateral NL. Contralateral-projecting axons form a delay line system along a band of NL neurons. Binaural acoustic signals in the form of phase-locked action potentials from NM cells arrive at NL and establish a topographic map of sound source location along the azimuth. These pathways are assumed to represent a circuit similar to the Jeffress model of sound localization, establishing a place code along an isofrequency contour of NL. Three-dimensional measurements of axon lengths reveal major discrepancies with the current model; the temporal offset based on conduction length alone makes encoding of physiological ITDs impossible. However, axon diameter and distances between Nodes of Ranvier also influence signal propagation times along an axon. Our measurements of these parameters reveal that diameter and internode distance can compensate for the temporal offset inferred from axon lengths alone. Together with other recent studies these unexpected results should inspire new thinking on the cellular biology, evolution and plasticity of the circuitry underlying low frequency sound localization in both birds and mammals.

A multiplicative combination of tuning to interaural time difference (ITD) and interaural level difference (ILD) contributes to the generation of spatially selective auditory neurons in the owl's midbrain. Previous analyses of multiplicative responses in the owl have not taken into consideration the frequency-dependence of ITD and ILD cues that occur under natural listening conditions. Here, we present a model for the responses of ITD- and ILD-sensitive neurons in the barn owl's inferior colliculus which satisfies constraints raised by experimental data on frequency convergence, multiplicative interaction of ITD and ILD, and response properties of afferent neurons. We propose that multiplication between ITD- and ILD-dependent signals occurs only within frequency channels and that frequency integration occurs using a linear-threshold mechanism. The model reproduces the experimentally observed nonlinear responses to ITD and ILD in the inferior colliculus, with greater accuracy than previous models. We show that linear-threshold frequency integration allows the system to represent multiple sound sources with natural sound localization cues, whereas multiplicative frequency integration does not. Nonlinear responses in the owl's inferior colliculus can thus be generated using a combination of cellular and network mechanisms, showing that multiple elements of previous theories can be combined in a single system.

The auditory systems of birds and mammals use timing information from each ear to detect interaural time difference (ITD). To determine whether the Jeffress-type algorithms that underlie sensitivity to ITD in birds are an evolutionarily stable strategy, we recorded from the auditory nuclei of crocodilians, who are the sister group to the birds. In alligators, precisely timed spikes in the first-order nucleus magnocellularis (NM) encode the timing of sounds, and NM neurons project to neurons in the nucleus laminaris (NL) that detect interaural time differences. In vivo recordings from NL neurons show that the arrival time of phase-locked spikes differs between the ipsilateral and contralateral inputs. When this disparity is nullified by their best ITD, the neurons respond maximally. Thus NL neurons act as coincidence detectors. A biologically detailed model of NL with alligator parameters discriminated ITDs up to 1 kHz. The range of best ITDs represented in NL was much larger than in birds, however, and extended from 0 to 1000 μs contralateral, with a median ITD of 450 μs. Thus, crocodilians and birds employ similar algorithms for ITD detection, although crocodilians have larger heads.

Bilateral cochlear implantation attempts to increase performance over a monaural prosthesis by harnessing the binaural processing of the auditory system. Although many bilaterally implanted human subjects discriminate interaural time differences (ITDs), a major cue for sound localization and signal detection in noise, their performance is typically poorer than that of normal-hearing listeners. We developed an animal model of bilateral cochlear implantation to study neural ITD sensitivity for trains of electric current pulses delivered via bilaterally implanted intracochlear electrodes. We found that a majority of single units in the inferior colliculus of acutely deafened, anesthetized cats are sensitive to ITD and that electric ITD tuning is as sharp as found for acoustic stimulation with broadband noise in normal-hearing animals. However, the sharpness and shape of ITD tuning often depended strongly on stimulus intensity; some neurons had dynamic ranges of ITD sensitivity as low as 1 dB. We also found that neural ITD sensitivity was best at pulse rates below 100 Hz and decreased with increasing pulse rate. This rate limitation parallels behavioral ITD discrimination in bilaterally implanted individuals. The sharp neural ITD sensitivity found with electric stimulation at the appropriate intensity is encouraging for the prospect of restoring the functional benefits of binaural hearing in bilaterally implanted human subjects and suggests that neural plasticity resulting from previous deafness and deprivation of binaural experience may play a role in the poor ITD discrimination with current bilateral implants.

Interaural time difference (ITD) is a cue to the location of sounds containing low frequencies and is represented in the inferior colliculus (IC) by cells that respond maximally at a particular best delay (BD). Previous studies have demonstrated that single ITD-sensitive cells contain sufficient information in their discharge patterns to account for ITD acuity on the midline (ITD = 0). If ITD discrimination were based on the activity of the most sensitive cell available (“lower envelope hypothesis”), then ITD acuity should be relatively constant as a function of ITD. In response to broadband noise, however, the ITD acuity of human listeners degrades as ITD increases. To account for these results, we hypothesize that pooling of information across neurons is an essential component of ITD discrimination. This report describes a neural pooling model of ITD discrimination based on the response properties of ITD-sensitive cells in the IC of anesthetized cats.

Rate versus ITD curves were fit with a cross-correlation model of ITD sensitivity, and the parameters were used to constrain a population model of ITD discrimination. The model accurately predicts ITD acuity as a function of ITD for broadband noise stimuli when responses are pooled across best frequency (BF). Furthermore, ITD tuning based solely on a system of internal delays is not sufficient to predict ITD acuity in response to 500 Hz tones, suggesting that acuity is likely refined by additional mechanisms. The physiological data confirms evidence from the guinea pig that BD varies systematically with BF, generalizing the observation across species.

We used in vivo voltage-sensitive dye optical imaging to examine the cortical representation of interaural time difference (ITD), which is believed to be involved in sound source localization. We found that acoustic stimuli with dissimilar ITD activate various localized domains in the auditory cortex. The main loci of the activation pattern shift up to 1 mm during the first 40 ms of the response period. We suppose that some of the neurons in each pool are sensitive to the definite ITD and involved in the transduction of information about sound source localization, based on the ITD. This assumption gives a reasonable fit to the Jeffress model in which the neural network calculates the ITD to define the direction of the sound source. Such calculation forms the basis for the cortex's ability to detect the azimuth of the sound source.

Many animals use the interaural time differences (ITDs) to locate the source of low frequency sounds. The place coding theory proposed by Jeffress has long been a dominant model to account for the neural mechanisms of ITD detection. Recent research, however, suggests a wider range of strategies for ITD coding in the binaural auditory brainstem. We discuss how ITD is coded in avian, mammalian, and reptilian nervous systems, and review underlying synaptic and cellular properties that enable precise temporal computation. The latest advances in recording and analysis techniques provide powerful tools for both overcoming and utilizing the large field potentials in these nuclei.

Initial analysis of interaural temporal disparities (ITDs), a cue for sound localization, occurs in the superior olivary complex. The medial superior olive (MSO) receives excitatory input from the left and right cochlear nuclei. Its neurons are believed to be coincidence detectors, discharging when input arrives simultaneously from the two sides. Many current psychophysical models assume a strict version of coincidence, in which neurons of the MSO cross correlate their left and right inputs. However, there have been few tests of this assumption. Here we examine data derived from two earlier studies of the MSO and compare the responses to the output of a computational model. We find that the MSO is not an ideal cross correlator. Ideal cross correlation implies a strict relationship between the precision of phase-locking of the inputs and the range of ITDs to which a neuron responds. This relationship does not appear to be met. Instead, the modeling implies that a neuron responds over a wider range of ITDs than expected from the inferred precision of phase-locking of the inputs. The responses are more consistent with a scheme in which the neuron can also be activated by the input from one side alone. Such activation degrades the tuning of neurons in the MSO to ITDs.

The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways.

The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways.

Bilateral cochlear implantation seeks to improve hearing by taking advantage of the binaural processing of the central auditory system. Cochlear implants typically encode sound in each spectral channel by amplitude modulating (AM) a fixed-rate pulse train, thus interaural time differences (ITD) are only delivered in the envelope. We investigated the ITD sensitivity of inferior colliculus (IC) neurons with sinusoidally AM pulse trains. ITD was introduced independently to the AM and/or carrier pulses to measure the relative efficacy of envelope and fine structure for delivering ITD information. We found that many IC cells are sensitive to ITD in both the envelope (ITDenv) and fine structure (ITDfs) for appropriate modulation frequencies and carrier rates. ITDenv sensitivity was generally similar to that seen in normal-hearing animals with AM tones. ITDenv tuning generally improved with increasing modulation frequency up to the maximum modulation frequency that elicited a sustained response in a neuron (tested ≤Hz). ITDfs sensitivity was present in about half the neurons for 1,000 pulse/s (pps) carriers and was nonexistent at 5,000 pps. The neurons that were sensitive to ITDfs at 1,000 pps were those that showed the best ITD sensitivity to low-rate pulse trains. Overall, the best ITD sensitivity was found for ITD contained in the fine structure of a moderate rate AM pulse train (1,000 pps). These results suggest that the interaural timing of current pulses should be accurately controlled in a bilateral cochlear implant processing strategy that provides salient ITD cues.

In models of temporal processing, time delays incurred by axonal propagation of action potentials play a prominent role. A preeminent model of temporal processing in audition is the binaural model of Jeffress (1948), which has dominated theories regarding our acute sensitivity to interaural time differences (ITDs). In Jeffress’ model a binaural cell is maximally active when the ITD is compensated by an internal delay, which brings the inputs from left and right ears in coincidence, and which would arise from axonal branching patterns of monaural input fibers. By arranging these patterns in systematic and opposite ways for the ipsi- and contralateral inputs, a range of length differences, and thereby of internal delays, is created so that ITD is transformed into a spatial activation pattern along the binaural nucleus. We reanalyze single, labeled and physiologically characterized, axons of spherical bushy cells of the cat anteroventral cochlear nucleus (AVCN) which project to binaural coincidence detectors in the medial superior olive (MSO). The reconstructions largely confirm the observations of two previous reports, but several features are observed which are inconsistent with Jeffress’ model. We found that ipsilateral projections can also form a caudally-directed delay line pattern, which would counteract delays incurred by caudally-directed contralateral projections. Comparisons of estimated axonal delays with binaural physiological data indicate that the suggestive anatomical patterns cannot account for the frequency-dependent distribution of best delays in the cat. Surprisingly, the tonotopic distribution of the afferents endings indicate that low CFs are under- rather than overrepresented in the MSO.

A biologically detailed model of the binaural avian nucleus laminaris is constructed, as a two-dimensional array of multicompartment, conductance-based neurons, along tonotopic and interaural time delay (ITD) axes. The model is based primarily on data from chick nucleus laminaris. Typical chick-like parameters perform ITD discrimination up to 2 kHz, and enhancements for barn owl perform ITD discrimination up to 6 kHz. The dendritic length gradient of NL is explained concisely. The response to binaural out-of-phase input is suppressed well below the response to monaural input (without any spontaneous activity on the opposite side), implicating active potassium channels as crucial to good ITD discrimination.

The barn owl is a well-known model system for studying auditory processing and sound localization. This article reviews the morphological and functional organization, as well as the role of the underlying microcircuits, of the barn owl's inferior colliculus (IC). We focus on the processing of frequency and interaural time (ITD) and level differences (ILD). We first summarize the morphology of the sub-nuclei belonging to the IC and their differentiation by antero- and retrograde labeling and by staining with various antibodies. We then focus on the response properties of neurons in the three major sub-nuclei of IC [core of the central nucleus of the IC (ICCc), lateral shell of the central nucleus of the IC (ICCls), and the external nucleus of the IC (ICX)]. ICCc projects to ICCls, which in turn sends its information to ICX. The responses of neurons in ICCc are sensitive to changes in ITD but not to changes in ILD. The distribution of ITD sensitivity with frequency in ICCc can only partly be explained by optimal coding. We continue with the tuning properties of ICCls neurons, the first station in the midbrain where the ITD and ILD pathways merge after they have split at the level of the cochlear nucleus. The ICCc and ICCls share similar ITD and frequency tuning. By contrast, ICCls shows sigmoidal ILD tuning which is absent in ICCc. Both ICCc and ICCls project to the forebrain, and ICCls also projects to ICX, where space-specific neurons are found. Space-specific neurons exhibit side peak suppression in ITD tuning, bell-shaped ILD tuning, and are broadly tuned to frequency. These neurons respond only to restricted positions of auditory space and form a map of two-dimensional auditory space. Finally, we briefly review major IC features, including multiplication-like computations, correlates of echo suppression, plasticity, and adaptation.

In order to localize sounds in the environment, the auditory system detects and encodes differences in signals between each ear. The exquisite sensitivity of auditory brain stem neurons to the differences in rise time of the excitation signals from the two ears allows for neuronal encoding of microsecond interaural time differences.

Low-frequency sound localization depends on the neural computation of interaural time differences (ITD) and relies on neurons in the auditory brain stem that integrate synaptic inputs delivered by the ipsi- and contralateral auditory pathways that start at the two ears. The first auditory neurons that respond selectively to ITD are found in the medial superior olivary nucleus (MSO). We identified a new mechanism for ITD coding using a brain slice preparation that preserves the binaural inputs to the MSO. There was an internal latency difference for the two excitatory pathways that would, if left uncompensated, position the ITD response function too far outside the physiological range to be useful for estimating ITD. We demonstrate, and support using a biophysically based computational model, that a bilateral asymmetry in excitatory post-synaptic potential (EPSP) slopes provides a robust compensatory delay mechanism due to differential activation of low threshold potassium conductance on these inputs and permits MSO neurons to encode physiological ITDs. We suggest, more generally, that the dependence of spike probability on rate of depolarization, as in these auditory neurons, provides a mechanism for temporal order discrimination between EPSPs.

Author Summary

Animals can locate the source of a sound by detecting microsecond differences in the arrival time of sound at the two ears. Neurons encoding these interaural time differences (ITDs) receive an excitatory synaptic input from each ear. They can perform a microsecond computation with excitatory synapses that have millisecond time scale because they are extremely sensitive to the input's “rise time,” the time taken to reach the peak of the synaptic input. Current theories assume that the biophysical properties of the two inputs are identical. We challenge this assumption by showing that the rise times of excitatory synaptic potentials driven by the ipsilateral ear are faster than those driven by the contralateral ear. Further, we present a computational model demonstrating that this disparity in rise times, together with the neurons' sensitivity to excitation's rise time, can endow ITD-encoding with microsecond resolution in the biologically relevant range. Our analysis also resolves a timing mismatch. The difference between contralateral and ipsilateral latencies is substantially larger than the relevant ITD range. We show how the rise time disparity compensates for this mismatch. Generalizing, we suggest that phasic-firing neurons—those that respond to rapidly, but not to slowly, changing stimuli—are selective to the temporal ordering of brief inputs. In a coincidence-detection computation the neuron will respond more robustly when a faster input leads a slower one, even if the inputs are brief and have similar amplitudes.

Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model.

Author Summary

Neuronal codes are usually studied by estimating how much information the brain activity carries about the stimulus. On a single cell level, the relevant features of neuronal activity such as the firing rate or spike timing are readily available. On a population level, where many neurons together encode a stimulus property, finding the most appropriate activity features is less obvious, particularly because the neurons respond with a huge cell-to-cell variability. Here, using the example of the neuronal representation of interaural time differences, we show that the quality of the population code strongly depends on the assumption — or the model — of the population readout. We argue that invariances are useful constraints to identify “good” population codes. Based on these ideas, we suggest that the representation of interaural time differences serves a two-channel code in which the difference between the summed activities of the neurons in the two hemispheres exhibits an invariant and linear dependence on interaural time difference.

Barn owls are capable of great accuracy in detecting the interaural time differences (ITDs) that underlie azimuthal sound localization. They compute ITDs in a circuit in nucleus laminaris (NL) that is reorganized with respect to birds like the chicken. The events that lead to the reorganization of the barn owl NL take place during embryonic development, shortly after the cochlear and laminaris nuclei have differentiated morphologically. At first the developing owl’s auditory brainstem exhibits morphology reminiscent of that of the developing chicken. Later, the two systems diverge, and the owl’s brainstem auditory nuclei undergo a secondary morphogenetic phase during which NL dendrites retract, the laminar organization is lost, and synapses are redistributed. These events lead to the restructuring of the ITD coding circuit and the consequent reorganization of the hindbrain map of ITDs and azimuthal space.

The brainstem auditory pathway is obligatory for all aural information. Brainstem auditory neurons must encode the level and timing of sounds, as well as their time-dependent spectral properties, the fine structure and envelope, which are essential for sound discrimination. This study focused on envelope coding in the two cochlear nuclei of the barn owl, nucleus angularis (NA) and nucleus magnocellularis (NM). NA and NM receive input from bifurcating auditory nerve fibers and initiate processing pathways specialized in encoding interaural time (ITD) and level (ILD) differences, respectively. We found that NA neurons, though unable to accurately encode stimulus phase, lock more strongly to the stimulus envelope than NM units. The spectrotemporal receptive fields (STRFs) of NA neurons exhibit a pre-excitatory suppressive field. Using multilinear regression analysis and computational modeling, we show that this feature of STRFs can account for enhanced across-trial response reliability, by locking spikes to the stimulus envelope. Our findings indicate a dichotomy in envelope coding between the time and intensity processing pathways as early as at the level of the cochlear nuclei. This allows the ILD processing pathway to encode envelope information with greater fidelity than the ITD processing pathway. Furthermore, we demonstrate that the properties of the neurons’ STRFs can be quantitatively related to spike timing reliability.

Binaural signal detection in an NoSπ task relies on interaural disparities introduced by adding an antiphasic signal to diotic noise. What metric of interaural disparity best predicts performance? Some models use interaural correlation; others differentiate between dynamic interaural time differences (ITDs) and interaural level differences (ILDs) of the effective stimulus. To examine the relative contributions of ITDs and ILDs in binaural detection, we developed a novel signal processing technique that selectively degrades different aspects (potential cues) of binaural stimuli (e.g., only ITDs are scrambled). Degrading a particular cue will affect performance only if that cue is relevant to the binaural processing underlying detection. This selective scrambling technique was applied to the stimuli of a classic N0Sπ task in which the listener had to detect an antiphasic 500-Hz signal in the presence of a diotic wideband noise masker. Data obtained from five listeners showed that (1) selective scrambling of ILDs had little effect on binaural detection, (2) selective scrambling of ITDs significantly degraded detection, and (3) combined scrambling of ILDs and ITDs had the same effect as exclusive scrambling of ITDs. Regarding the question which stimulus properties determine detection, we conclude that for this binaural task (1) dynamic ITDs dominate detection performance, (2) ILDs are largely irrelevant, and (3) interaural correlation of the stimulus is a poor predictor of detection. Two simple stimulus-based models that each reproduce all binaural aspects of the data quite well are described: (1) a single-parameter detection model using ITD variance as detection criterion and (2) a compressive transformation followed by a crosscorrelation analysis. The success of both of these contrasting models shows that our data alone cannot reveal the mechanisms underlying the dominance of ITD cues. The physiological implications of our findings are discussed.

Binaural signal detection in an NoSπ task relies on interaural disparities introduced by adding an antiphasic signal to diotic noise. What metric of interaural disparity best predicts performance? Some models use interaural correlation; others differentiate between dynamic interaural time differences (ITDs) and interaural level differences (ILDs) of the effective stimulus. To examine the relative contributions of ITDs and ILDs in binaural detection, we developed a novel signal processing technique that selectively degrades different aspects (potential cues) of binaural stimuli (e.g., only ITDs are scrambled). Degrading a particular cue will affect performance only if that cue is relevant to the binaural processing underlying detection. This selective scrambling technique was applied to the stimuli of a classic N0Sπ task in which the listener had to detect an antiphasic 500-Hz signal in the presence of a diotic wideband noise masker. Data obtained from five listeners showed that (1) selective scrambling of ILDs had little effect on binaural detection, (2) selective scrambling of ITDs significantly degraded detection, and (3) combined scrambling of ILDs and ITDs had the same effect as exclusive scrambling of ITDs. Regarding the question which stimulus properties determine detection, we conclude that for this binaural task (1) dynamic ITDs dominate detection performance, (2) ILDs are largely irrelevant, and (3) interaural correlation of the stimulus is a poor predictor of detection. Two simple stimulus-based models that each reproduce all binaural aspects of the data quite well are described: (1) a single-parameter detection model using ITD variance as detection criterion and (2) a compressive transformation followed by a crosscorrelation analysis. The success of both of these contrasting models shows that our data alone cannot reveal the mechanisms underlying the dominance of ITD cues. The physiological implications of our findings are discussed.