Coding interaural time differences at low best frequencies in the barn owl

Theoretical Relationship Between Two Measures of Spike Synchrony: Correlation Index and Vector Strength

Information processing in the nervous system critically relies on temporally precise spiking activity. In the auditory system, various degrees of phase-locking can be observed from the auditory nerve to cortical neurons. The classical metric for quantifying phase-locking is the vector strength (VS), which captures the periodicity in neuronal spiking. More recently, another metric, called the correlation index (CI), was proposed to quantify the temporally reproducible response characteristics of a neuron. The CI is defined as the peak value of a normalized shuffled autocorrelogram (SAC). Both VS and CI have been used to investigate how temporal information is processed and propagated along the auditory pathways. While previous analyses of physiological data in cats suggested covariation of these two metrics, general characterization of their connection has never been performed. In the present study, we derive a rigorous relationship between VS and CI. To model phase-locking, we assume Poissonian spike trains with a temporally changing intensity function following a von Mises distribution. We demonstrate that VS and CI are mutually related via the so-called concentration parameter that determines the degree of phase-locking. We confirm that these theoretical results are largely consistent with physiological data recorded in the auditory brainstem of various animals. In addition, we generate artificial phase-locked spike sequences, for which recording and analysis parameters can be systematically manipulated. Our analysis results suggest that mismatches between empirical data and the theoretical prediction can often be explained with deviations from the von Mises distribution, including skewed or multimodal period histograms. Furthermore, temporal relations of spike trains across trials can contribute to higher CI values than predicted mathematically based on the VS. We find that, for most applications, a SAC bin width of 50 ms seems to be a favorable choice, leading to an estimated error below 2.5% for physiologically plausible conditions. Overall, our results provide general relations between the two measures of phase-locking and will aid future analyses of different physiological datasets that are characterized with these metrics.

Cooperativity of Kv7.4 channels confers ultrafast electromechanical sensitivity and emergent properties in cochlear outer hair cells

The mammalian cochlea relies on active electromotility of outer hair cells (OHCs) to resolve sound frequencies. OHCs use ionic channels and somatic electromotility to achieve the process. It is unclear, though, how the kinetics of voltage-gated ionic channels operate to overcome extrinsic viscous drag on OHCs at high frequency. Here, we report ultrafast electromechanical gating of clustered K_v7.4 in OHCs. Increases in kinetics and sensitivity resulting from cooperativity among clustered-K_v7.4 were revealed, using optogenetics strategies. Upon clustering, the half-activation voltage shifted negative, and the speed of activation increased relative to solitary channels. Clustering also rendered K_v7.4 channels mechanically sensitive, confirmed in consolidated K_v7.4 channels at the base of OHCs. K_v7.4 clusters provide OHCs with ultrafast electromechanical channel gating, varying in magnitude and speed along the cochlea axis. Ultrafast K_v7.4 gating provides OHCs with a feedback mechanism that enables the cochlea to overcome viscous drag and resolve sounds at auditory frequencies.

The barn owls' Minimum Audible Angle

Interaural time differences (ITD) and interaural level differences (ILD) are physical cues that enable the auditory system to pinpoint the position of a sound source in space. This ability is crucial for animal communication and predator-prey interactions. The barn owl has evolved an exceptional sense of hearing and shows abilities of sound localisation that outperform most other species. So far, behavioural studies in the barn owl often used reflexive responses to investigate aspects of sound localisation. Furthermore, they predominately probed the higher frequencies of the owl's hearing range (> 3 kHz). In the present study we used a Go/NoGo paradigm to measure the barn owl's behavioural sound localisation acuity (expressed as the Minimum Audible Angle, MAA) as a function of stimulus type (narrow-band noise centred at 500, 1000, 2000, 4000 and 8000 Hz, and broad-band noise) and sound source position. We found significant effects of both stimulus type and sound source position on the barn owls' MAA. The MAA improved with increasing stimulus frequency, from 14° at 500 Hz to 6° at 8000 Hz. The smallest MAA of 4° was found for broadband noise stimuli. Comparing different sound source positions revealed smaller MAAs for frontal compared to lateral stimulus presentation, irrespective of stimulus type. These results are consistent with both the known variations in physical ITDs and variation in the width of neural ITD tuning curves with azimuth and frequency. Physical and neural characteristics combine to result in better spatial acuity for frontal compared to lateral sounds and reduced localisation acuity at lower frequencies.

Diverse Intrinsic Properties Shape Functional Phenotype of Low-Frequency Neurons in the Auditory Brainstem

In the auditory system, tonotopy is the spatial arrangement of where sounds of different frequencies are processed. Defined by the organization of neurons and their inputs, tonotopy emphasizes distinctions in neuronal structure and function across topographic gradients and is a common feature shared among vertebrates. In this study we characterized action potential firing patterns and ion channel properties from neurons located in the extremely low-frequency region of the chicken nucleus magnocellularis (NM), an auditory brainstem structure. We found that NM neurons responsible for encoding the lowest sound frequencies (termed NMc neurons) have enhanced excitability and fired bursts of action potentials to sinusoidal inputs ≤10 Hz; a distinct firing pattern compared to higher-frequency neurons. This response property was due to lower amounts of voltage dependent potassium (KV) conductances, unique combination of KV subunits and specialized sodium (NaV) channel properties. Particularly, NMc neurons had significantly lower KV1 and KV3 currents, but higher KV2 current. NMc neurons also showed larger and faster transient NaV current (INaT) with different voltage dependence of inactivation from higher-frequency neurons. In contrast, significantly smaller resurgent sodium current (INaR) was present in NMc with kinetics and voltage dependence that differed from higher-frequency neurons. Immunohistochemistry showed expression of NaV1.6 channel subtypes across the tonotopic axis. However, various immunoreactive patterns were observed between regions, likely underlying some tonotopic differences in INaT and INaR. Finally, using pharmacology and computational modeling, we concluded that KV3, KV2 channels and INaR work synergistically to regulate burst firing in NMc.

Combination of Interaural Level and Time Difference in Azimuthal Sound Localization in Owls

A function of the auditory system is to accurately determine the location of a sound source. The main cues for sound location are interaural time (ITD) and level (ILD) differences. Humans use both ITD and ILD to determine the azimuth. Thus far, the conception of sound localization in barn owls was that their facial ruff and asymmetrical ears generate a two-dimensional grid of ITD for azimuth and ILD for elevation. We show that barn owls also use ILD for azimuthal sound localization when ITDs are ambiguous. For high-frequency narrowband sounds, midbrain neurons can signal multiple locations, leading to the perception of an auditory illusion called a phantom source. Owls respond to such an illusory percept by orienting toward it instead of the true source. Acoustical measurements close to the eardrum reveal a small ILD component that changes with azimuth, suggesting that ITD and ILD information could be combined to eliminate the illusion. Our behavioral data confirm that perception was robust against ambiguities if ITD and ILD information was combined. Electrophysiological recordings of ILD sensitivity in the owl’s midbrain support the behavioral findings indicating that rival brain hemispheres drive the decision to orient to either true or phantom sources. Thus, the basis for disambiguation, and reliable detection of sound source azimuth, relies on similar cues across species as similar response to combinations of ILD and narrowband ITD has been observed in humans.

Coupled ears in lizards and crocodilians

Lizard ears are coupled across the pharynx, and are very directional. In consequence all auditory responses should be directional, without a requirement for computation of sound source location. Crocodilian ears are connected through sinuses, and thus less tightly coupled. Coupling may improve the processing of low-frequency directional signals, while higher frequency signals appear to be progressively uncoupled. In both lizards and crocodilians, the increased directionality of the coupled ears leads to an effectively larger head and larger physiological range of ITDs. This increased physiological range is reviewed in the light of current theories of sound localization.

The Binaural Interaction Component in Barn Owl (Tyto alba) Presents few Differences to Mammalian Data

The auditory brainstem response (ABR) is an evoked potential that reflects the responses to sound by brainstem neural centers. The binaural interaction component (BIC) is obtained by subtracting the sum of the monaural ABR responses from the binaural response. Its latency and amplitude change in response to variations in binaural cues. The BIC is thus thought to reflect the activity of binaural nuclei and is used to non-invasively test binaural processing. However, any conclusions are limited by a lack of knowledge of the relevant processes at the level of individual neurons. The aim of this study was to characterize the ABR and BIC in the barn owl, an animal where the ITD-processing neural circuits are known in great detail. We recorded ABR responses to chirps and to 1 and 4 kHz tones from anesthetized barn owls. General characteristics of the barn owl ABR were similar to those observed in other bird species. The most prominent peak of the BIC was associated with nucleus laminaris and is thus likely to reflect the known processes of ITD computation in this nucleus. However, the properties of the BIC were very similar to previously published mammalian data and did not reveal any specific diagnostic features. For example, the polarity of the BIC was negative, which indicates a smaller response to binaural stimulation than predicted by the sum of monaural responses. This is contrary to previous predictions for an excitatory-excitatory system such as nucleus laminaris. Similarly, the change in BIC latency with varying ITD was not distinguishable from mammalian data. Contrary to previous predictions, this behavior appears unrelated to the known underlying neural delay-line circuitry. In conclusion, the generation of the BIC is currently inadequately understood and common assumptions about the BIC need to be reconsidered when interpreting such measurements.

In vivo Recordings from Low-Frequency Nucleus Laminaris in the Barn Owl

Localization of sound sources relies on 2 main binaural cues: interaural time differences (ITD) and interaural level differences. ITD computing is first carried out in tonotopically organized areas of the brainstem nucleus laminaris (NL) in birds and the medial superior olive (MSO) in mammals. The specific way in which ITD are derived was long assumed to conform to a delay line model in which arrays of systematically arranged cells create a representation of auditory space, with different cells responding maximally to specific ITD. This model conforms in many details to the particular case of the high-frequency regions (above 3 kHz) in the barn owl NL. However, data from recent studies in mammals are not consistent with a delay line model. A new model has been suggested in which neurons are not topographically arranged with respect to ITD and coding occurs through assessment of the overall response of 2 large neuron populations – 1 in each brainstem hemisphere. Currently available data comprise mainly low-frequency (<1,500 Hz) recordings in the case of mammals and higher-frequency recordings in the case of birds. This makes it impossible to distinguish between group-related adaptations and frequency-related adaptations. Here we report the first comprehensive data set from low-frequency NL in the barn owl and compare it to data from other avian and mammalian studies. Our data are consistent with a delay line model, so differences between ITD processing systems are more likely to have originated through divergent evolution of different vertebrate groups.

Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245-15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

Synaptic morphology and the influence of auditory experience

The auditory experience is crucial for the normal development and maturation of brain structure and the maintenance of the auditory pathways. The specific aims of this review are (i) to provide a brief background of the synaptic morphology of the endbulb of Held in hearing and deaf animals; (ii) to argue the importance of this large synaptic ending in linking neural activity along ascending pathways to environmental acoustic events; (iii) to describe how the re-introduction of electrical activity changes this synapse; and (iv) to examine how changes at the endbulb synapse initiate trans-synaptic changes in ascending auditory projections to the superior olivary complex, the inferior complex, and the auditory cortex.

Perception of auditory signals

Auditory signals are decomposed into discrete frequency elements early in the transduction process, yet somehow these signals are recombined into the rich acoustic percepts that we readily identify and are familiar with. The cerebral cortex is necessary for the perception of these signals, and studies from several laboratories over the past decade have made significant advances in our understanding of the neuronal mechanisms underlying auditory perception. This review will concentrate on recent studies in the macaque monkey that indicate that the activity of populations of neurons better accounts for the perceptual abilities compared to the activity of single neurons. The best examples address whether the acoustic space is represented along the "where" pathway in the caudal regions of auditory cortex. Our current understanding of how such population activity could also underlie the perception of the nonspatial features of acoustic stimuli is reviewed, as is how multisensory interactions can influence our auditory perception.

The biological basis of audition

Audition is one of the fundamental extrasensory percepts in mammals. Two of the primary objectives of audition are to determine where sounds originate from in space and what those sounds are. Neural processing of acoustic signals, which are commonly quite complex under natural conditions, is extensive in the brainstem, midbrain, and thalamus. This processing extracts multiple salient features that are then transmitted to the cerebral cortex. The cerebral cortex is a necessary neural structure for audition, or the perception of acoustic auditory objects and/or events. This entry will review the early processing along the ascending auditory central nervous system from the cochlea to the cerebral cortex. The neural mechanisms of audition will then be explored for spatial and non-spatial perception, drawing largely on examples from non-human primates, but insights gained from other mammalian species will also be covered. How these models relate to current studies in human subjects, using both functional imaging and invasive techniques, will also be explored as well as the types of future studies that will enable us to better understand the neural mechanisms of audition. WIREs Cogni Sci 2011 2 408-418 DOI: 10.1002/wcs.118 For further resources related to this article, please visit the WIREs website.

Estimated Cochlear Delays in Low Best-Frequency Neurons in the Barn Owl Cannot Explain Coding of Interaural Time Difference

The functional role of the low-frequency range (<3 kHz) in barn owl hearing is not well understood. Here, it was tested whether cochlear delays could explain the representation of interaural time difference (ITD) in this frequency range. Recordings were obtained from neurons in the core of the central nucleus of the inferior colliculus. The response of these neurons varied with the ITD of the stimulus. The response peak shared by all neurons in a dorsoventral penetration was called the array-specific ITD and served as criterion for the representation of a given ITD in a neuron. Array-specific ITDs were widely distributed. Isolevel frequency response functions obtained with binaural, contralateral, and ispilateral stimulation exhibited a clear response peak and the accompanying frequency was called the best frequency. The data were tested with respect to predictions of a model, the stereausis model, assuming cochlear delays as source for the best ITD of a neuron. According to this model, different cochlear delays determined by mismatches between the ipsilateral and contralateral best frequencies are the source for the ITD in a binaural neuron. The mismatch should depend on the best frequency and the best ITD. The predictions of the stereausis model were not fulfilled in the low best-frequency neurons analyzed here. It is concluded that cochlear delays are not responsible for the representation of best ITD in the barn owl.

Effect of sampling frequency on the measurement of phase-locked action potentials

Phase-locked spikes in various types of neurons encode temporal information. To quantify the degree of phase-locking, the metric called vector strength (VS) has been most widely used. Since VS is derived from spike timing information, error in measurement of spike occurrence should result in errors in VS calculation. In electrophysiological experiments, the timing of an action potential is detected with finite temporal precision, which is determined by the sampling frequency. In order to evaluate the effects of the sampling frequency on the measurement of VS, we derive theoretical upper and lower bounds of VS from spikes collected with finite sampling rates. We next estimate errors in VS assuming random sampling effects, and show that our theoretical calculation agrees with data from electrophysiological recordings in vivo. Our results provide a practical guide for choosing the appropriate sampling frequency in measuring VS.

Maps of interaural time difference in the chicken's brainstem nucleus laminaris

Animals, including humans, use interaural time differences (ITDs) that arise from different sound path lengths to the two ears as a cue of horizontal sound source location. The nature of the neural code for ITD is still controversial. Current models differentiate between two population codes: either a map-like rate-place code of ITD along an array of neurons, consistent with a large body of data in the barn owl, or a population rate code, consistent with data from small mammals. Recently, it was proposed that these different codes reflect optimal coding strategies that depend on head size and sound frequency. The chicken makes an excellent test case of this proposal because its physical prerequisites are similar to small mammals, yet it shares a more recent common ancestry with the owl. We show here that, like in the barn owl, the brainstem nucleus laminaris in mature chickens displayed the major features of a place code of ITD. ITD was topographically represented in the maximal responses of neurons along each isofrequency band, covering approximately the contralateral acoustic hemisphere. Furthermore, the represented ITD range appeared to change with frequency, consistent with a pressure gradient receiver mechanism in the avian middle ear. At very low frequencies, below 400 Hz, maximal neural responses were symmetrically distributed around zero ITD and it remained unclear whether there was a topographic representation. These findings do not agree with the above predictions for optimal coding and thus revive the discussion as to what determines the neural coding strategies for ITDs.

The biological basis of audition

Interest has recently surged in the neural mechanisms of audition, particularly with regard to functional imaging studies in human subjects. This review emphasizes recent work on two aspects of auditory processing. The first explores auditory spatial processing and the role of the auditory cortex in both nonhuman primates and human subjects. The interactions with visual stimuli, the ventriloquism effect, and the ventriloquism aftereffect are also reviewed. The second aspect is temporal processing. Studies investigating temporal integration, forward masking, and gap detection are reviewed, as well as examples from the birdsong system and echolocating bats.

Distribution of interaural time difference in the barn owl's inferior colliculus in the low- and high-frequency ranges

Interaural time differences are an important cue for azimuthal sound localization. It is still unclear whether the same neuronal mechanisms underlie the representation in the brain of interaural time difference in different vertebrates and whether these mechanisms are driven by common constraints, such as optimal coding. Current sound localization models may be discriminated by studying the spectral distribution of response peaks in tuning curves that measure the sensitivity to interaural time difference. The sound localization system of the barn owl has been studied intensively, but data that would allow discrimination between currently discussed models are missing from this animal. We have therefore obtained extracellular recordings from the time-sensitive subnuclei of the barn owl's inferior colliculus. Response peaks were broadly scattered over the physiological range of interaural time differences. A change in the representation of the interaural phase differences with frequency was not observed. In some neurons, response peaks fell outside the physiological range of interaural time differences. For a considerable number of neurons, the peak closest to zero interaural time difference was not the behaviorally relevant peak. The data are in best accordance with models suggesting that a place code underlies the representation of interaural time difference. The data from the high-frequency range, but not from the low-frequency range, are consistent with predictions of optimal coding. We speculate that the deviation of the representation of interaural time difference from optimal-coding models in the low-frequency range is attributable to the diminished importance of low frequencies for catching prey in this species.