Linear coding of complex sound spectra by discharge rate in neurons of the medial nucleus of the trapezoid body (MNTB) and its inputs

A Developmental Switch in Cholinergic Mechanisms of Modulation in the Medial Nucleus of the Trapezoid Body

The medial nucleus of the trapezoid body (MNTB) has been intensively investigated as a primary source of inhibition in brainstem auditory circuitry. MNTB-derived inhibition plays a critical role in the computation of sound location, as temporal features of sounds are precisely conveyed through the calyx of Held/MNTB synapse. In adult gerbils, cholinergic signaling influences sound-evoked responses of MNTB neurons via nicotinic acetylcholine receptors (nAChRs; Zhang et al., 2021) establishing a modulatory role for cholinergic input to this nucleus. However, the cellular mechanisms through which acetylcholine (ACh) mediates this modulation in the MNTB remain obscure. To investigate these mechanisms, we used whole-cell current and voltage-clamp recordings to examine cholinergic physiology in MNTB neurons from Mongolian gerbils (Meriones unguiculatus) of both sexes. Membrane excitability was assessed in brain slices, in pre-hearing (postnatal days 9-13) and post-hearing onset (P18-20) MNTB neurons during bath application of agonists and antagonists of nicotinic (nAChRs) and muscarinic receptors (mAChRs). Muscarinic activation induced a potent increase in excitability most prominently prior to hearing onset with nAChR modulation emerging at later time points. Pharmacological manipulations further demonstrated that the voltage-gated K+ channel KCNQ (Kv7) is the downstream effector of mAChR activation that impacts excitability early in development. Cholinergic modulation of Kv7 reduces outward K+ conductance and depolarizes resting membrane potential. Immunolabeling revealed expression of Kv7 channels as well as mAChRs containing M1 and M3 subunits. Together, our results suggest that mAChR modulation is prominent but transient in the developing MNTB and that cholinergic modulation functions to shape auditory circuit development.

Multiple Sources of Cholinergic Input to the Superior Olivary Complex

The superior olivary complex (SOC) is a major computation center in the brainstem auditory system. Despite previous reports of high expression levels of cholinergic receptors in the SOC, few studies have addressed the functional role of acetylcholine in the region. The source of the cholinergic innervation is unknown for all but one of the nuclei of the SOC, limiting our understanding of cholinergic modulation. The medial nucleus of the trapezoid body, a key inhibitory link in monaural and binaural circuits, receives cholinergic input from other SOC nuclei and also from the pontomesencephalic tegmentum. Here, we investigate whether these same regions are sources of cholinergic input to other SOC nuclei. We also investigate whether individual cholinergic cells can send collateral projections bilaterally (i.e., into both SOCs), as has been shown at other levels of the subcortical auditory system. We injected retrograde tract tracers into the SOC in gerbils, then identified retrogradely-labeled cells that were also immunolabeled for choline acetyltransferase, a marker for cholinergic cells. We found that both the SOC and the pontomesencephalic tegmentum (PMT) send cholinergic projections into the SOC, and these projections appear to innervate all major SOC nuclei. We also observed a small cholinergic projection into the SOC from the lateral paragigantocellular nucleus of the reticular formation. These various sources likely serve different functions; e.g., the PMT has been associated with things such as arousal and sensory gating whereas the SOC may provide feedback more closely tuned to specific auditory stimuli. Further, individual cholinergic neurons in each of these regions can send branching projections into both SOCs. Such projections present an opportunity for cholinergic modulation to be coordinated across the auditory brainstem.

Endogenous Cholinergic Signaling Modulates Sound-Evoked Responses of the Medial Nucleus of the Trapezoid Body

The medial nucleus of trapezoid body (MNTB) is a major source of inhibition in auditory brainstem circuitry. The MNTB projects well-timed inhibitory output to principal sound-localization nuclei in the superior olive (SOC) as well as other computationally important centers. Acoustic information is conveyed to MNTB neurons through a single calyx of Held excitatory synapse arising from the cochlear nucleus. The encoding efficacy of this large synapse depends on its activity rate, which is primarily determined by sound intensity and stimulus frequency. However, MNTB activity rate is additionally influenced by inhibition and possibly neuromodulatory inputs, albeit their functional role is unclear. Happe and Morley (2004) discovered prominent expression of α7 nAChRs in rat SOC, suggesting possible engagement of ACh-mediated modulation of neural activity in the MNTB. However, the existence and nature of this putative modulation have never been physiologically demonstrated. We probed nicotinic cholinergic influences on acoustic responses of MNTB neurons from adult gerbils (Meriones unguiculatus) of either sex. We recorded tone-evoked MNTB single-neuron activity in vivo using extracellular single-unit recording. Piggyback multibarrel electrodes enabled pharmacological manipulation of nAChRs by reversibly applying antagonists to two receptor types, α7 and α4β2. We observed that tone-evoked responses are dependent on ACh modulation by both nAChR subtypes. Spontaneous activity was not affected by antagonist application. Functionally, we demonstrate that ACh contributes to sustaining high discharge rates and enhances signal encoding efficacy. Additionally, we report anatomic evidence revealing novel cholinergic projections to MNTB arising from pontine and superior olivary nuclei.SIGNIFICANCE STATEMENT This study is the first to physiologically probe how acetylcholine, a pervasive neuromodulator in the brain, influences the encoding of acoustic information by the medial nucleus of trapezoid body, the most prominent source of inhibition in brainstem sound-localization circuitry. We demonstrate that this cholinergic input enhances neural discrimination of tones from noise stimuli, which may contribute to processing important acoustic signals, such as speech. Additionally, we describe novel anatomic projections providing cholinergic input to the MNTB. Together, these findings shed new light on the contribution of neuromodulation to fundamental computational processes in auditory brainstem circuitry and to a more holistic understanding of modulatory influences in sensory processing.

Stimulus-frequency-dependent dominance of sound localization cues across the cochleotopic map of the inferior colliculus

The horizontal direction of a sound source (i.e., azimuth) is perceptually determined in a frequency-dependent manner: low- and high-frequency sounds are localized via differences in the arrival time and intensity of the sound at the two ears, respectively, called interaural time and level differences (ITDs and ILDs). In the central auditory system, these binaural cues to direction are thought to be separately encoded by neurons tuned to low and high characteristic frequencies (CFs). However, at high sound levels a neuron often responds to frequencies far from its CF, raising the possibility that individual neurons may encode the azimuths of both low- and high-frequency sounds using both binaural cues. We tested this possibility by measuring auditory-driven single-unit responses in the central nucleus of the inferior colliculus (ICC) of unanesthetized female Dutch Belted rabbits with a multitetrode drive. At 70 dB SPL, ICC neurons across the cochleotopic map transmitted information in their firing rates about the direction of both low- and high-frequency noise stimuli. We independently manipulated ITD and ILD cues in virtual acoustic space and found that sensitivity to ITD and ILD, respectively, shaped the directional sensitivity of ICC neurons to low (<1.5 kHz)- and high (>3 kHz)-pass stimuli, regardless of the neuron's CF. We also found evidence that high-CF neurons transmit information about both the fine-structure and envelope ITD of low-frequency sound. Our results indicate that at conversational sound levels the majority of the cochleotopic map is engaged in transmitting directional information, even for sources with narrowband spectra.NEW & NOTEWORTHY A "division of labor" has previously been assumed in which the directions of low- and high-frequency sound sources are thought to be encoded by neurons preferentially sensitive to low and high frequencies, respectively. Contrary to this, we found that auditory midbrain neurons encode the directions of both low- and high-frequency sounds regardless of their preferred frequencies. Neural responses were shaped by different sound localization cues depending on the stimulus spectrum-even within the same neuron.

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.

Between-ear sound frequency disparity modulates a brain stem biomarker of binaural hearing

The auditory brain stem response (ABR) is an evoked potential that indexes a cascade of neural events elicited by sound. In the present study we evaluated the influence of sound frequency on a derived component of the ABR known as the binaural interaction component (BIC). Specifically, we evaluated the effect of acoustic interaural (between-ear) frequency mismatch on BIC amplitude. Goals were to 1) increase basic understanding of sound features that influence this long-studied auditory potential and 2) gain insight about the persistence of the BIC with interaural electrode mismatch in human users of bilateral cochlear implants, presently a limitation on the prospective utility of the BIC in audiological settings. Data were collected in an animal model that is audiometrically similar to humans, the chinchilla (Chinchilla lanigera; 6 females). Frequency disparities and amplitudes of acoustic stimuli were varied over broad ranges, and associated variation of BIC amplitude was quantified. Subsequently, responses were simulated with the use of established models of the brain stem pathway thought to underlie the BIC. Collectively, the data demonstrate that at high sound intensities (≥85 dB SPL), the acoustically elicited BIC persisted with interaurally disparate stimulation (click frequencies ≥1.5 octaves apart). However, sharper tuning emerged at moderate sound intensities (65 dB SPL), with the largest BIC occurring for stimulus frequencies within ~0.8 octaves, equivalent to ±1 mm in cochlear place. Such responses were consistent with simulated responses of the presumed brain stem generator of the BIC, the lateral superior olive. The data suggest that leveraging focused electrical stimulation strategies could improve BIC-based bilateral cochlear implant fitting outcomes.NEW & NOTEWORTHY Traditional hearing tests evaluate each ear independently. Diagnosis and treatment of binaural hearing dysfunction remains a basic challenge for hearing clinicians. We demonstrate in an animal model that the prospective utility of a noninvasive electrophysiological signature of binaural function, the binaural interaction component (BIC), depends strongly on the intensity of auditory stimulation. Data suggest that more informative BIC measurements could be obtained with clinical protocols leveraging stimuli restricted in effective bandwidth.

The Physiological Basis and Clinical Use of the Binaural Interaction Component of the Auditory Brainstem Response

The auditory brainstem response (ABR) is a sound-evoked noninvasively measured electrical potential representing the sum of neuronal activity in the auditory brainstem and midbrain. ABR peak amplitudes and latencies are widely used in human and animal auditory research and for clinical screening. The binaural interaction component (BIC) of the ABR stands for the difference between the sum of the monaural ABRs and the ABR obtained with binaural stimulation. The BIC comprises a series of distinct waves, the largest of which (DN1) has been used for evaluating binaural hearing in both normal hearing and hearing-impaired listeners. Based on data from animal and human studies, the authors discuss the possible anatomical and physiological bases of the BIC (DN1 in particular). The effects of electrode placement and stimulus characteristics on the binaurally evoked ABR are evaluated. The authors review how interaural time and intensity differences affect the BIC and, analyzing these dependencies, draw conclusion about the mechanism underlying the generation of the BIC. Finally, the utility of the BIC for clinical diagnoses are summarized.

Test-Retest Reliability of the Binaural Interaction Component of the Auditory Brainstem Response

OBJECTIVES

The binaural interaction component (BIC) is the residual auditory brainstem response (ABR) obtained after subtracting the sum of monaurally evoked from binaurally evoked ABRs. The DN1 peak-the first negative peak of the BIC-has been postulated to have diagnostic value as a biomarker for binaural hearing abilities. Indeed, not only do DN1 amplitudes depend systematically upon binaural cues to location (interaural time and level differences), but they are also predictive of central hearing deficits in humans. A prominent issue in using BIC measures as a diagnostic biomarker is that DN1 amplitudes not only exhibit considerable variability across subjects, but also within subjects across different measurement sessions.

DESIGN

In this study, the authors investigate the DN1 amplitude measurement reliability by conducting repeated measurements on different days in eight adult guinea pigs.

RESULTS

Despite consistent ABR thresholds, ABR and DN1 amplitudes varied between and within subjects across recording sessions. However, the study analysis reveals that DN1 amplitudes varied proportionally with parent monaural ABR amplitudes, suggesting that common experimental factors likely account for the variability in both waveforms. Despite this variability, the authors show that the shape of the dependence between DN1 amplitude and interaural time difference is preserved. The authors then provide a BIC normalization strategy using monaural ABR amplitude that reduces the variability of DN1 peak measurements. Finally, the authors evaluate this normalization strategy in the context of detecting changes of the DN1 amplitude-to-interaural time difference relationship.

CONCLUSIONS

The study results indicate that the BIC measurement variability can be reduced by a factor of two by performing a simple and objective normalization operation. The authors discuss the potential for this normalized BIC measure as a biomarker for binaural hearing.

Physiological models of the lateral superior olive

In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD), which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO) in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi- and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones (‘shot-noise’ models) to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type). These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1) that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2) that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub-neuronal nonlinear processes play important roles, and (3) that, for general purposes, intermediate models might be a reasonable compromise between simplicity and biological plausibility.

Computational models help our understanding of complex biological systems, by identifying their key elements and revealing their operational principles. Close comparisons between model predictions and empirical observations ensure our confidence in a model as a building block for further applications. Most current neuronal models, however, are constructed to replicate only a small specific set of experimental data. Thus, it is usually unclear how these models can be generalized to different datasets and how they compare with each other. In this paper, seven neuronal models are examined that are designed to reproduce known physiological characteristics of auditory neurons involved in the detection of sound source location. Despite their different levels of complexity, the models generate largely similar results when their parameters are tuned with common criteria. Comparisons show that simple models are computationally more efficient and theoretically transparent, and therefore suitable for rigorous mathematical analyses and engineering applications including real-time simulations. In contrast, complex models are necessary for investigating the relationship between underlying biophysical processes and sub- and suprathreshold spiking properties, although they have a large number of unconstrained, unverified parameters. Having identified their advantages and drawbacks, these auditory neuron models may readily be used for future studies and applications.

Recurrent Inhibition to the Medial Nucleus of the Trapezoid Body in the Mongolian Gerbil (Meriones Unguiculatus)

Principal neurons in the medial nucleus of the trapezoid body (MNTB) receive strong and temporally precise excitatory input from globular bushy cells in the cochlear nucleus through the calyx of Held. The extremely large synaptic currents produced by the calyx have sometimes led to the view of the MNTB as a simple relay synapse which converts incoming excitation to outgoing inhibition. However, electrophysiological and anatomical studies have shown the additional presence of inhibitory glycinergic currents that are large enough to suppress action potentials in MNTB neurons at least in some cases. The source(s) of glycinergic inhibition to MNTB are not fully understood. One major extrinsic source of glycinergic inhibitory input to MNTB is the ventral nucleus of the trapezoid body. However, it has been suggested that MNTB neurons receive additional inhibitory inputs via intrinsic connections (collaterals of glycinergic projections of MNTB neurons). While several authors have postulated their presence, these collaterals have never been examined in detail. Here we test the hypothesis that collaterals of MNTB principal cells provide glycinergic inhibition to the MNTB. We injected dye into single principal neurons in the MNTB, traced their projections, and immunohistochemically identified their synapses. We found that collaterals terminate within the MNTB and provide an additional source of inhibition to other principal cells, creating an inhibitory microcircuit within the MNTB. Only about a quarter to a third of MNTB neurons receive such collateral inputs. This microcircuit could produce side band inhibition and enhance frequency tuning of MNTB neurons, consistent with physiological observations.

Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds

Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

Detecting coincident arrivals of synaptic inputs is a shared fundamental property of many sensory neurons. Such 'coincidence detection' usually refers to the detection of synchronized excitatory inputs only. Experimental evidence, however, indicated that some auditory neurons are also sensitive to the relative timing of excitatory and inhibitory synaptic inputs. This type of sensitivity is suggested to be important for coding temporal information of amplitude-modulated sounds, such as speech and other naturalistic sounds. In this study, we used a minimal model of coincidence detection to identify the key elements for temporal information processing. Our series of simulations demonstrated that (1) the threshold and time window for coincidence detection were the major factors for determining the response properties to excitatory inputs, and that (2) timed interactions between excitatory and inhibitory synaptic inputs are responsible for determining the temporal tuning properties of the neuron. These results suggest that coincidence detection is an essential function of neurons that detect the 'anti-coincidence' of excitatory and inhibitory inputs to encode temporal information of sounds.