Cooperative population coding facilitates efficient sound-source separability by adaptation to input statistics

Review of Binaural Processing With Asymmetrical Hearing Outcomes in Patients With Bilateral Cochlear Implants

Bilateral cochlear implants (BiCIs) result in several benefits, including improvements in speech understanding in noise and sound source localization. However, the benefit bilateral implants provide among recipients varies considerably across individuals. Here we consider one of the reasons for this variability: difference in hearing function between the two ears, that is, interaural asymmetry. Thus far, investigations of interaural asymmetry have been highly specialized within various research areas. The goal of this review is to integrate these studies in one place, motivating future research in the area of interaural asymmetry. We first consider bottom-up processing, where binaural cues are represented using excitation-inhibition of signals from the left ear and right ear, varying with the location of the sound in space, and represented by the lateral superior olive in the auditory brainstem. We then consider top-down processing via predictive coding, which assumes that perception stems from expectations based on context and prior sensory experience, represented by cascading series of cortical circuits. An internal, perceptual model is maintained and updated in light of incoming sensory input. Together, we hope that this amalgamation of physiological, behavioral, and modeling studies will help bridge gaps in the field of binaural hearing and promote a clearer understanding of the implications of interaural asymmetry for future research on optimal patient interventions.

Adaptation in auditory processing

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

Contextual Lateralization Based on Interaural Level Differences Is Preshaped by the Auditory Periphery and Predominantly Immune Against Sequential Segregation

The perceived azimuth of a target sound is determined by the interaural time difference and the interaural level difference (ILD) and is subject to contextual effects from precursor sounds. This study characterized ILD-based precursor effects (PEs) for high-frequency stimuli in a total of seven normal-hearing listeners. In Experiment 1, precursor and target were band-pass-filtered noises approximately centered at 4 kHz (1.2- and 1-octave bandwidth, respectively) separated by a 10-ms gap. The effects of precursor location (ipsilateral, contralateral, and central) on the perceived target azimuth were measured using a head-pointing task. Relative to control trials without a precursor, ipsilateral precursors biased the perceived target azimuth toward midline (medial bias) and contralateral precursors biased it contralaterally (lateral bias). Central precursors caused a symmetric lateral bias. An auditory periphery model that determines the "internal" ILD at the auditory nerve level, including either realistic efferent compression control or auditory nerve adaptation, explained about 50% of the variance in the PEs. These within-trial PEs were accompanied by an across-trial PE, inducing medial bias. Experiment 2 studied the role of sequential segregation in the within-trial PE by introducing a pitch difference between precursor and target. Segregation conditions caused increased PE for ipsilateral, no effect for contralateral, and either no effect or reduced PE for central precursors. Overall, the ILD-based within-trial PE appears to be preshaped already in the auditory periphery and the mechanism underlying at least the ipsilateral PE appears to be immune against sequential segregation.

Robustness of neuronal tuning to binaural sound localization cues against age-related loss of inhibitory synaptic inputs

Sound localization relies on minute differences in the timing and intensity of sound arriving at both ears. Neurons of the lateral superior olive (LSO) in the brainstem process these interaural disparities by precisely detecting excitatory and inhibitory synaptic inputs. Aging generally induces selective loss of inhibitory synaptic transmission along the entire auditory pathways, including the reduction of inhibitory afferents to LSO. Electrophysiological recordings in animals, however, reported only minor functional changes in aged LSO. The perplexing discrepancy between anatomical and physiological observations suggests a role for activity-dependent plasticity that would help neurons retain their binaural tuning function despite loss of inhibitory inputs. To explore this hypothesis, we use a computational model of LSO to investigate mechanisms underlying the observed functional robustness against age-related loss of inhibitory inputs. The LSO model is an integrate-and-fire type enhanced with a small amount of low-voltage activated potassium conductance and driven with (in)homogeneous Poissonian inputs. Without synaptic input loss, model spike rates varied smoothly with interaural time and level differences, replicating empirical tuning properties of LSO. By reducing the number of inhibitory afferents to mimic age-related loss of inhibition, overall spike rates increased, which negatively impacted binaural tuning performance, measured as modulation depth and neuronal discriminability. To simulate a recovery process compensating for the loss of inhibitory fibers, the strength of remaining inhibitory inputs was increased. By this modification, effects of inhibition loss on binaural tuning were considerably weakened, leading to an improvement of functional performance. These neuron-level observations were further confirmed by population modeling, in which binaural tuning properties of multiple LSO neurons were varied according to empirical measurements. These results demonstrate the plausibility that homeostatic plasticity could effectively counteract known age-dependent loss of inhibitory fibers in LSO and suggest that behavioral degradation of sound localization might originate from changes occurring more centrally.

Ambient noise exposure induces long-term adaptations in adult brainstem neurons

To counterbalance long-term environmental changes, neuronal circuits adapt the processing of sensory information. In the auditory system, ongoing background noise drives long-lasting adaptive mechanism in binaural coincidence detector neurons in the superior olive. However, the compensatory cellular mechanisms of the binaural neurons in the medial superior olive (MSO) to long-term background changes are unexplored. Here we investigated the cellular properties of MSO neurons during long-lasting adaptations induced by moderate omnidirectional noise exposure. After noise exposure, the input resistance of MSO neurons of mature Mongolian gerbils was reduced, likely due to an upregulation of hyperpolarisation-activated cation and low voltage-activated potassium currents. Functionally, the long-lasting adaptations increased the action potential current threshold and facilitated high frequency output generation. Noise exposure accelerated the occurrence of spontaneous postsynaptic currents. Together, our data suggest that cellular adaptations in coincidence detector neurons of the MSO to continuous noise exposure likely increase the sensitivity to differences in sound pressure levels.

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.

Listening in complex acoustic scenes

Being able to pick out particular sounds, such as speech, against a background of other sounds represents one of the key tasks performed by the auditory system. Understanding how this happens is important because speech recognition in noise is particularly challenging for older listeners and for people with hearing impairments. Central to this ability is the capacity of neurons to adapt to the statistics of sounds reaching the ears, which helps to generate noise-tolerant representations of sounds in the brain. In more complex auditory scenes, such as a cocktail party — where the background noise comprises other voices, sound features associated with each source have to be grouped together and segregated from those belonging to other sources. This depends on precise temporal coding and modulation of cortical response properties when attending to a particular speaker in a multi-talker environment. Furthermore, the neural processing underlying auditory scene analysis is shaped by experience over multiple timescales.

Binaural spatial adaptation as a mechanism for asymmetric trading of interaural time and level differences

A classic paradigm used to quantify the perceptual weighting of binaural spatial cues requires a listener to adjust the value of one cue, while the complementary cue is held constant. Adjustments are made until the auditory percept appears centered in the head, and the values of both cues are recorded as a trading relation (TR), most commonly in μs interaural time difference per dB interaural level difference. Interestingly, existing literature has shown that TRs differ according to the cue being adjusted. The current study investigated whether cue-specific adaptation, which might arise due to the continuous, alternating presentation of signals during adjustment tasks, could account for this poorly understood phenomenon. Three experiments measured TRs via adjustment and via lateralization of single targets in virtual reality (VR). Targets were 500 Hz pure tones preceded by silence or by adapting trains that held one of the cues constant. VR removed visual anchors and provided an intuitive response technique during lateralization. The pattern of results suggests that adaptation can account for cue-dependent TRs. In addition, VR seems to be a viable tool for psychophysical tasks.

Computational principles of neural adaptation for binaural signal integration

Adaptation to statistics of sensory inputs is an essential ability of neural systems and extends their effective operational range. Having a broad operational range facilitates to react to sensory inputs of different granularities, thus is a crucial factor for survival. The computation of auditory cues for spatial localization of sound sources, particularly the interaural level difference (ILD), has long been considered as a static process. Novel findings suggest that this process of ipsi- and contra-lateral signal integration is highly adaptive and depends strongly on recent stimulus statistics. Here, adaptation aids the encoding of auditory perceptual space of various granularities. To investigate the mechanism of auditory adaptation in binaural signal integration in detail, we developed a neural model architecture for simulating functions of lateral superior olive (LSO) and medial nucleus of the trapezoid body (MNTB) composed of single compartment conductance-based neurons. Neurons in the MNTB serve as an intermediate relay population. Their signal is integrated by the LSO population on a circuit level to represent excitatory and inhibitory interactions of input signals. The circuit incorporates an adaptation mechanism operating at the synaptic level based on local inhibitory feedback signals. The model’s predictive power is demonstrated in various simulations replicating physiological data. Incorporating the innovative adaptation mechanism facilitates a shift in neural responses towards the most effective stimulus range based on recent stimulus history. The model demonstrates that a single LSO neuron quickly adapts to these stimulus statistics and, thus, can encode an extended range of ILDs in the ipsilateral hemisphere. Most significantly, we provide a unique measurement of the adaptation efficacy of LSO neurons. Prerequisite of normal function is an accurate interaction of inhibitory and excitatory signals, a precise encoding of time and a well-tuned local feedback circuit. We suggest that the mechanisms of temporal competitive-cooperative interaction and the local feedback mechanism jointly sensitize the circuit to enable a response shift towards contra-lateral and ipsi-lateral stimuli, respectively.

Why are we more precise in localizing a sound after hearing it several times? Adaptation to the statistics of a stimulus plays a crucial role in this. The present article investigates the abilities of a neural adaptation mechanism for improved localization skills based on a neural network model. Adaptation to stimulus statistics is very prominent in sensory systems of animals and allows them to respond to a wide range of stimuli, thus is a crucial factor for survival. For example, humans are able to navigate under suddenly changing illumination conditions (driving a car into and out of a tunnel). This is possible by courtesy of adaptation abilities of our sensory organs and pathways. Certainly, adaptation is not confined to a single sense like vision but also affects other senses like audition. Especially the perception of sound source location. Compared to vision, the localization of a sound source in the horizontal plane is a rather complicated task since the location cannot be read out from the receptor surface but needs to be computed. This requires the underlying neural system to calculate differences of the intensity between the two ears which provide a distinct cue for the location of a sound source. Here, adaptation to this cue allows to focus on a specific part of auditory space and thereby facilitates improved localisation abilities. Based on recent findings that suggest that the intensity difference computation is a flexible process with distinct adaptation mechanisms, we developed a neural model that computes the intensity difference to two incoming sound signals. The model comprises a novel mechanism for adaptation to sound source locations and provides a means to investigate underlying neural principles of adaptation and compare their effectivenesses. We demonstrate that due this mechanism the perceptual range is extended and a finer resolution of auditory space is obtained. Results explain the neural basis for adaptation and indicate that the interplay between different adaptation mechanisms facilitate highly precise sound source localization in a wide range of locations.