Neural Rate and Timing Cues for Detection and Discrimination of Amplitude-Modulated Tones in the Awake Rabbit Inferior Colliculus

Midbrain sensitivity to auditory motion studied with dichotic sweeps of broadband noise

Many neurons in the central nucleus of the inferior colliculus (IC) show sensitivity to interaural time differences (ITDs), which is thought to be relayed from the brainstem. However, studies with interaural phase modulation of pure tones showed that IC neurons have a sensitivity to changes in ITD that is not present at the level of the brainstem. This sensitivity has been interpreted as a form of sensitivity to motion. A new type of stimulus is used here to study the sensitivity of IC neurons to dynamic changes in ITD, in which broad- or narrowband stimuli are swept through a range of ITDs with arbitrary start-ITD, end-ITD, speed, and direction. Extracellular recordings were obtained under barbiturate anesthesia in the cat. We applied the same analyses as previously introduced for the study of responses to tones. We find effects of motion which are similar to those described in response to interaural phase modulation of tones. The size of the effects strongly depended on the motion parameters but was overall smaller than reported for tones. We found that the effects of motion could largely be explained by the temporal response pattern of the neuron such as adaptation and build-up. Our data add to previous evidence questioning true coding of motion at the level of the IC.

Neurometric amplitude modulation detection in the inferior colliculus of Young and Aged rats

Amplitude modulation is an important acoustic cue for sound discrimination, and humans and animals are able to detect small modulation depths behaviorally. In the inferior colliculus (IC), both firing rate and phase-locking may be used to detect amplitude modulation. How neural representations that detect modulation change with age are poorly understood, including the extent to which age-related changes may be attributed to the inherited properties of ascending inputs to IC neurons. Here, simultaneous measures of local field potentials (LFPs) and single-unit responses were made from the inferior colliculus of Young and Aged rats using both noise and tone carriers in response to sinusoidally amplitude-modulated sounds of varying depths. We found that Young units had higher firing rates than Aged for noise carriers, whereas Aged units had higher phase-locking (vector strength), especially for tone carriers. Sustained LFPs were larger in Young animals for modulation frequencies 8-16 Hz and comparable at higher modulation frequencies. Onset LFP amplitudes were much larger in Young animals and were correlated with the evoked firing rates, while LFP onset latencies were shorter in Aged animals. Unit neurometric thresholds by synchrony or firing rate measures did not differ significantly across age and were comparable to behavioral thresholds in previous studies whereas LFP thresholds were lower than behavior.

Neural decoding of inferior colliculus multiunit activity for sound category identification with temporal correlation and transfer learning

Natural sounds are easily perceived and identified by humans and animals. Despite this, the neural transformations that enable sound perception remain largely unknown. It is thought that the temporal characteristics of sounds may be reflected in auditory assembly responses at the inferior colliculus (IC) and which may play an important role in identification of natural sounds. In our study, natural sounds will be predicted from multi-unit activity (MUA) signals collected in the IC. Data is obtained from an international platform publicly accessible. The temporal correlation values of the MUA signals are converted into images. We used two different segment sizes and with a denoising method, we generated four subsets for the classification. Using pre-trained convolutional neural networks (CNNs), features of the images were extracted and the type of heard sound was classified. For this, we applied transfer learning from Alexnet, Googlenet and Squeezenet CNNs. The classifiers support vector machines (SVM), k-nearest neighbour (KNN), Naive Bayes and Ensemble were used. The accuracy, sensitivity, specificity, precision and F1 score were measured as evaluation parameters. By using all the tests and removing the noise, the accuracy improved significantly. These results will allow neuroscientists to make interesting conclusions.

Population coding of time-varying sounds in the nonlemniscal inferior colliculus

The inferior colliculus (IC) of the midbrain is important for complex sound processing, such as discriminating conspecific vocalizations and human speech. The IC's nonlemniscal, dorsal "shell" region is likely important for this process, as neurons in these layers project to higher-order thalamic nuclei that subsequently funnel acoustic signals to the amygdala and nonprimary auditory cortices, forebrain circuits important for vocalization coding in a variety of mammals, including humans. However, the extent to which shell IC neurons transmit acoustic features necessary to discern vocalizations is less clear, owing to the technical difficulty of recording from neurons in the IC's superficial layers via traditional approaches. Here, we use two-photon Ca2+ imaging in mice of either sex to test how shell IC neuron populations encode the rate and depth of amplitude modulation, important sound cues for speech perception. Most shell IC neurons were broadly tuned, with a low neurometric discrimination of amplitude modulation rate; only a subset was highly selective to specific modulation rates. Nevertheless, neural network classifier trained on fluorescence data from shell IC neuron populations accurately classified amplitude modulation rate, and decoding accuracy was only marginally reduced when highly tuned neurons were omitted from training data. Rather, classifier accuracy increased monotonically with the modulation depth of the training data, such that classifiers trained on full-depth modulated sounds had median decoding errors of ∼0.2 octaves. Thus, shell IC neurons may transmit time-varying signals via a population code, with perhaps limited reliance on the discriminative capacity of any individual neuron.NEW & NOTEWORTHY The IC's shell layers originate a "nonlemniscal" pathway important for perceiving vocalization sounds. However, prior studies suggest that individual shell IC neurons are broadly tuned and have high response thresholds, implying a limited reliability of efferent signals. Using Ca2+ imaging, we show that amplitude modulation is accurately represented in the population activity of shell IC neurons. Thus, downstream targets can read out sounds' temporal envelopes from distributed rate codes transmitted by populations of broadly tuned neurons.

GluN2C/D-containing NMDA receptors enhance temporal summation and increase sound-evoked and spontaneous firing in the inferior colliculus

Along the ascending auditory pathway, there is a broad shift from temporal coding, which is common in the lower auditory brainstem, to rate coding, which predominates in auditory cortex. This temporal-to-rate transition is particularly prominent in the inferior colliculus (IC), the midbrain hub of the auditory system, but the mechanisms that govern how individual IC neurons integrate information across time remain largely unknown. Here, we report the widespread expression of Glun2c and Glun2d mRNA in IC neurons. GluN2C/D-containing NMDA receptors are relatively insensitive to voltage-dependent Mg2+ block, and thus can conduct current at resting membrane potential. Using in situ hybridization and pharmacology, we show that VIP neurons in the IC express GluN2D-containing NMDA receptors that are activatable by commissural inputs from the contralateral IC. In addition, GluN2C/D-containing receptors have much slower kinetics than other NMDA receptors, and we found that GluN2D-containing receptors facilitate temporal summation of synaptic inputs in VIP neurons. In a model neuron, we show that a GluN2C/D-like conductance interacts with the passive membrane properties of the neuron to alter temporal and rate coding of stimulus trains. Consistent with this, we show in vivo that blocking GluN2C/D-containing receptors decreases both the spontaneous firing rate and the overall firing rate elicited by amplitude-modulated (AM) sounds in many IC neurons. These results suggest that GluN2C/D-containing NMDA receptors influence rate coding for auditory stimuli in the IC by facilitating the temporal integration of synaptic inputs.

Neural Fluctuation Contrast as a Code for Complex Sounds: The Role and Control of Peripheral Nonlinearities

The nonlinearities of the inner ear are often considered to be obstacles that the central nervous system has to overcome to decode neural responses to sounds. This review describes how peripheral nonlinearities, such as saturation of the inner-hair-cell response and of the IHC-auditory-nerve synapse, are instead beneficial to the neural encoding of complex sounds such as speech. These nonlinearities set up contrast in the depth of neural-fluctuations in auditory-nerve responses along the tonotopic axis, referred to here as neural fluctuation contrast (NFC). Physiological support for the NFC coding hypothesis is reviewed, and predictions of several psychophysical phenomena, including masked detection and speech intelligibility, are presented. Lastly, a framework based on the NFC code for understanding how the medial olivocochlear (MOC) efferent system contributes to the coding of complex sounds is presented. By modulating cochlear gain control in response to both sound energy and fluctuations in neural responses, the MOC system is hypothesized to function not as a simple feedback gain-control device, but rather as a mechanism for enhancing NFC along the tonotopic axis, enabling robust encoding of complex sounds across a wide range of sound levels and in the presence of background noise. Effects of sensorineural hearing loss on the NFC code and on the MOC feedback system are presented and discussed.

Identifying neuron types and circuit mechanisms in the auditory midbrain

The inferior colliculus (IC) is a critical computational hub in the central auditory pathway. From its position in the midbrain, the IC receives nearly all the ascending output from the lower auditory brainstem and provides the main source of auditory information to the thalamocortical system. In addition to being a crossroads for auditory circuits, the IC is rich with local circuits and contains more than five times as many neurons as the nuclei of the lower auditory brainstem combined. These results hint at the enormous computational power of the IC, and indeed, systems-level studies have identified numerous important transformations in sound coding that occur in the IC. However, despite decades of effort, the cellular mechanisms underlying IC computations and how these computations change following hearing loss have remained largely impenetrable. In this review, we argue that this challenge persists due to the surprisingly difficult problem of identifying the neuron types and circuit motifs that comprise the IC. After summarizing the extensive evidence pointing to a diversity of neuron types in the IC, we highlight the successes of recent efforts to parse this complexity using molecular markers to define neuron types. We conclude by arguing that the discovery of molecularly identifiable neuron types ushers in a new era for IC research marked by molecularly targeted recordings and manipulations. We propose that the ability to reproducibly investigate IC circuits at the neuronal level will lead to rapid advances in understanding the fundamental mechanisms driving IC computations and how these mechanisms shift following hearing loss.

Normal behavioral discrimination of envelope statistics in budgerigars with kainate-induced cochlear synaptopathy

Cochlear synaptopathy is a common pathology in humans associated with aging and potentially sound overexposure. Synaptopathy is widely expected to cause "hidden hearing loss," including difficulty perceiving speech in noise, but support for this hypothesis is controversial. Here in budgerigars (Melopsittacus undulatus), we evaluated the impact of long-term cochlear synaptopathy on behavioral discrimination of Gaussian noise (GN) and low-noise noise (LNN) signals processed to have a flatter envelope. Stimuli had center frequencies of 1-3kHz, 100-Hz bandwidth, and were presented at sensation levels (SLs) from 10 to 30dB. We reasoned that narrowband, low-SL stimuli of this type should minimize spread of excitation across auditory-nerve fibers, and hence might reveal synaptopathy-related defects if they exist. Cochlear synaptopathy was induced without hair-cell injury using kainic acid (KA). Behavioral threshold tracking experiments characterized the minimum stimulus duration above which animals could reliably discriminate between LNN and GN. Budgerigar thresholds for LNN-GN discrimination ranged from 40 to 60ms at 30dB SL, were similar across frequencies, and increased for lower SLs. Notably, animals with long-term 39-77% estimated synaptopathy performed similarly to controls, requiring on average a ∼7.5% shorter stimulus duration (-0.7±1.0dB; mean difference ±SE) for LNN-GN discrimination. Decision-variable correlation analyses of detailed behavioral response patterns showed that individual animals relied on envelope cues to discriminate LNN and GN, with lesser roles of FM and energy cues; no difference was found between KA-exposed and control groups. These results suggest that long-term cochlear synaptopathy does not impair discrimination of low-level signals with different envelope statistics.

Neuronal responses in mouse inferior colliculus correlate with behavioral detection of amplitude-modulated sound

Amplitude modulation (AM) is a common feature of natural sounds, including speech and animal vocalizations. Here, we used operant conditioning and in vivo electrophysiology to determine the AM detection threshold of mice as well as its underlying neuronal encoding. Mice were trained in a Go-NoGo task to detect the transition to AM within a noise stimulus designed to prevent the use of spectral side-bands or a change in intensity as alternative cues. Our results indicate that mice, compared with other species, detect high modulation frequencies up to 512 Hz well, but show much poorer performance at low frequencies. Our in vivo multielectrode recordings in the inferior colliculus (IC) of both anesthetized and awake mice revealed a few single units with remarkable phase-locking ability to 512 Hz modulation, but not sufficient to explain the good behavioral detection at that frequency. Using a model of the population response that combined dimensionality reduction with threshold detection, we reproduced the general band-pass characteristics of behavioral detection based on a subset of neurons showing the largest firing rate change (both increase and decrease) in response to AM, suggesting that these neurons are instrumental in the behavioral detection of AM stimuli by the mice.NEW & NOTEWORTHY The amplitude of natural sounds, including speech and animal vocalizations, often shows characteristic modulations. We examined the relationship between neuronal responses in the mouse inferior colliculus and the behavioral detection of amplitude modulation (AM) in sound and modeled how the former can give rise to the latter. Our model suggests that behavioral detection can be well explained by the activity of a subset of neurons showing the largest firing rate changes in response to AM.

Population coding of time-varying sounds in the non-lemniscal Inferior Colliculus

The inferior colliculus (IC) of the midbrain is important for complex sound processing, such as discriminating conspecific vocalizations and human speech. The IC's non-lemniscal, dorsal "shell" region is likely important for this process, as neurons in these layers project to higher-order thalamic nuclei that subsequently funnel acoustic signals to the amygdala and non-primary auditory cortices; forebrain circuits important for vocalization coding in a variety of mammals, including humans. However, the extent to which shell IC neurons transmit acoustic features necessary to discern vocalizations is less clear, owing to the technical difficulty of recording from neurons in the IC's superficial layers via traditional approaches. Here we use 2-photon Ca2+ imaging in mice of either sex to test how shell IC neuron populations encode the rate and depth of amplitude modulation, important sound cues for speech perception. Most shell IC neurons were broadly tuned, with a low neurometric discrimination of amplitude modulation rate; only a subset were highly selective to specific modulation rates. Nevertheless, neural network classifier trained on fluorescence data from shell IC neuron populations accurately classified amplitude modulation rate, and decoding accuracy was only marginally reduced when highly tuned neurons were omitted from training data. Rather, classifier accuracy increased monotonically with the modulation depth of the training data, such that classifiers trained on full-depth modulated sounds had median decoding errors of ~0.2 octaves. Thus, shell IC neurons may transmit time-varying signals via a population code, with perhaps limited reliance on the discriminative capacity of any individual neuron.

Effects of sensorineural hearing loss on formant-frequency discrimination: Measurements and models

This study concerns the effect of hearing loss on discrimination of formant frequencies in vowels. In the response of the healthy ear to a harmonic sound, auditory-nerve (AN) rate functions fluctuate at the fundamental frequency, F0. Responses of inner-hair-cells (IHCs) tuned near spectral peaks are captured (or dominated) by a single harmonic, resulting in lower fluctuation depths than responses of IHCs tuned between spectral peaks. Therefore, the depth of neural fluctuations (NFs) varies along the tonotopic axis and encodes spectral peaks, including formant frequencies of vowels. This NF code is robust across a wide range of sound levels and in background noise. The NF profile is converted into a rate-place representation in the auditory midbrain, wherein neurons are sensitive to low-frequency fluctuations. The NF code is vulnerable to sensorineural hearing loss (SNHL) because capture depends upon saturation of IHCs, and thus the interaction of cochlear gain with IHC transduction. In this study, formant-frequency discrimination limens (DLFFs) were estimated for listeners with normal hearing or mild to moderate SNHL. The F0 was fixed at 100 Hz, and formant peaks were either aligned with harmonic frequencies or placed between harmonics. Formant peak frequencies were 600 and 2000 Hz, in the range of first and second formants of several vowels. The difficulty of the task was varied by changing formant bandwidth to modulate the contrast in the NF profile. Results were compared to predictions from model auditory-nerve and inferior colliculus (IC) neurons, with listeners' audiograms used to individualize the AN model. Correlations between DLFFs, audiometric thresholds near the formant frequencies, age, and scores on the Quick speech-in-noise test are reported. SNHL had a strong effect on DLFF for the second formant frequency (F2), but relatively small effect on DLFF for the first formant (F1). The IC model appropriately predicted substantial threshold elevations for changes in F2 as a function of SNHL and little effect of SNHL on thresholds for changes in F1.

Representations of fricatives in subcortical model responses: Comparisons with human consonant perception

Fricatives are obstruent sound contrasts made by airflow constrictions in the vocal tract that produce turbulence across the constriction or at a site downstream from the constriction. Fricatives exhibit significant intra/intersubject and contextual variability. Yet, fricatives are perceived with high accuracy. The current study investigated modeled neural responses to fricatives in the auditory nerve (AN) and inferior colliculus (IC) with the hypothesis that response profiles across populations of neurons provide robust correlates to consonant perception. Stimuli were 270 intervocalic fricatives (10 speakers × 9 fricatives × 3 utterances). Computational model response profiles had characteristic frequencies that were log-spaced from 125 Hz to 8 or 20 kHz to explore the impact of high-frequency responses. Confusion matrices generated by k-nearest-neighbor subspace classifiers were based on the profiles of average rates across characteristic frequencies as feature vectors. Model confusion matrices were compared with published behavioral data. The modeled AN and IC neural responses provided better predictions of behavioral accuracy than the stimulus spectra, and IC showed better accuracy than AN. Behavioral fricative accuracy was explained by modeled neural response profiles, whereas confusions were only partially explained. Extended frequencies improved accuracy based on the model IC, corroborating the importance of extended high frequencies in speech perception.

Incorporating models of subcortical processing improves the ability to predict EEG responses to natural speech

The goal of describing how the human brain responds to complex acoustic stimuli has driven auditory neuroscience research for decades. Often, a systems-based approach has been taken, in which neurophysiological responses are modeled based on features of the presented stimulus. This includes a wealth of work modeling electroencephalogram (EEG) responses to complex acoustic stimuli such as speech. Examples of the acoustic features used in such modeling include the amplitude envelope and spectrogram of speech. These models implicitly assume a direct mapping from stimulus representation to cortical activity. However, in reality, the representation of sound is transformed as it passes through early stages of the auditory pathway, such that inputs to the cortex are fundamentally different from the raw audio signal that was presented. Thus, it could be valuable to account for the transformations taking place in lower-order auditory areas, such as the auditory nerve, cochlear nucleus, and inferior colliculus (IC) when predicting cortical responses to complex sounds. Specifically, because IC responses are more similar to cortical inputs than acoustic features derived directly from the audio signal, we hypothesized that linear mappings (temporal response functions; TRFs) fit to the outputs of an IC model would better predict EEG responses to speech stimuli. To this end, we modeled responses to the acoustic stimuli as they passed through the auditory nerve, cochlear nucleus, and inferior colliculus before fitting a TRF to the output of the modeled IC responses. Results showed that using model-IC responses in traditional systems analyzes resulted in better predictions of EEG activity than using the envelope or spectrogram of a speech stimulus. Further, it was revealed that model-IC derived TRFs predict different aspects of the EEG than acoustic-feature TRFs, and combining both types of TRF models provides a more accurate prediction of the EEG response.

Mechanisms of masking by Schroeder-phase harmonic tone complexes in the budgerigar (Melopsittacus undulatus)

Schroeder-phase harmonic tone complexes can have a flat temporal envelope and rising or falling instantaneous-frequency sweeps within F0 periods, depending on the phase-scaling parameter C. Human tone-detection thresholds in a concurrent Schroeder masker are 10-15 dB lower for positive C values (rising frequency sweeps) compared to negative (falling sweeps), potentially due to cochlear mechanics, though this hypothesis remains controversial. Birds provide an interesting model for studies of Schroeder masking because many species produce vocalizations containing frequency sweeps. Prior behavioral studies in birds suggest less behavioral threshold difference between maskers with opposite C values than in humans, but focused on low masker F0s and did not explore neural mechanisms. We performed behavioral Schroeder-masking experiments in budgerigars (Melopsittacus undulatus) using a wide range of masker F0 and C values. Signal frequency was 2800 Hz. Neural recordings from the midbrain characterized encoding of behavioral stimuli in awake animals. Behavioral thresholds increased with increasing masker F0 and showed minimal difference between opposite C values, consistent with prior budgerigar studies. Midbrain recordings showed prominent temporal and rate-based encoding of Schroeder F0, and in many cases, marked asymmetry in Schroeder responses between C polarities. Neural thresholds for Schroeder-masked tone detection were often based on a response decrement compared to the masker alone, consistent with prominent modulation tuning in midbrain neurons, and were generally similar between opposite C values. The results highlight the likely importance of envelope cues in Schroeder masking and show that differences in supra-threshold Schroeder responses do not necessarily result in neural threshold differences.

Adaptive mechanisms facilitate robust performance in noise and in reverberation in an auditory categorization model

For robust vocalization perception, the auditory system must generalize over variability in vocalization production as well as variability arising from the listening environment (e.g., noise and reverberation). We previously demonstrated using guinea pig and marmoset vocalizations that a hierarchical model generalized over production variability by detecting sparse intermediate-complexity features that are maximally informative about vocalization category from a dense spectrotemporal input representation. Here, we explore three biologically feasible model extensions to generalize over environmental variability: (1) training in degraded conditions, (2) adaptation to sound statistics in the spectrotemporal stage and (3) sensitivity adjustment at the feature detection stage. All mechanisms improved vocalization categorization performance, but improvement trends varied across degradation type and vocalization type. One or more adaptive mechanisms were required for model performance to approach the behavioral performance of guinea pigs on a vocalization categorization task. These results highlight the contributions of adaptive mechanisms at multiple auditory processing stages to achieve robust auditory categorization.

Incorporating models of subcortical processing improves the ability to predict EEG responses to natural speech

The goal of describing how the human brain responds to complex acoustic stimuli has driven auditory neuroscience research for decades. Often, a systems-based approach has been taken, in which neurophysiological responses are modeled based on features of the presented stimulus. This includes a wealth of work modeling electroencephalogram (EEG) responses to complex acoustic stimuli such as speech. Examples of the acoustic features used in such modeling include the amplitude envelope and spectrogram of speech. These models implicitly assume a direct mapping from stimulus representation to cortical activity. However, in reality, the representation of sound is transformed as it passes through early stages of the auditory pathway, such that inputs to the cortex are fundamentally different from the raw audio signal that was presented. Thus, it could be valuable to account for the transformations taking place in lower-order auditory areas, such as the auditory nerve, cochlear nucleus, and inferior colliculus (IC) when predicting cortical responses to complex sounds. Specifically, because IC responses are more similar to cortical inputs than acoustic features derived directly from the audio signal, we hypothesized that linear mappings (temporal response functions; TRFs) fit to the outputs of an IC model would better predict EEG responses to speech stimuli. To this end, we modeled responses to the acoustic stimuli as they passed through the auditory nerve, cochlear nucleus, and inferior colliculus before fitting a TRF to the output of the modeled IC responses. Results showed that using model-IC responses in traditional systems analyses resulted in better predictions of EEG activity than using the envelope or spectrogram of a speech stimulus. Further, it was revealed that model-IC derived TRFs predict different aspects of the EEG than acoustic-feature TRFs, and combining both types of TRF models provides a more accurate prediction of the EEG response.x.

Temporal Envelope Coding of the Human Auditory Nerve Inferred from Electrocochleography: Comparison with Envelope Following Responses

Neural coding of the slow amplitude fluctuations of sound (i.e., temporal envelope) is thought to be essential for speech understanding; however, such coding by the human auditory nerve is poorly understood. Here, neural coding of the temporal envelope by the human auditory nerve is inferred from measurements of the compound action potential in response to an amplitude modulated carrier (CAPENV) for modulation frequencies ranging from 20 to 1000 Hz. The envelope following response (EFR) was measured simultaneously with CAPENV from active electrodes placed on the high forehead and tympanic membrane, respectively. Results support the hypothesis that phase locking to higher modulation frequencies (> 80 Hz) will be stronger for CAPENV, compared to EFR, consistent with the upper-frequency limits of phase locking for auditory nerve fibers compared to auditory brainstem/cortex neurons. Future work is needed to determine the extent to which (1) CAPENV is a useful tool for studying how temporal processing of the auditory nerve is affected by aging, hearing loss, and noise-induced cochlear synaptopathy and (2) CAPENV reveals the relationship between auditory nerve temporal processing and perception of the temporal envelope.

Responses to dichotic tone-in-noise stimuli in the inferior colliculus

Human listeners are more sensitive to tones embedded in diotic noise when the tones are out-of-phase at the two ears (N0Sπ) than when they are in-phase (N0S0). The difference between the tone-detection thresholds for these two conditions is referred to as the binaural masking level difference (BMLD) and reflects a benefit of binaural processing. Detection in the N0Sπ condition has been explained in modeling studies by changes in interaural correlation (IAC), but this model has only been directly tested physiologically for low frequencies. Here, the IAC-based hypothesis for binaural detection was examined across a wide range of frequencies and masker levels using recordings in the awake rabbit inferior colliculus (IC). IAC-based cues were strongly correlated with neural responses to N0Sπ stimuli. Additionally, average rate-based thresholds were calculated for both N0S0 and N0Sπ conditions. The rate-based neural BMLD at 500 Hz matched rabbit behavioral data, but the trend of neural BMLDs across frequency differed from that of humans.

Neural processing and perception of Schroeder-phase harmonic tone complexes in the gerbil: Relating single-unit neurophysiology to behavior

Schroeder-phase harmonic tone complexes have been used in physiological and psychophysical studies in several species to gain insight into cochlear function. Each pitch period of the Schroeder stimulus contains a linear frequency sweep; the duty cycle, sweep velocity, and direction are controlled by parameters of the phase spectrum. Here, responses to a range of Schroeder-phase harmonic tone complexes were studied both behaviorally and in neural recordings from the auditory nerve and inferior colliculus of Mongolian gerbils. Gerbils were able to discriminate Schroeder-phase harmonic tone complexes based on sweep direction, duty cycle, and/or velocity for fundamental frequencies up to 200 Hz. Temporal representation in neural responses based on the van Rossum spike-distance metric, with time constants of either 1 ms or related to the stimulus' period, was compared to average discharge rates. Neural responses and behavioral performance were both expressed in terms of sensitivity, d', to allow direct comparisons. Our results suggest that in the auditory nerve, stimulus fine structure is represented by spike timing while envelope is represented by rate. In the inferior colliculus, both temporal fine structure and envelope appear to be represented best by rate. However, correlations between neural d' values and behavioral sensitivity for sweep direction were strongest for both temporal metrics, for both auditory nerve and inferior colliculus. Furthermore, the high sensitivity observed in the inferior colliculus neural rate-based discrimination suggests that these neurons integrate across multiple inputs arising from the auditory periphery.

Rabbits use both spectral and temporal cues to discriminate the fundamental frequency of harmonic complexes with missing fundamentals

The pitch of harmonic complex tones (HCTs) common in speech, music, and animal vocalizations plays a key role in the perceptual organization of sound. Unraveling the neural mechanisms of pitch perception requires animal models, but little is known about complex pitch perception by animals, and some species appear to use different pitch mechanisms than humans. Here, we tested rabbits' ability to discriminate the fundamental frequency (F0) of HCTs with missing fundamentals, using a behavioral paradigm inspired by foraging behavior in which rabbits learned to harness a spatial gradient in F0 to find the location of a virtual target within a room for a food reward. Rabbits were initially trained to discriminate HCTs with F0s in the range 400-800 Hz and with harmonics covering a wide frequency range (800-16,000 Hz) and then tested with stimuli differing in spectral composition to test the role of harmonic resolvability (experiment 1) or in F0 range (experiment 2) or in both F0 and spectral content (experiment 3). Together, these experiments show that rabbits can discriminate HCTs over a wide F0 range (200-1,600 Hz) encompassing the range of conspecific vocalizations and can use either the spectral pattern of harmonics resolved by the cochlea for higher F0s or temporal envelope cues resulting from interaction between unresolved harmonics for lower F0s. The qualitative similarity of these results to human performance supports the use of rabbits as an animal model for studies of pitch mechanisms, providing species differences in cochlear frequency selectivity and F0 range of vocalizations are taken into account.NEW & NOTEWORTHY Understanding the neural mechanisms of pitch perception requires experiments in animal models, but little is known about pitch perception by animals. Here we show that rabbits, a popular animal in auditory neuroscience, can discriminate complex sounds differing in pitch using either spectral cues or temporal cues. The results suggest that the role of spectral cues in pitch perception by animals may have been underestimated by predominantly testing low frequencies in the range of human voice.

Corticothalamic projections deliver enhanced responses to medial geniculate body as a function of the temporal reliability of the stimulus

Ageing and challenging signal-in-noise conditions are known to engage the use of cortical resources to help maintain speech understanding. Extensive corticothalamic projections are thought to provide attentional, mnemonic and cognitive-related inputs in support of sensory inferior colliculus (IC) inputs to the medial geniculate body (MGB). Here we show that a decrease in modulation depth, a temporally less distinct periodic acoustic signal, leads to a jittered ascending temporal code, changing MGB unit responses from adapting responses to responses showing repetition enhancement, posited to aid identification of important communication and environmental sounds. Young-adult male Fischer Brown Norway rats, injected with the inhibitory opsin archaerhodopsin T (ArchT) into the primary auditory cortex (A1), were subsequently studied using optetrodes to record single-units in MGB. Decreasing the modulation depth of acoustic stimuli significantly increased repetition enhancement. Repetition enhancement was blocked by optical inactivation of corticothalamic terminals in MGB. These data support a role for corticothalamic projections in repetition enhancement, implying that predictive anticipation could be used to improve neural representation of weakly modulated sounds. KEY POINTS: In response to a less temporally distinct repeating sound with low modulation depth, medial geniculate body (MGB) single units show a switch from adaptation towards repetition enhancement. Repetition enhancement was reversed by blockade of MGB inputs from the auditory cortex. Collectively, these data argue that diminished acoustic temporal cues such as weak modulation engage cortical processes to enhance coding of those cues in auditory thalamus.

Mapping cortico-subcortical sensitivity to 4 Hz amplitude modulation depth in human auditory system with functional MRI

Temporal modulations in the envelope of acoustic waveforms at rates around 4 Hz constitute a strong acoustic cue in speech and other natural sounds. It is often assumed that the ascending auditory pathway is increasingly sensitive to slow amplitude modulation (AM), but sensitivity to AM is typically considered separately for individual stages of the auditory system. Here, we used blood oxygen level dependent (BOLD) fMRI in twenty human subjects (10 male) to measure sensitivity of regional neural activity in the auditory system to 4 Hz temporal modulations. Participants were exposed to AM noise stimuli varying parametrically in modulation depth to characterize modulation-depth effects on BOLD responses. A Bayesian hierarchical modeling approach was used to model potentially nonlinear relations between AM depth and group-level BOLD responses in auditory regions of interest (ROIs). Sound stimulation activated the auditory brainstem and cortex structures in single subjects. BOLD responses to noise exposure in core and belt auditory cortices scaled positively with modulation depth. This finding was corroborated by whole-brain cluster-level inference. Sensitivity to AM depth variations was particularly pronounced in the Heschl's gyrus but also found in higher-order auditory cortical regions. None of the sound-responsive subcortical auditory structures showed a BOLD response profile that reflected the parametric variation in AM depth. The results are compatible with the notion that early auditory cortical regions play a key role in processing low-rate modulation content of sounds in the human auditory system.

Responses to diotic tone-in-noise stimuli in the inferior colliculus: stimulus envelope and neural fluctuation cues

Human detection thresholds in tone-in-noise (TIN) paradigms cannot be explained by the prevalent power-spectrum model when stimulus energy is made less reliable, e.g., in roving-level or equal-energy paradigms. Envelope-related cues provide an alternative that is more robust across level. The TIN stimulus envelope is encoded by slow fluctuations in auditory-nerve (AN) responses - a temporal representation affected by inner-hair-cell (IHC) saturation and cochlear compression. Here, envelope-related fluctuations in AN responses were hypothesized to be reflected in responses of neurons in the inferior colliculus (IC), which have average discharge rates that are sensitive to amplitude-modulation (AM) depth and frequency. Responses to tones masked by narrowband gaussian noise (GN) and low-noise noise (LNN) were recorded in the IC of awake rabbits. Fluctuation amplitudes in the stimulus envelope and in model AN responses decrease for GN maskers and increase for LNN upon addition of tones near threshold. Response rates of IC neurons that are excited by AM were expected to be positively correlated with fluctuation amplitudes, whereas rates of neurons suppressed by AM were expected to be negatively correlated. Of neurons with measurable TIN-detection thresholds, most had the predicted changes in rate with increasing tone level for both GN and LNN maskers. Changes in rate with tone level were correlated with envelope sensitivity measured with two methods, including the maximum slopes of modulation transfer functions. IC rate-based thresholds were broadly consistent with published human and rabbit behavioral data. These results highlight the importance of midbrain sensitivity to envelope cues, as represented in peripheral neural fluctuations, for detection of signals in noise.

Midbrain-Level Neural Correlates of Behavioral Tone-in-Noise Detection: Dependence on Energy and Envelope Cues

Hearing in noise is a problem often assumed to depend on encoding of energy level by channels tuned to target frequencies, but few studies have tested this hypothesis. The present study examined neural correlates of behavioral tone-in-noise (TIN) detection in budgerigars (Melopsittacus undulatus, either sex), a parakeet species with human-like behavioral sensitivity to many simple and complex sounds. Behavioral sensitivity to tones in band-limited noise was assessed using operant-conditioning procedures. Neural recordings were made in awake animals from midbrain-level neurons in the inferior colliculus, the first processing stage of the ascending auditory pathway with pronounced rate-based encoding of stimulus amplitude modulation. Budgerigar TIN detection thresholds were similar to human thresholds across the full range of frequencies (0.5-4 kHz) and noise levels (45-85 dB SPL) tested. Also as in humans, thresholds were minimally affected by a challenging roving-level condition with random variation in background-noise level. Many midbrain neurons showed a decreasing response rate as TIN signal-to-noise ratio (SNR) was increased by elevating the tone level, a pattern attributable to amplitude-modulation tuning in these cells and the fact that higher SNR tone-plus-noise stimuli have flatter amplitude envelopes. TIN thresholds of individual neurons were as sensitive as behavioral thresholds under most conditions, perhaps surprisingly even when the unit's characteristic frequency was tuned an octave or more away from the test frequency. A model that combined responses of two cell types enhanced TIN sensitivity in the roving-level condition. These results highlight the importance of midbrain-level envelope encoding and off-frequency neural channels for hearing in noise.SIGNIFICANCE STATEMENT Detection of target sounds in noise is often assumed to depend on energy-level encoding by neural processing channels tuned to the target frequency. In contrast, we found that tone-in-noise sensitivity in budgerigars was often greatest in midbrain neurons not tuned to the test frequency, underscoring the potential importance of off-frequency channels for perception. Furthermore, the results highlight the importance of envelope processing for hearing in noise, especially under challenging conditions with random variation in background noise level over time.

Amplitude modulation encoding in the auditory cortex: comparisons between the primary and middle lateral belt regions

In macaques, the middle lateral auditory cortex (ML) is a belt region adjacent to the primary auditory cortex (A1) and believed to be at a hierarchically higher level. Although ML single-unit responses have been studied for several auditory stimuli, the ability of ML cells to encode amplitude modulation (AM)-an ability that has been widely studied in A1-has not yet been characterized. Here, we compared the responses of A1 and ML neurons to amplitude-modulated (AM) noise in awake macaques. Although several of the basic properties of A1 and ML responses to AM noise were similar, we found several key differences. ML neurons were less likely to phase lock, did not phase lock as strongly, and were more likely to respond in a nonsynchronized fashion than A1 cells, consistent with a temporal-to-rate transformation as information ascends the auditory hierarchy. ML neurons tended to have lower temporally (phase-locking) based best modulation frequencies than A1 neurons. Neurons that decreased their firing rate in response to AM noise relative to their firing rate in response to unmodulated noise became more common at the level of ML than they were in A1. In both A1 and ML, we found a prevalent class of neurons that usually have enhanced rate responses relative to responses to the unmodulated noise at lower modulation frequencies and suppressed rate responses relative to responses to the unmodulated noise at middle modulation frequencies.NEW & NOTEWORTHY ML neurons synchronized less than A1 neurons, consistent with a hierarchical temporal-to-rate transformation. Both A1 and ML had a class of modulation transfer functions previously unreported in the cortex with a low-modulation-frequency (MF) peak, a middle-MF trough, and responses similar to unmodulated noise responses at high MFs. The results support a hierarchical shift toward a two-pool opponent code, where subtraction of neural activity between two populations of oppositely tuned neurons encodes AM.

Amplitude modulation transfer functions reveal opposing populations within both the inferior colliculus and medial geniculate body

Based on single-unit recordings of modulation transfer functions (MTFs) in the inferior colliculus (IC) and the medial geniculate body (MGB) of the unanesthetized rabbit, we identified two opposing populations: band-enhanced (BE) and band-suppressed (BS) neurons. In response to amplitude-modulated (AM) sounds, firing rates of BE and BS neurons were enhanced and suppressed, respectively, relative to their responses to an unmodulated noise with a one-octave bandwidth. We also identified a third population, designated hybrid neurons, whose firing rates were enhanced by some modulation frequencies and suppressed by others. Our finding suggests that perception of AM may be based on the co-occurrence of enhancement and suppression of responses of the opposing populations of neurons. Because AM carries an important part of the content of speech, progress in understanding auditory processing of AM sounds should lead to progress in understanding speech perception. Each of the BE, BS, and hybrid types of MTFs comprised approximately one-third of the total sample. Modulation envelopes having short duty cycles of 20-50% and raised-sine envelopes accentuated the degree of enhancement and suppression and sharpened tuning of the MTFs. With sinusoidal envelopes, peak modulation frequencies were centered around 32-64 Hz among IC BE neurons, whereas the MGB peak frequencies skewed toward lower frequencies, with a median of 16 Hz. We also tested an auditory-brainstem model and found that a simple circuit containing fast excitatory synapses and slow inhibitory synapses was able to reproduce salient features of the BE- and BS-type MTFs of IC neurons.NEW & NOTEWORTHY Opposing populations of neurons have been identified in the mammalian auditory midbrain and thalamus. In response to amplitude-modulated sounds, responses of one population (band-enhanced) increased whereas responses of another (band-suppressed) decreased relative to their responses to an unmodulated sound. These opposing auditory populations are analogous to the ON and OFF populations of the visual system and may improve transfer of information carried by the temporal envelopes of complex sounds such as speech.

The role of cochlear place coding in the perception of frequency modulation

Natural sounds convey information via frequency and amplitude modulations (FM and AM). Humans are acutely sensitive to the slow rates of FM that are crucial for speech and music. This sensitivity has long been thought to rely on precise stimulus-driven auditory-nerve spike timing (time code), whereas a coarser code, based on variations in the cochlear place of stimulation (place code), represents faster FM rates. We tested this theory in listeners with normal and impaired hearing, spanning a wide range of place-coding fidelity. Contrary to predictions, sensitivity to both slow and fast FM correlated with place-coding fidelity. We also used incoherent AM on two carriers to simulate place coding of FM and observed poorer sensitivity at high carrier frequencies and fast rates, two properties of FM detection previously ascribed to the limits of time coding. The results suggest a unitary place-based neural code for FM across all rates and carrier frequencies.

Neural fluctuation cues for simultaneous notched-noise masking and profile-analysis tasks: Insights from model midbrain responses

Results of simultaneous notched-noise masking are commonly interpreted as reflecting the bandwidth of underlying auditory filters. This interpretation assumes that listeners detect a tone added to notched-noise based on an increase in energy at the output of an auditory filter. Previous work challenged this assumption by showing that randomly and independently varying (roving) the levels of each stimulus interval does not substantially worsen listener thresholds [Lentz, Richards, and Matiasek (1999). J. Acoust. Soc. Am. 106, 2779-2792]. Lentz et al. further challenged this assumption by showing that filter bandwidths based on notched-noise results were different from those based on a profile-analysis task [Green (1983). Am. Psychol. 38, 133-142; (1988). (Oxford University Press, New York)], although these estimates were later reconciled by emphasizing spectral peaks of the profile-analysis stimulus [Lentz (2006). J. Acoust. Soc. Am. 120, 945-956]. Here, a single physiological model is shown to account for performance in fixed- and roving-level notched-noise tasks and the Lentz et al. profile-analysis task. This model depends on peripheral neural fluctuation cues that are transformed into the average rates of model inferior colliculus neurons. Neural fluctuations are influenced by peripheral filters, synaptic adaptation, cochlear amplification, and saturation of inner hair cells, an element not included in previous theories of envelope-based cues for these tasks. Results suggest reevaluation of the interpretation of performance in these paradigms.

Identifying cues for tone-in-noise detection using decision variable correlation in the budgerigar (Melopsittacus undulatus)

Previous studies evaluated cues for masked tone detection using reproducible noise waveforms. Human results founded on this approach suggest that tone detection is based on combined energy and envelope (ENV) cues, but detection cues in nonhuman species are less clear. Decision variable correlation (DVC) was used to evaluate tone-in-noise detection cues in the budgerigar, an avian species with human-like behavioral sensitivity to many complex sounds. DVC quantifies a model's ability to predict trial-by-trial variance in behavioral responses. Budgerigars were behaviorally conditioned to detect 500-Hz tones in wideband (WB; 100-3000 Hz) and narrowband (NB; 452-552 Hz) noise. Behavioral responses were obtained using a single-interval, two-alternative discrimination task and two-down, one-up adaptive tracking procedures. Tone-detection thresholds in WB noise were higher than human thresholds, putatively due to broader peripheral frequency tuning, whereas NB thresholds were within ∼1 dB of human results. Budgerigar average hit and false-alarm rates across noise waveforms were consistent, highly correlated across subjects, and correlated to human results. Trial-by-trial behavioral results in NB noise were best explained by a model combining energy and ENV cues. In contrast, WB results were better predicted by ENV-based or multiple-channel energy detector models. These results suggest that budgerigars and humans use similar cues for tone-in-noise detection.

Pitch of harmonic complex tones: rate and temporal coding of envelope repetition rate in inferior colliculus of unanesthetized rabbits

Harmonic complex tones (HCTs) found in speech, music, and animal vocalizations evoke strong pitch percepts at their fundamental frequencies. The strongest pitches are produced by HCTs that contain harmonics resolved by cochlear frequency analysis, but HCTs containing solely unresolved harmonics also evoke a weaker pitch at their envelope repetition rate (ERR). In the auditory periphery, neurons phase lock to the stimulus envelope, but this temporal representation of ERR degrades and gives way to rate codes along the ascending auditory pathway. To assess the role of the inferior colliculus (IC) in such transformations, we recorded IC neuron responses to HCT and sinusoidally modulated broadband noise (SAMN) with varying ERR from unanesthetized rabbits. Different interharmonic phase relationships of HCT were used to manipulate the temporal envelope without changing the power spectrum. Many IC neurons demonstrated band-pass rate tuning to ERR between 60 and 1,600 Hz for HCT and between 40 and 500 Hz for SAMN. The tuning was not related to the pure-tone best frequency of neurons but was dependent on the shape of the stimulus envelope, indicating a temporal rather than spectral origin. A phenomenological model suggests that the tuning may arise from peripheral temporal response patterns via synaptic inhibition. We also characterized temporal coding to ERR. Some IC neurons could phase lock to the stimulus envelope up to 900 Hz for either HCT or SAMN, but phase locking was weaker with SAMN. Together, the rate code and the temporal code represent a wide range of ERR, providing strong cues for the pitch of unresolved harmonics.NEW & NOTEWORTHY Envelope repetition rate (ERR) provides crucial cues for pitch perception of frequency components that are not individually resolved by the cochlea, but the neural representation of ERR for stimuli containing many harmonics is poorly characterized. Here we show that the pitch of stimuli with unresolved harmonics is represented by both a rate code and a temporal code for ERR in auditory midbrain neurons and propose possible underlying neural mechanisms with a computational model.

Nonlinear auditory models yield new insights into representations of vowels

Studies of vowel systems regularly appeal to the need to understand how the auditory system encodes and processes the information in the acoustic signal. The goal of this study is to present computational models to address this need, and to use the models to illustrate responses to vowels at two levels of the auditory pathway. Many of the models previously used to study auditory representations of speech are based on linear filter banks simulating the tuning of the inner ear. These models do not incorporate key nonlinear response properties of the inner ear that influence responses at conversational-speech sound levels. These nonlinear properties shape neural representations in ways that are important for understanding responses in the central nervous system. The model for auditory-nerve (AN) fibers used here incorporates realistic nonlinear properties associated with the basilar membrane, inner hair cells (IHCs), and the IHC-AN synapse. These nonlinearities set up profiles of f0-related fluctuations that vary in amplitude across the population of frequency-tuned AN fibers. Amplitude fluctuations in AN responses are smallest near formant peaks and largest at frequencies between formants. These f0-related fluctuations strongly excite or suppress neurons in the auditory midbrain, the first level of the auditory pathway where tuning for low-frequency fluctuations in sounds occurs. Formant-related amplitude fluctuations provide representations of the vowel spectrum in discharge rates of midbrain neurons. These representations in the midbrain are robust across a wide range of sound levels, including the entire range of conversational-speech levels, and in the presence of realistic background noise levels.

Modeling the effects of medial olivocochlear efferent stimulation at the level of the inferior colliculus

Various studies on medial olivocochlear (MOC) efferents have implicated it in multiple roles in the auditory system (e.g., dynamic range adaptation, masking reduction, and selective attention). This study presents a systematic simulation of inferior colliculus (IC) responses with and without electrical stimulation of the MOC. Phenomenological models of the responses of auditory nerve (AN) fibers and IC neurons were used to this end. The simulated responses were highly consistent with physiological data (replicated 3 of the 4 known rate-level responses all MOC effects-shifts, high stimulus level reduction and enhancement). Complex MOC efferent effects which were previously thought to require integration from different characteristic frequency (CF) neurons were simulated using the same frequency inhibition excitation circuitry. MOC-induced enhancing effects were found only in neurons with a CF range from 750 Hz to 2 kHz. This limited effect is indicative of the role of MOC activation on the AN responses at the stimulus offset.

Pitch of Harmonic Complex Tones: Rate Coding of Envelope Repetition Rate in the Auditory Midbrain

Envelope repetition rate (ERR) is an important cue for the pitch of harmonic complex tones (HCT), especially when the tone consists entirely of unresolved harmonics. Neural synchronization to the stimulus envelope provides a prominent cue for ERR in the auditory periphery, but this temporal code becomes degraded and gives way to rate codes in higher centers. The inferior colliculus (IC) likely plays a key role in this temporal-to-rate code transformation. Here we recorded single IC neuron responses to HCT at varying fundamental frequencies (F 0). ERR was manipulated by applying different inter-harmonic phase relationships. We identified a subset of neurons that showed a 'non-tonotopic' rate tuning to ERR between 160 and 1500 Hz. A comparison of neural responses to HCT and sinusoidally amplitude modulated (SAM) noise suggests that this tuning is dependent on the shape of stimulus envelope. A phenomenological model is able to reproduce the non-tonotopic tuning to ERR, and suggests it arises in the IC via synaptic inhibition.

Focal Suppression of Distractor Sounds by Selective Attention in Auditory Cortex

Auditory selective attention is required for parsing crowded acoustic environments, but cortical systems mediating the influence of behavioral state on auditory perception are not well characterized. Previous neurophysiological studies suggest that attention produces a general enhancement of neural responses to important target sounds versus irrelevant distractors. However, behavioral studies suggest that in the presence of masking noise, attention provides a focal suppression of distractors that compete with targets. Here, we compared effects of attention on cortical responses to masking versus non-masking distractors, controlling for effects of listening effort and general task engagement. We recorded single-unit activity from primary auditory cortex (A1) of ferrets during behavior and found that selective attention decreased responses to distractors masking targets in the same spectral band, compared with spectrally distinct distractors. This suppression enhanced neural target detection thresholds, suggesting that limited attention resources serve to focally suppress responses to distractors that interfere with target detection. Changing effort by manipulating target salience consistently modulated spontaneous but not evoked activity. Task engagement and changing effort tended to affect the same neurons, while attention affected an independent population, suggesting that distinct feedback circuits mediate effects of attention and effort in A1.

Supra-Threshold Hearing and Fluctuation Profiles: Implications for Sensorineural and Hidden Hearing Loss

An important topic in contemporary auditory science is supra-threshold hearing. Difficulty hearing at conversational speech levels in background noise has long been recognized as a problem of sensorineural hearing loss, including that associated with aging (presbyacusis). Such difficulty in listeners with normal thresholds has received more attention recently, especially associated with descriptions of synaptopathy, the loss of auditory nerve (AN) fibers as a result of noise exposure or aging. Synaptopathy has been reported to cause a disproportionate loss of low- and medium-spontaneous rate (L/MSR) AN fibers. Several studies of synaptopathy have assumed that the wide dynamic ranges of L/MSR AN fiber rates are critical for coding supra-threshold sounds. First, this review will present data from the literature that argues against a direct role for average discharge rates of L/MSR AN fibers in coding sounds at moderate to high sound levels. Second, the encoding of sounds at supra-threshold levels is examined. A key assumption in many studies is that saturation of AN fiber discharge rates limits neural encoding, even though the majority of AN fibers, high-spontaneous rate (HSR) fibers, have saturated average rates at conversational sound levels. It is argued here that the cross-frequency profile of low-frequency neural fluctuation amplitudes, not average rates, encodes complex sounds. As described below, this fluctuation-profile coding mechanism benefits from both saturation of inner hair cell (IHC) transduction and average rate saturation associated with the IHC-AN synapse. Third, the role of the auditory efferent system, which receives inputs from L/MSR fibers, is revisited in the context of fluctuation-profile coding. The auditory efferent system is hypothesized to maintain and enhance neural fluctuation profiles. Lastly, central mechanisms sensitive to neural fluctuations are reviewed. Low-frequency fluctuations in AN responses are accentuated by cochlear nucleus neurons which, either directly or via other brainstem nuclei, relay fluctuation profiles to the inferior colliculus (IC). IC neurons are sensitive to the frequency and amplitude of low-frequency fluctuations and convert fluctuation profiles from the periphery into a phase-locked rate profile that is robust across a wide range of sound levels and in background noise. The descending projection from the midbrain (IC) to the efferent system completes a functional loop that, combined with inputs from the L/MSR pathway, is hypothesized to maintain "sharp" supra-threshold hearing, reminiscent of visual mechanisms that regulate optical accommodation. Examples from speech coding and detection in noise are reviewed. Implications for the effects of synaptopathy on control mechanisms hypothesized to influence supra-threshold hearing are discussed. This framework for understanding neural coding and control mechanisms for supra-threshold hearing suggests strategies for the design of novel hearing aid signal-processing and electrical stimulation patterns for cochlear implants.

Temporal Coding of Voice Pitch Contours in Mandarin Tones

Accurate perception of time-variant pitch is important for speech recognition, particularly for tonal languages with different lexical tones such as Mandarin, in which different tones convey different semantic information. Previous studies reported that the auditory nerve and cochlear nucleus can encode different pitches through phase-locked neural activities. However, little is known about how the inferior colliculus (IC) encodes the time-variant periodicity pitch of natural speech. In this study, the Mandarin syllable /ba/ pronounced with four lexical tones (flat, rising, falling then rising and falling) were used as stimuli. Local field potentials (LFPs) and single neuron activity were simultaneously recorded from 90 sites within contralateral IC of six urethane-anesthetized and decerebrate guinea pigs in response to the four stimuli. Analysis of the temporal information of LFPs showed that 93% of the LFPs exhibited robust encoding of periodicity pitch. Pitch strength of LFPs derived from the autocorrelogram was significantly (p < 0.001) stronger for rising tones than flat and falling tones. Pitch strength are also significantly increased (p < 0.05) with the characteristic frequency (CF). On the other hand, only 47% (42 or 90) of single neuron activities were significantly synchronized to the fundamental frequency of the stimulus suggesting that the temporal spiking pattern of single IC neuron could encode the time variant periodicity pitch of speech robustly. The difference between the number of LFPs and single neurons that encode the time-variant F0 voice pitch supports the notion of a transition at the level of IC from direct temporal coding in the spike trains of individual neurons to other form of neural representation.

Developmental deprivation-induced perceptual and cortical processing deficits in awake-behaving animals

Sensory deprivation during development induces lifelong changes to central nervous system function that are associated with perceptual impairments. However, the relationship between neural and behavioral deficits is uncertain due to a lack of simultaneous measurements during task performance. Therefore, we telemetrically recorded from auditory cortex neurons in gerbils reared with developmental conductive hearing loss as they performed an auditory task in which rapid fluctuations in amplitude are detected. These data were compared to a measure of auditory brainstem temporal processing from each animal. We found that developmental HL diminished behavioral performance, but did not alter brainstem temporal processing. However, the simultaneous assessment of neural and behavioral processing revealed that perceptual deficits were associated with a degraded cortical population code that could be explained by greater trial-to-trial response variability. Our findings suggest that the perceptual limitations that attend early hearing loss are best explained by an encoding deficit in auditory cortex.

Preferred Tempo and Low-Audio-Frequency Bias Emerge From Simulated Sub-cortical Processing of Sounds With a Musical Beat

Prior research has shown that musical beats are salient at the level of the cortex in humans. Yet below the cortex there is considerable sub-cortical processing that could influence beat perception. Some biases, such as a tempo preference and an audio frequency bias for beat timing, could result from sub-cortical processing. Here, we used models of the auditory-nerve and midbrain-level amplitude modulation filtering to simulate sub-cortical neural activity to various beat-inducing stimuli, and we used the simulated activity to determine the tempo or beat frequency of the music. First, irrespective of the stimulus being presented, the preferred tempo was around 100 beats per minute, which is within the range of tempi where tempo discrimination and tapping accuracy are optimal. Second, sub-cortical processing predicted a stronger influence of lower audio frequencies on beat perception. However, the tempo identification algorithm that was optimized for simple stimuli often failed for recordings of music. For music, the most highly synchronized model activity occurred at a multiple of the beat frequency. Using bottom-up processes alone is insufficient to produce beat-locked activity. Instead, a learned and possibly top-down mechanism that scales the synchronization frequency to derive the beat frequency greatly improves the performance of tempo identification.

Persistent Auditory Nerve Damage Following Kainic Acid Excitotoxicity in the Budgerigar (Melopsittacus undulatus)

Permanent loss of auditory nerve (AN) fibers occurs with increasing age and sound overexposure, sometimes without hair cell damage or associated audiometric threshold elevation. Rodent studies suggest effects of AN damage on central processing and behavior, but these species have limited capacity to discriminate low-frequency speech-like sounds. Here, we introduce a new animal model of AN damage in an avian communication specialist, the budgerigar (Melopsittacus undulatus). The budgerigar is a vocal learner and speech mimic with sensitive low-frequency hearing and human-like behavioral sensitivity to many complex signals including speech components. Excitotoxic AN damage was induced through bilateral cochlear infusions of kainic acid (KA). Acute KA effects on cochlear function were assessed using AN compound action potentials (CAPs) and hair cell cochlear microphonics (CMs). Long-term KA effects were assessed using auditory brainstem response (ABR) measurements for up to 31 weeks post-KA exposure. KA infusion immediately abolished AN CAPs while having mild impact on the CM. ABR wave I, the far-field AN response, showed a pronounced 40-75 % amplitude reduction at moderate-to-high sound levels that persisted for the duration of the study. In contrast, wave I latency and the amplitude of wave V were nearly unaffected by KA, and waves II-IV were less reduced than wave I. ABR thresholds, calculated based on complete response waveforms, showed no impairment following KA. These results demonstrate that KA exposure in the budgerigar causes irreversible AN damage, most likely through excitotoxic injury to afferent fibers or synapses as in other species, while sparing ABR thresholds. Normal wave V amplitude, assumed to originate centrally, may persist through compensatory mechanisms that restore central response amplitude by downregulating inhibition. Future studies in this new animal model of AN damage can explore effects of this neural lesion, in isolation from hair cell trauma and threshold elevation, on central processing and perception of complex sounds.

Formant-frequency discrimination of synthesized vowels in budgerigars (Melopsittacus undulatus) and humans

Vowels are complex sounds with four to five spectral peaks known as formants. The frequencies of the two lowest formants, F1and F2, are sufficient for vowel discrimination. Behavioral studies show that many birds and mammals can discriminate vowels. However, few studies have quantified thresholds for formant-frequency discrimination. The present study examined formant-frequency discrimination in budgerigars (Melopsittacus undulatus) and humans using stimuli with one or two formants and a constant fundamental frequency of 200 Hz. Stimuli had spectral envelopes similar to natural speech and were presented with random level variation. Thresholds were estimated for frequency discrimination of F1, F2, and simultaneous F1 and F2 changes. The same two-down, one-up tracking procedure and single-interval, two-alternative task were used for both species. Formant-frequency discrimination thresholds were as sensitive in budgerigars as in humans and followed the same patterns across all conditions. Thresholds expressed as percent frequency difference were higher for F1 than for F2, and were unchanged between stimuli with one or two formants. Thresholds for simultaneous F1 and F2 changes indicated that discrimination was based on combined information from both formant regions. Results were consistent with previous human studies and show that budgerigars provide an exceptionally sensitive animal model of vowel feature discrimination.

Neural coding of time-varying interaural time differences and time-varying amplitude in the inferior colliculus

Binaural cues occurring in natural environments are frequently time varying, either from the motion of a sound source or through interactions between the cues produced by multiple sources. Yet, a broad understanding of how the auditory system processes dynamic binaural cues is still lacking. In the current study, we directly compared neural responses in the inferior colliculus (IC) of unanesthetized rabbits to broadband noise with time-varying interaural time differences (ITD) with responses to noise with sinusoidal amplitude modulation (SAM) over a wide range of modulation frequencies. On the basis of prior research, we hypothesized that the IC, one of the first stages to exhibit tuning of firing rate to modulation frequency, might use a common mechanism to encode time-varying information in general. Instead, we found weaker temporal coding for dynamic ITD compared with amplitude modulation and stronger effects of adaptation for amplitude modulation. The differences in temporal coding of dynamic ITD compared with SAM at the single-neuron level could be a neural correlate of "binaural sluggishness," the inability to perceive fluctuations in time-varying binaural cues at high modulation frequencies, for which a physiological explanation has so far remained elusive. At ITD-variation frequencies of 64 Hz and above, where a temporal code was less effective, noise with a dynamic ITD could still be distinguished from noise with a constant ITD through differences in average firing rate in many neurons, suggesting a frequency-dependent tradeoff between rate and temporal coding of time-varying binaural information.NEW & NOTEWORTHY Humans use time-varying binaural cues to parse auditory scenes comprising multiple sound sources and reverberation. However, the neural mechanisms for doing so are poorly understood. Our results demonstrate a potential neural correlate for the reduced detectability of fluctuations in time-varying binaural information at high speeds, as occurs in reverberation. The results also suggest that the neural mechanisms for processing time-varying binaural and monaural cues are largely distinct.

Midbrain Synchrony to Envelope Structure Supports Behavioral Sensitivity to Single-Formant Vowel-Like Sounds in Noise

Vowels make a strong contribution to speech perception under natural conditions. Vowels are encoded in the auditory nerve primarily through neural synchrony to temporal fine structure and to envelope fluctuations rather than through average discharge rate. Neural synchrony is thought to contribute less to vowel coding in central auditory nuclei, consistent with more limited synchronization to fine structure and the emergence of average-rate coding of envelope fluctuations. However, this hypothesis is largely unexplored, especially in background noise. The present study examined coding mechanisms at the level of the midbrain that support behavioral sensitivity to simple vowel-like sounds using neurophysiological recordings and matched behavioral experiments in the budgerigar. Stimuli were harmonic tone complexes with energy concentrated at one spectral peak, or formant frequency, presented in quiet and in noise. Behavioral thresholds for formant-frequency discrimination decreased with increasing amplitude of stimulus envelope fluctuations, increased in noise, and were similar between budgerigars and humans. Multiunit recordings in awake birds showed that the midbrain encodes vowel-like sounds both through response synchrony to envelope structure and through average rate. Whereas neural discrimination thresholds based on either coding scheme were sufficient to support behavioral thresholds in quiet, only synchrony-based neural thresholds could account for behavioral thresholds in background noise. These results reveal an incomplete transformation to average-rate coding of vowel-like sounds in the midbrain. Model simulations suggest that this transformation emerges due to modulation tuning, which is shared between birds and mammals. Furthermore, the results underscore the behavioral relevance of envelope synchrony in the midbrain for detection of small differences in vowel formant frequency under real-world listening conditions.

Simulating electrical modulation detection thresholds using a biophysical model of the auditory nerve

Modulation detection thresholds (MDTs) assess listeners' sensitivity to changes in the temporal envelope of a signal and have been shown to strongly correlate with speech perception in cochlear implant users. MDTs are simulated with a stochastic model of a population of auditory nerve fibers that has been verified to accurately simulate a number of physiologically important temporal response properties. The procedure to estimate detection thresholds has previously been applied to stimulus discrimination tasks. The population model simulates the MDT-stimulus intensity relationship measured in cochlear implant users. The model also recreates the shape of the modulation transfer function and the relationship between MDTs and carrier rate. Discrimination based on fluctuations in synchronous firing activity predicts better performance at low carrier rates, but quantitative measures of modulation coding predict better neural representation of high carrier rate stimuli. Manipulating the number of fibers and a temporal integration parameter, the width of a sliding temporal integration window, varies properties of the MDTs, such as cutoff frequency and peak threshold. These results demonstrate the importance of using a multi-diameter fiber population in modeling the MDTs and demonstrate a wider applicability of this model to simulating behavioral performance in cochlear implant listeners.

Neural correlates of behavioral amplitude modulation sensitivity in the budgerigar midbrain

Amplitude modulation (AM) is a crucial feature of many communication signals, including speech. Whereas average discharge rates in the auditory midbrain correlate with behavioral AM sensitivity in rabbits, the neural bases of AM sensitivity in species with human-like behavioral acuity are unexplored. Here, we used parallel behavioral and neurophysiological experiments to explore the neural (midbrain) bases of AM perception in an avian speech mimic, the budgerigar (Melopsittacus undulatus). Behavioral AM sensitivity was quantified using operant conditioning procedures. Neural AM sensitivity was studied using chronically implanted microelectrodes in awake, unrestrained birds. Average discharge rates of multiunit recording sites in the budgerigar midbrain were insufficient to explain behavioral sensitivity to modulation frequencies <100 Hz for both tone- and noise-carrier stimuli, even with optimal pooling of information across recording sites. Neural envelope synchrony, in contrast, could explain behavioral performance for both carrier types across the full range of modulation frequencies studied (16-512 Hz). The results suggest that envelope synchrony in the budgerigar midbrain may underlie behavioral sensitivity to AM. Behavioral AM sensitivity based on synchrony in the budgerigar, which contrasts with rate-correlated behavioral performance in rabbits, raises the possibility that envelope synchrony, rather than average discharge rate, might also underlie AM perception in other species with sensitive AM detection abilities, including humans. These results highlight the importance of synchrony coding of envelope structure in the inferior colliculus. Furthermore, they underscore potential benefits of devices (e.g., midbrain implants) that evoke robust neural synchrony.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear-nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately.

SIGNIFICANCE STATEMENT

An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too.

Neural population encoding and decoding of sound source location across sound level in the rabbit inferior colliculus

At lower levels of sensory processing, the representation of a stimulus feature in the response of a neural population can vary in complex ways across different stimulus intensities, potentially changing the amount of feature-relevant information in the response. How higher-level neural circuits could implement feature decoding computations that compensate for these intensity-dependent variations remains unclear. Here we focused on neurons in the inferior colliculus (IC) of unanesthetized rabbits, whose firing rates are sensitive to both the azimuthal position of a sound source and its sound level. We found that the azimuth tuning curves of an IC neuron at different sound levels tend to be linear transformations of each other. These transformations could either increase or decrease the mutual information between source azimuth and spike count with increasing level for individual neurons, yet population azimuthal information remained constant across the absolute sound levels tested (35, 50, and 65 dB SPL), as inferred from the performance of a maximum-likelihood neural population decoder. We harnessed evidence of level-dependent linear transformations to reduce the number of free parameters in the creation of an accurate cross-level population decoder of azimuth. Interestingly, this decoder predicts monotonic azimuth tuning curves, broadly sensitive to contralateral azimuths, in neurons at higher levels in the auditory pathway.

Speech Coding in the Brain: Representation of Vowel Formants by Midbrain Neurons Tuned to Sound Fluctuations

Current models for neural coding of vowels are typically based on linear descriptions of the auditory periphery, and fail at high sound levels and in background noise. These models rely on either auditory nerve discharge rates or phase locking to temporal fine structure. However, both discharge rates and phase locking saturate at moderate to high sound levels, and phase locking is degraded in the CNS at middle to high frequencies. The fact that speech intelligibility is robust over a wide range of sound levels is problematic for codes that deteriorate as the sound level increases. Additionally, a successful neural code must function for speech in background noise at levels that are tolerated by listeners. The model presented here resolves these problems, and incorporates several key response properties of the nonlinear auditory periphery, including saturation, synchrony capture, and phase locking to both fine structure and envelope temporal features. The model also includes the properties of the auditory midbrain, where discharge rates are tuned to amplitude fluctuation rates. The nonlinear peripheral response features create contrasts in the amplitudes of low-frequency neural rate fluctuations across the population. These patterns of fluctuations result in a response profile in the midbrain that encodes vowel formants over a wide range of levels and in background noise. The hypothesized code is supported by electrophysiological recordings from the inferior colliculus of awake rabbits. This model provides information for understanding the structure of cross-linguistic vowel spaces, and suggests strategies for automatic formant detection and speech enhancement for listeners with hearing loss.

Auditory distance coding in rabbit midbrain neurons and human perception: monaural amplitude modulation depth as a cue

Mechanisms underlying sound source distance localization are not well understood. Here we tested the hypothesis that a novel mechanism can create monaural distance sensitivity: a combination of auditory midbrain neurons' sensitivity to amplitude modulation (AM) depth and distance-dependent loss of AM in reverberation. We used virtual auditory space (VAS) methods for sounds at various distances in anechoic and reverberant environments. Stimulus level was constant across distance. With increasing modulation depth, some rabbit inferior colliculus neurons increased firing rates whereas others decreased. These neurons exhibited monotonic relationships between firing rates and distance for monaurally presented noise when two conditions were met: (1) the sound had AM, and (2) the environment was reverberant. The firing rates as a function of distance remained approximately constant without AM in either environment and, in an anechoic condition, even with AM. We corroborated this finding by reproducing the distance sensitivity using a neural model. We also conducted a human psychophysical study using similar methods. Normal-hearing listeners reported perceived distance in response to monaural 1 octave 4 kHz noise source sounds presented at distances of 35-200 cm. We found parallels between the rabbit neural and human responses. In both, sound distance could be discriminated only if the monaural sound in reverberation had AM. These observations support the hypothesis. When other cues are available (e.g., in binaural hearing), how much the auditory system actually uses the AM as a distance cue remains to be determined.

Neural coding of sound envelope in reverberant environments

Speech reception depends critically on temporal modulations in the amplitude envelope of the speech signal. Reverberation encountered in everyday environments can substantially attenuate these modulations. To assess the effect of reverberation on the neural coding of amplitude envelope, we recorded from single units in the inferior colliculus (IC) of unanesthetized rabbit using sinusoidally amplitude modulated (AM) broadband noise stimuli presented in simulated anechoic and reverberant environments. Although reverberation degraded both rate and temporal coding of AM in IC neurons, in most neurons, the degradation in temporal coding was smaller than the AM attenuation in the stimulus. This compensation could largely be accounted for by the compressive shape of the modulation input-output function (MIOF), which describes the nonlinear transformation of modulation depth from acoustic stimuli into neural responses. Additionally, in a subset of neurons, the temporal coding of AM was better for reverberant stimuli than for anechoic stimuli having the same modulation depth at the ear. Using hybrid anechoic stimuli that selectively possess certain properties of reverberant sounds, we show that this reverberant advantage is not caused by envelope distortion, static interaural decorrelation, or spectral coloration. Overall, our results suggest that the auditory system may possess dual mechanisms that make the coding of amplitude envelope relatively robust in reverberation: one general mechanism operating for all stimuli with small modulation depths, and another mechanism dependent on very specific properties of reverberant stimuli, possibly the periodic fluctuations in interaural correlation at the modulation frequency.