A computational model of auditory chirp-velocity sensitivity and amplitude-modulation tuning in inferior colliculus neurons.

We demonstrate a model of chirp-velocity sensitivity in the inferior colliculus (IC) that retains the tuning to amplitude modulation (AM) that was established in earlier models. The mechanism of velocity sensitivity is sequence detection by octopus cells of the posteroventral cochlear nucleus, which have been proposed in physiological studies to respond preferentially to the order of arrival of cross-frequency inputs of different amplitudes. Model architecture is based on coincidence detection of a combination of excitatory and inhibitory inputs. Chirp-sensitivity of the IC output is largely controlled by the strength and timing of the chirp-sensitive octopus-cell inhibitory input. AM tuning is controlled by inhibition and excitation that are tuned to the same frequency. We present several example neurons that demonstrate the feasibility of the model in simulating realistic chirp-sensitivity and AM tuning for a wide range of characteristic frequencies. Additionally, we explore the systematic impact of varying parameters on model responses. The proposed model can be used to assess the contribution of IC chirp-velocity sensitivity to responses to complex sounds, such as speech.

A Subcortical Model for Auditory Forward Masking with Efferent Control of Cochlear Gain.

Previous physiological and psychophysical studies have explored whether feedback to the cochlea from the efferent system influences forward masking. The present work proposes that the limited growth-of-masking (GOM) observed in auditory nerve (AN) fibers may have been misunderstood; namely, that this limitation may be due to the influence of anesthesia on the efferent system. Building on the premise that the unanesthetized AN may exhibit GOM similar to more central nuclei, the present computational modeling study demonstrates that feedback from the medial olivocochlear (MOC) efferents may contribute to GOM observed physiologically in onset-type neurons in both the cochlear nucleus and inferior colliculus (IC). Additionally, the computational model of MOC efferents used here generates a decrease in masking with longer masker-signal delays similar to that observed in IC physiology and in psychophysical studies. An advantage of this explanation over alternative physiological explanations (e.g., that forward masking requires inhibition from the superior paraolivary nucleus) is that this theory can explain forward masking observed in the brainstem, early in the ascending pathway. For explaining psychoacoustic results, one strength of this model is that it can account for the lack of elevation in thresholds observed when masker level is randomly varied from interval-to-interval, a result that is difficult to explain using the conventional temporal window model of psychophysical forward masking. Future directions for evaluating the efferent mechanism as a contributing mechanism for psychoacoustic results are discussed.

Otoacoustic emissions predict cochlear-nerve but not behavioral frequency tuning in an avian vocal-communication specialist.

Frequency analysis by the cochlea forms a key foundation for all subsequent auditory processing. Stimulus-frequency otoacoustic emissions (SFOAEs) are a potentially powerful alternative to traditional behavioral experiments for estimating cochlear tuning without invasive testing, as is necessary in humans. Which methods accurately predict cochlear tuning remains controversial due to only a single animal study comparing SFOAE-based, behavioral, and cochlear frequency tuning in the same species. The budgerigar is a parakeet species with human-like behavioral sensitivity to many sounds and the capacity to mimic speech. Multiple studies show that budgerigars exhibit a perceptual "auditory fovea" with sharpest behavioral frequency tuning at mid frequencies from 3.5-4 kHz, in contrast to the typical pattern of monotonically increasing tuning sharpness for higher characteristic frequencies. We measured SFOAE-based and cochlear-afferent tuning in budgerigars, for comparison to previously reported behavioral results. SFOAE-based and cochlear-afferent tuning sharpness both increased monotonically for higher frequencies, in contrast to the behavioral pattern. Thus, SFOAE-based tuning in budgerigars accurately predicted cochlear tuning, and both measures aligned with typical patterns of cochlear frequency tuning in other species. Given divergent behavioral tuning in the budgerigars, which could reflect specializations for central processing of masked signals, these results highlight the value of SFOAEs for estimating cochlear tuning and caution against direct inference of cochlear tuning from behavioral results.

Outer hair cells stir cochlear fluids.

Recent observations regarding the non-selective action of outer hair cells contradict frequency-selective cochlear amplification. We hypothesized that active outer hair cells drive cochlear fluid circulation. The hypothesis was tested by delivering a neurotoxin, kainic acid, to the round window of young gerbil cochleae while monitoring auditory responses in the cochlear nucleus. Sounds presented at a modest level significantly expedited kainic acid delivery. When outer-hair-cell motility was suppressed by salicylate, the facilitation effect was compromised. A low-frequency tone was more effective than broadband noise, especially for drug delivery to apical locations. Computational model simulations provided the physical basis for our observation, which incorporated solute diffusion, fluid advection, fluid-structure interaction, and outer-hair-cell motility. Active outer hair cells deformed the organ of Corti like a peristaltic tube to generate apically streaming flows along the tunnel of Corti and basally streaming flows along the scala tympani. Our measurements and simulations coherently indicate that broadband outer-hair-cell action is for cochlear fluid circulation.

A Computational Model of Auditory Chirp-Velocity Sensitivity and Amplitude-Modulation Tuning in Inferior Colliculus Neurons.

We demonstrate a model of chirp-velocity sensitivity in the inferior colliculus (IC) that retains the tuning to amplitude modulation (AM) that was established in earlier models. The mechanism of velocity sensitivity is sequence detection by octopus cells of the posteroventral cochlear nucleus, which have been proposed in physiological studies to respond preferentially to the order of arrival of cross-frequency inputs of different amplitudes. Model architecture is based on coincidence detection of a combination of excitatory and inhibitory inputs. Chirp-sensitivity of the IC output is largely controlled by the strength and timing of the chirp-sensitive octopus-cell inhibitory input. AM tuning is controlled by inhibition and excitation that are tuned to the same frequency. We present several example neurons that demonstrate the feasibility of the model in simulating realistic chirp-sensitivity and AM tuning for a wide range of characteristic frequencies. Additionally, we explore the systematic impact of varying parameters on model responses. The proposed model can be used to assess the contribution of IC chirp-velocity sensitivity to responses to complex sounds, such as speech.

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.

Subcortical auditory model including efferent dynamic gain control with inputs from cochlear nucleus and inferior colliculus.

An auditory model has been developed with a time-varying, gain-control signal based on the physiology of the efferent system and subcortical neural pathways. The medial olivocochlear (MOC) efferent stage of the model receives excitatory projections from fluctuation-sensitive model neurons of the inferior colliculus (IC) and wide-dynamic-range model neurons of the cochlear nucleus. The response of the model MOC stage dynamically controls cochlear gain via simulated outer hair cells. In response to amplitude-modulated (AM) noise, firing rates of most IC neurons with band-enhanced modulation transfer functions in awake rabbits increase over a time course consistent with the dynamics of the MOC efferent feedback. These changes in the rates of IC neurons in awake rabbits were employed to adjust the parameters of the efferent stage of the proposed model. Responses of the proposed model to AM noise were able to simulate the increasing IC rate over time, whereas the model without the efferent system did not show this trend. The proposed model with efferent gain control provides a powerful tool for testing hypotheses, shedding insight on mechanisms in hearing, specifically those involving the efferent system.

Sensitivity to direction and velocity of fast frequency chirps in the inferior colliculus of awake rabbit.

Neurons in the mammalian inferior colliculus (IC) are sensitive to the velocity (speed and direction) of fast frequency chirps contained in Schroeder-phase harmonic complexes (SCHR). However, IC neurons are also sensitive to stimulus periodicity, a prominent feature of SCHR stimuli. Here, to disentangle velocity sensitivity from periodicity tuning, we introduced a novel stimulus consisting of aperiodic random chirps. Extracellular, single-unit recordings were made in the IC of Dutch-belted rabbits in response to both SCHR and aperiodic chirps. Rate-velocity functions were constructed from aperiodic-chirp responses and compared to SCHR rate profiles, revealing interactions between stimulus periodicity and neural velocity sensitivity. A generalized linear model analysis demonstrated that periodicity tuning influences SCHR response rates more strongly than velocity sensitivity. Principal component analysis of rate-velocity functions revealed that neurons were more often sensitive to the direction of lower-velocity chirps and were less often sensitive to the direction of higher-velocity chirps. Overall, these results demonstrate that sensitivity to chirp velocity is common in the IC. Harmonic sounds with complex phase spectra, such as speech and music, contain chirps, and velocity sensitivity would shape IC responses to these sounds.

Dissecting neural computations in the human auditory pathway using deep neural networks for speech.

The human auditory system extracts rich linguistic abstractions from speech signals. Traditional approaches to understanding this complex process have used linear feature-encoding models, with limited success. Artificial neural networks excel in speech recognition tasks and offer promising computational models of speech processing. We used speech representations in state-of-the-art deep neural network (DNN) models to investigate neural coding from the auditory nerve to the speech cortex. Representations in hierarchical layers of the DNN correlated well with the neural activity throughout the ascending auditory system. Unsupervised speech models performed at least as well as other purely supervised or fine-tuned models. Deeper DNN layers were better correlated with the neural activity in the higher-order auditory cortex, with computations aligned with phonemic and syllabic structures in speech. Accordingly, DNN models trained on either English or Mandarin predicted cortical responses in native speakers of each language. These results reveal convergence between DNN model representations and the biological auditory pathway, offering new approaches for modeling neural coding in the auditory cortex.

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.

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.

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.

Inherent envelope fluctuations in forward masking: Effects of age and hearing loss.

Forward masking is generally greater for Gaussian noise (GN) than for low-fluctuation noise maskers, i.e., GN disruption. Because the minimal hearing loss that is associated with older age may affect GN disruption differently than more significant hearing loss, the current study explored the contribution of minimal hearing loss associated with older age to GN disruption. GN disruption was measured using three masker-signal delays (25, 75, and 150 ms) for three adult groups: younger participants with normal hearing (NH), older participants with minimal hearing loss, and older participants with sensorineural hearing loss. The role of underlying mechanisms was tested using a computational model for midbrain neurons. The primary result suggests that older listeners with mild threshold elevations that typically occur with age may be more susceptible to the deleterious effects of masker envelope fluctuations than younger listeners with NH. Results from the computational model indicate that there may be a larger influence of efferent feedback and saturation of inner hair cells on forward masking and GN disruption than previously considered.

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.

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.

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.

A comparative study of eight human auditory models of monaural processing.

A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.

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 with 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, whereas 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.

Predicting speech intelligibility in hearing-impaired listeners using a physiologically inspired auditory model.

This study presents a major update and full evaluation of a speech intelligibility (SI) prediction model previously introduced by Scheidiger, Carney, Dau, and Zaar [(2018), Acta Acust. United Ac. 104, 914-917]. The model predicts SI in speech-in-noise conditions via comparison of the noisy speech and the noise-alone reference. The two signals are processed through a physiologically inspired nonlinear model of the auditory periphery, for a range of characteristic frequencies (CFs), followed by a modulation analysis in the range of the fundamental frequency of speech. The decision metric of the model is the mean of a series of short-term, across-CF correlations between population responses to noisy speech and noise alone, with a sensitivity-limitation process imposed. The decision metric is assumed to be inversely related to SI and is converted to a percent-correct score using a single data-based fitting function. The model performance was evaluated in conditions of stationary, fluctuating, and speech-like interferers using sentence-based speech-reception thresholds (SRTs) previously obtained in 5 normal-hearing (NH) and 13 hearing-impaired (HI) listeners. For the NH listener group, the model accurately predicted SRTs across the different acoustic conditions (apart from a slight overestimation of the masking release observed for fluctuating maskers), as well as plausible effects in response to changes in presentation level. For HI listeners, the model was adjusted to account for the individual audiograms using standard assumptions concerning the amount of HI attributed to inner-hair-cell (IHC) and outer-hair-cell (OHC) impairment. HI model results accounted remarkably well for elevated individual SRTs and reduced masking release. Furthermore, plausible predictions of worsened SI were obtained when the relative contribution of IHC impairment to HI was increased. Overall, the present model provides a useful tool to accurately predict speech-in-noise outcomes in NH and HI listeners, and may yield important insights into auditory processes that are crucial for speech understanding.

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.