Biology subjects

Carney, L. H.

Publications and source records attributed to Carney, L. H..

10 recordsLinked to original sources

bioRxiv2024

Auditory Forward Masking Explained by a Subcortical Model 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 account for 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 psychoacoustical results are discussed. Significance StatementThe simulations presented here demonstrate that a recent computational model of the auditory subcortex including medial-olivocochlear efferents generates forward masking, an increase in detection threshold for a short probe tone following a preceding sound. This model explains results from physiological recordings and suggests potential connections to psychoacoustic experiments. The theory that efferent control of cochlear gain is a contributing mechanism for forward masking has several advantages. This theory can explain the strength of masking exhibited by cochlear nucleus neurons, a phenomenon not explained by current physiological theories in which the strength of forward-masking is not increased relative to the periphery until later in the ascending pathway. Additionally, this theory explains results for a psychoacoustic task with random variation in masker level, results not explained by the theory that persistent masker energy interferes with detection of the probe.

neuroscience↗

bioRxiv2023

A fast and flexible approximation of power-law adaptation for auditory computational models

1.Power-law adaptation is a form of neural adaptation that has been shown to provide a better description of auditory-nerve adaptation dynamics as compared to simpler exponential-adaptation processes. However, the computational costs associated with power-law adaptation are high and, problematically, grow superlinearly with the number of samples in the simulation. This cost limits the applicability of power-law adaptation in simulations of responses to relatively long stimuli, such as speech, or in simulations for which high sampling rates are needed. Here, we present a simple approximation to power-law adaptation based on a parallel set of exponential-adaptation processes with different time constants, demonstrate that the approximation improves on an existing approximation provided in the literature, and provide updates to a popular phenomenological model of the auditory periphery that implements the new approximation.

neuroscience↗

bioRxiv2023

Profile analysis in listeners with sensorineural hearing loss: behavioral data and computational models

Many sounds contain spectral modulations at multiple scales, but much is still unknown about how such spectral features are represented in the auditory system. One behavioral task that provides insight into this question is profile analysis. In a typical profile-analysis task, listeners are asked to discriminate between a complex tone with equal-amplitude components and a complex tone with a single incremented component. Because listeners can perform profile analysis even when the overall sound level of the stimuli is randomized from interval to interval, this task is thought to be a useful index of relative processing of spectral shape, rather than just sensitivity to absolute level changes. Here, we measured profile analysis across the frequency range in a group of listeners that varied widely in their hearing status. We then modeled the resulting behavioral data by decoding responses to the stimuli from computational models of the auditory nerve and inferior colliculus. We found that both hearing loss at the target frequency and increases in the target frequency were associated with poorer profile-analysis thresholds, and that these results could both be explained as the result of corresponding changes in sensitivity of temporal modulation-sensitive cells at the level of the inferior colliculus. These results suggest that key features of profile-analysis may reflect the limits of central neural tuning to temporal modulations.

neuroscience↗

bioRxiv2023

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

neuroscience↗

bioRxiv2022

Auditory-nerve Model including Efferent Dynamic Gain Control with Inputs from Cochlear Nucleus and Inferior Colliculus

We developed an auditory model with a time-varying, gain-control signal based on the physiology of the efferent system and the sub-cortical neural pathways. The medial olivocochlear (MOC) efferent stage of the model receives excitatory projections from both 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, while 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.

neuroscience↗

bioRxiv2022

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.

neuroscience↗

bioRxiv2022

Distinguishing sensitivity to direction and velocity of fast frequency chirps from periodicity tuning in the inferior colliculus

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. HighlightsIC neurons had diverse sensitivity to chirp velocity (speed and direction) of periodic and aperiodic-chirp stimuli. Both velocity and periodicity sensitivity were necessary to predict neural responses to Schroeder-phase harmonic complexes. Neurons were more commonly sensitive to the direction of chirps at lower-speeds (e.g., < 2 kHz/ms) than higher-speeds (e.g., > 2 kHz/ms) in the tested range. The chirp speeds for which IC neurons were most sensitive are present in common harmonic sounds with realistic phase spectra, such as speech and music.

neuroscience↗

bioRxiv2022

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 either rising or falling instantaneous-frequency sweeps within periods of the fundamental frequency (F0), depending on the phase-scaling parameter C. Human thresholds for tone detection 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 the impulse response of cochlear filtering, though this hypothesis remains controversial. Birds provide an interesting animal model for studies of Schroeder masking because prior reports suggest less behavioral threshold difference between maskers with opposite C values. However, most behavioral studies focused on relatively low masker F0s, and neurophysiological mechanisms in birds have not been explored. We performed behavioral Schroeder-masking experiments in budgerigars (Melopsittacus undulatus) using a wide range of masker F0 and C values. The signal frequency was 2800 Hz. Neural recordings at the midbrain processing level 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 studies. Neural recordings showed prominent temporal and rate-based encoding of Schroeder F0, and in many neurons, marked response asymmetry between Schroeder stimuli with opposite C values. Neural thresholds for Schroeder-masked tone detection were (1) in most cases based on a response decrement compared to the masker alone, consistent with prominent modulation tuning in midbrain neurons, and (2) generally similar between opposite masker C values. These results highlight the likely importance of envelope cues in behavioral studies of Schroeder masking.

neuroscience↗

bioRxiv2022

Representations of fricatives in sub-cortical model responses: comparisons with human 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/inter-subject 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 x 9 fricatives x 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 them with published behavioral data. The modeled AN and IC neural responses provided better predictions of behavioral accuracy than the stimulus spectra, with IC showing 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.

neuroscience↗

bioRxiv2022

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, 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 normal hearing. 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 thought.

neuroscience↗