Auditory-Nerve Responses in Mice with Noise-Induced Cochlear Synaptopathy

Cochlear synaptopathy is the noise-induced or age-related loss of ribbon synapses between inner hair cells (IHCs) and auditory nerve fibers (ANFs), first reported in CBA/CaJ mice. Recordings from single ANFs in anaesthesized, noise-exposed guinea pigs suggested that neurons with low spontaneous rates (SRs) and high thresholds are more vulnerable than low-threshold, high-SR fibers. However, there is extensive post-exposure regeneration of ANFs in guinea pigs, but not in mice. Here, we exposed CBA/CaJ mice to octave-band noise and recorded sound-evoked and spontaneous activity from single ANFs at least 2 weeks later. Confocal analysis of cochleae immunostained for pre- and post-synaptic markers confirmed the expected loss of 40 - 50% of ANF synapses in the basal half of the cochlea, however, our data were not consistent with a selective loss of low-SR fibers. Rather they suggested a loss of both SR groups in synaptopathic regions. Single-fiber thresholds and frequency tuning recovered to pre-exposure levels however, response to tone bursts showed increased peak and steady-state firing rates as well as decreased jitter in first-spike latencies. This apparent gain-of-function increased the robustness of tone-burst responses in the presence of continuous masking noise. This study suggests that the nature of noise-induced synaptic damage varies between different species and that, in mouse, the noise-induced hyperexcitability seen in central auditory circuits is also observed at the level of the auditory nerve.

Ecological validity of masking release with speech-like stimuli

Comodulated masking noise and binaural cues can facilitate detecting a target sound from noise. These cues can induce a decrease in detection thresholds, quantified as comodulation masking release (CMR) and binaural masking level difference (BMLD), respectively. However, their relevance to speech perception is unclear as most studies have used artificial stimuli different from speech. Here, we investigated their ecological validity using sounds with speech-like spectro-temporal dynamics. We evaluated the ecological validity of such grouping effect with stimuli reflecting formant changes in speech. We set three masker bands at formant frequencies F1, F2, and F3 based on CV combination: /gu/, /fu/, and /pu/. We found that the CMR was little (< 3 dB) while BMLD was comparable to previous findings (~ 9 dB). In conclusion, we suggest that other features may play a role in facilitating frequency grouping by comodulation such as the spectral proximity and the number of masker bands.

Auditory Psychophysics in Birds: the Effects of Unique Noise on Sensitivity

<p>The performances of observers in auditory experiments are likely to be affected by extraneous noise from physiological or neurological sources and also by decision noise. Attempts have been made to measure the characteristics of this noise, in particular its level relative to that of masking noise provided by the experimenter. This study investigated an alternative approach, a method of analysis which seeks to reduce the effects of extraneous noise on measures derived from experimental data. Group-Operating-Characteristic (GOC) analysis was described by Watson (1963) and investigated by Boven (1976). Boven distinguished between common and unique noise. GOC analysis seeks to reduce the effects of unique noise. In the analysis, ratings of the same stimulus on different occasions are sunned. The cumulative frequency distributions of the resulting variable define a GOC curve. This curve is analogous to an ROC curve, but since the effects of unique noise tend to be averaged out during the summation, the GOC is less influenced by extraneous noise. The amount of improvement depends on the relative variance of the unique and common noise (k). Higher levels of unique noise lead to greater improvement. In this study four frequency discrimination experiments were carried out with pigeons as observers, using a three-key operant procedure. In other experiments, computer-simulated observers were used. The first two pigeon experiments, and the simulations, were based on known distributions of common noise. The ROCs for the constructed distributions provided a standard with which the GOC curve could be compared. In all cases the analysis led to improvements in the measures of performance and increased the match of the experimental results and the ideal ROC. The amount of improvement, as well as reflecting the level of unique noise, depended on the number of response categories. With smaller numbers of categories, improvement was reduced and k was underestimated. Since the pigeon observers made only "yes" or "no" responses, the results for the pigeon experiments were compared with the results of simulations with known distributions in order to obtain more accurate estimates of k. The third and fourth pigeon experiments involved frequency discrimination tasks with a standard of 450 Hz and comparison frequencies of 500, 600, 700, 800 and 900 Hz, and 650 Hz, respectively. With the multiple comparison frequencies the results were very variable. This was due to the small number of trials for each frequency and the small number of replications. The results obtained with one comparison frequency were more orderly but, like those of the previous experiment, were impossible to distinguish from those which would be expected if there was no common noise. A final set of experiments was based on a hardware simulation. Signals first used in the fourth pigeon experiment were processed by a system made up of a filter, a zero-axis crossing detector and a simulated observer. The results of these experiments were compatible with the possibility that the amount of unique noise in the pigeon experiments overwhelmed any evidence of common noise.</p>

Auditory Psychophysics in Birds: the Effects of Unique Noise on Sensitivity

<p>The performances of observers in auditory experiments are likely to be affected by extraneous noise from physiological or neurological sources and also by decision noise. Attempts have been made to measure the characteristics of this noise, in particular its level relative to that of masking noise provided by the experimenter. This study investigated an alternative approach, a method of analysis which seeks to reduce the effects of extraneous noise on measures derived from experimental data. Group-Operating-Characteristic (GOC) analysis was described by Watson (1963) and investigated by Boven (1976). Boven distinguished between common and unique noise. GOC analysis seeks to reduce the effects of unique noise. In the analysis, ratings of the same stimulus on different occasions are sunned. The cumulative frequency distributions of the resulting variable define a GOC curve. This curve is analogous to an ROC curve, but since the effects of unique noise tend to be averaged out during the summation, the GOC is less influenced by extraneous noise. The amount of improvement depends on the relative variance of the unique and common noise (k). Higher levels of unique noise lead to greater improvement. In this study four frequency discrimination experiments were carried out with pigeons as observers, using a three-key operant procedure. In other experiments, computer-simulated observers were used. The first two pigeon experiments, and the simulations, were based on known distributions of common noise. The ROCs for the constructed distributions provided a standard with which the GOC curve could be compared. In all cases the analysis led to improvements in the measures of performance and increased the match of the experimental results and the ideal ROC. The amount of improvement, as well as reflecting the level of unique noise, depended on the number of response categories. With smaller numbers of categories, improvement was reduced and k was underestimated. Since the pigeon observers made only "yes" or "no" responses, the results for the pigeon experiments were compared with the results of simulations with known distributions in order to obtain more accurate estimates of k. The third and fourth pigeon experiments involved frequency discrimination tasks with a standard of 450 Hz and comparison frequencies of 500, 600, 700, 800 and 900 Hz, and 650 Hz, respectively. With the multiple comparison frequencies the results were very variable. This was due to the small number of trials for each frequency and the small number of replications. The results obtained with one comparison frequency were more orderly but, like those of the previous experiment, were impossible to distinguish from those which would be expected if there was no common noise. A final set of experiments was based on a hardware simulation. Signals first used in the fourth pigeon experiment were processed by a system made up of a filter, a zero-axis crossing detector and a simulated observer. The results of these experiments were compatible with the possibility that the amount of unique noise in the pigeon experiments overwhelmed any evidence of common noise.</p>

The effect of the preceding masking noise on monaural and binaural release from masking

When a target tone is preceded by a noise, the threshold for target detection can be increased or decreased depending on the type of a preceding masker. The effect of preceding masker to the following sound can be interpreted as either the result of adaptation at the periphery or at the system level. To disentangle these, we investigated the time constant of adaptation by varying the length of the preceding masker. For inducing various masking conditions, we designed stimuli that can induce masking release. Comodulated masking noise and binaural cues can facilitate detecting a target sound from noise. These cues induce a decrease in detection thresholds, quantified as comodulation masking release (CMR) and binaural masking level difference (BMLD), respectively. We hypothesized that if the adaptation results from the top-down processing, both CMR and BMLD will be affected with increased length of the preceding masker. We measured CMR and BMLD when the length of preceding maskers varied from 0 (no preceding masker) to 500 ms. Results showed that CMR was more affected with longer preceding masker from 100 ms to 500 ms while the preceding masker did not affect BMLD. In this study, we suggest that the adaptation to preceding masking sound may arise from low level (e.g. cochlear nucleus, CN) rather than the temporal integration by the higher-level processing.

Acoustic deterrents influence foraging activity, flight and echolocation behaviour of free-flying bats

Acoustic deterrents have shown potential as a viable mitigation measure to reduce human impacts on bats, however, the mechanisms underpinning acoustic deterrence of bats have yet to be explored. Bats avoid ambient ultrasound in their environment and alter their echolocation calls in response to masking noise. Using stereo thermal videogrammetry and acoustic methods, we tested predictions that i) bats would avoid acoustic deterrents and forage and social call less in a ‘treated airspace’; ii) deterrents would cause bats to fly with more direct flight paths akin to commuting behaviour and in line with a reduction in foraging activity, resulting in increased flight speed and decreased flight tortuosity; iii) bats would alter their echolocation call structure in response to the masking deterrent sound. As predicted, overall bat activity was reduced by 30% and we recorded a significant reduction in counts of Pipistrellus pygmaeus (27%), Myotis spp. (probably M. daubentonii) (26%) and Nyctalus and Eptesicus spp. (68%) passes. P. pygmaeus feeding buzzes were also reduced by the deterrent in relation to general activity (by 38%), however social calls were not (only 23% reduction). Bats also increased their flight speed and reduced the tortuosity of their flight paths and P. pygmaeus reduced echolocation call bandwidth and start frequency of calls in response to deterrent playback, probably due to the masking effect of the sound. Deterrence could therefore be used to remove bats from areas where they forage, for example wind turbines and roads, where they may be under threat from direct mortality.

TAAC - TMS Adaptable Auditory Control: a universal tool to mask TMS click

BackgroundCoupling transcranial magnetic stimulation with electroencephalography (TMS-EEG) allows recording the EEG response to a direct, non-invasive cortical perturbation. However, obtaining a genuine TMS-evoked EEG potential requires controlling for several confounds, among which a main source is represented by the auditory evoked potentials (AEPs) associated to the TMS discharge noise (TMS click). This contaminating factor can be in principle prevented by playing a masking noise through earphones.New methodHere we release TMS Adaptable Auditory Control (TAAC), a highly flexible, open-source, Matlab®-based interface that generates in real-time customized masking noises. TAAC creates noises starting from the stimulator-specific TMS click and tailors them to fit the individual, subject-specific click perception by mixing and manipulating the standard noises in both time and frequency domains.ResultsWe showed that TAAC allows us to provide standard as well as customized noises able to effectively and safely mask the TMS click.Comparison with existing methodsHere, we showcased two customized noises by comparing them to two standard noises previously used in the TMS literature (i.e., a white noise and a noise generated from the stimulator-specific TMS click only). For each, we quantified the Sound Pressure Level (SPL; measured by a Head and Torso Simulator - HATS) required to mask the TMS click in a population of 20 healthy subjects. Both customized noises were effective at safe (according to OSHA and NIOSH safety guidelines), lower SPLs with respect to standard noises.ConclusionsAt odds with previous methods, TAAC allows creating effective and safe masking noises specifically tailored on each TMS device and subject. The combination of TAAC with tools for the real-time visualization of TEPs can help control the influence of auditory confounds also in non-compliant patients. Finally, TAAC is a highly flexible and open-source tool, so it can be further extended to meet different experimental requirements.

Data Augmentation for Roller Bearing Health Indicator Estimation Using Multi-Channel Frequency Data Representations

This paper demonstrates various data augmentation techniques that can be used when working with limited run-to-failure data to estimate health indicators related to the remaining useful life of roller bearings. The PRONOSTIA bearing prognosis dataset is used for benchmarking data augmentation techniques. The input to the networks are multi-dimensional frequency representations obtained by combining the spectra taken from two accelerometers. Data augmentation techniques are adapted from other machine learning fields and include adding Gaussian noise, region masking, masking noise, and pitch shifting. Augmented datasets are used in training a conventional CNN architecture comprising two convolutional and pooling layer sequences with batch normalization. Results from individually separating each bearing’s data for the purpose of validation shows that all methods, except pitch shifting, give improved validation accuracy on average. Masking noise and region masking both show the added benefit of dataset regularization by giving results that are more consistent after repeatedly training each configuration with new randomly generated augmented datasets. It is shown that gradually deteriorating bearings and bearings with abrupt failure are not treated significantly differently by the augmentation techniques.

Experimental Observations in Tire Cavity Resonance and Interactions with Periodic Noise Components

Tire cavity resonance is one of the major sources of tire-related in-cabin noise and vibration. It has gained more attention in recent years with the growth of the electric vehicle market. This is due to the absence of masking noise from the internal combustion engine and powertrain. Thus, the mitigation of this issue has become a critical task for tire and vehicle manufacturers. The excited cavity resonant frequency in an unloaded condition is typically between 170 - 220 Hz. However, multiple studies have shown that loading the tire will result in two dominant resonances transmitted into the cavity. Their corresponding mode shapes are typically described in terms of the direction of their characteristic acoustic pressure variation i.e., fore-aft cavity mode and vertical cavity mode. As the tire's rotational speed increases, in-cabin measurements show that the tire cavity resonant frequencies separate from each other. Further, interactions with the periodic component of tire noise at certain speeds are also observed. These periodic components can be attributed to tire non-uniformities and tread pattern related excitation. This interaction is perceived as tonal noise inside the vehicle cabin at discrete speeds. This work presents experimental results summarizing these findings.