Background: Breathing rate is affected by physical stressors such as temperature or hypercapnia and by psychosocial stressors such as noise or overcrowding. In behavioral tests for tinnitus, rodents are often presented with trains of startle pulses. We postulated that using these pulses at successively higher sound levels would produce a cumulative increase in stress. Here, we demonstrate a novel means of assessing that increase in stress. Methods: By placing pairs of reflective markers on the abdomen and using a motion tracking system, we were able to remotely measure respiratory movements. A series of 20 startle pulses were presented in sequence at seven increasing sound levels, and changes in respiratory rate were tested with the Wilcoxon matched-pairs signed rank test and the Friedman Test. Results: Markers placed on 20 alert active mice showed evidence of sniffing behavior but no purely respiratory signal. By contrast, in all 18 guinea pigs, abdominal markers did track respiratory movements. The breathing rate in guinea pigs was similar to previous studies: (mean 104 ± 13; range 86–131 bpm). Presenting quiet startle pulses to guinea pigs caused a significant increase in breathing rate (by about 20%), even with pulses at 75–80 dB SPL. Increasing pulse sound levels in the range of 85–105 dB SPL did not reliably produce any further increase in breathing rate. Conclusions: We propose that tracking abdominal movement may allow measurement of psychosocial stress in the guinea pig. Once an animal is startled, increasing the pulse sound level did not produce any further increase in stress levels.

The dynamic fluctuations in the amplitude of sound, known as sound envelopes, are ubiquitous in natural sounds and convey information critical for the recognition of speech, and of sounds generally. We are perceptually most sensitive to slow modulations which are most common. However, previous studies of envelope coding in the brainstem found an under-representation of these slow, low-frequency, modulations. Specifically, the synchronization of spike times to the envelope was enhanced in some neuron types, forming channels specialized for envelope processing but tuned to a restricted range of fast, high-frequency, envelopes (200-500 Hz). Here, we show using a historical dataset from cats that previous analyses, which made strong assumptions about the neural code, underestimated the encoding of low-frequency envelopes. While some neurons encode envelope better than others, most encode a wide range of envelope frequencies, and represent slower envelope fluctuations most accurately in their precise patterns of spike times. Identification of envelope frequency from spike-timing was linked to reliability, and to the way that dynamics of spiking interacted with the time-varying envelope. In some of the best-performing neurons, temporally complex "mode-locked" spike patterns served to enhance envelope coding. A second long-standing contradiction was that neural envelope coding is degraded at high sound levels, whilst the perception of envelope is robust at a wide range of sound levels. We find that spike-time encoding of envelope shape becomes level-robust for small populations of neurons. These findings argue against feature-specific coding of envelopes in the brainstem, and for a distributed population spike-time code for which synchrony to the envelope is an incomplete description. This code is accurate for slow fluctuations and robust across sound level. Thus, precise spike-timing information in the brainstem is after-all aligned with the needs of communication and the perception of environmental sounds.

Rodent models of tinnitus are commonly used to study its mechanisms and potential treatments. Tinnitus can be identified by changes in the gap-induced prepulse inhibition of the acoustic startle (GPIAS), most commonly by using pressure detectors to measure the whole-body startle (WBS). Unfortunately, the WBS habituates quickly, the measuring system can introduce mechanical oscillations and the response shows considerable variability. We have instead used a motion tracking system to measure the localized motion of small reflective markers in response to an acoustic startle reflex in guinea pigs and mice. For guinea pigs, the pinna had the largest responses both in terms of displacement between pairs of markers and in terms of the speed of the reflex movement. Smaller, but still reliable responses were observed with markers on the thorax, abdomen and back. The peak speed of the pinna reflex was the most sensitive measure for calculating GPIAS in the guinea pig. Recording the pinna reflex in mice proved impractical due to removal of the markers during grooming. However, recordings from their back and tail allowed us to measure the peak speed and the twitch amplitude (area under curve) of reflex responses and both analysis methods showed robust GPIAS. When mice were administered high doses of sodium salicylate, which induces tinnitus in humans, there was a significant reduction in GPIAS, consistent with the presence of tinnitus. Thus, measurement of the peak speed or twitch amplitude of pinna, back and tail markers provides a reliable assessment of tinnitus in rodents.

What happens when we hear? Where does the sound go when it enters our ears? Our ears sense the vibrations of the air and convert them into electrical signals the brain can process. But that is only the start. The brain uses tens of thousands of nerve cells to hear even the quietest or simplest sound. With those nerve cells, the brain is solving a never-ending puzzle: figuring out what is going on in the world. To do that, the brain must separate out sounds that are occurring at the same time, recognize them, and describe them in lots of ways, such as how loud a sound is and where it is coming from. This article gives an overview of how the ears and brain work together, so we can live in a world of sound.

We automatically use more than one of our senses to understand the world around us. When having a conversation, most of us use our ears to listen to what other people are saying. But you might be surprised to know that what you see is also very important in helping you to understand others. This article looks at how hearing and sight are combined and explains how both of these senses help us to understand speech. We demonstrate how important it is to see the faces of people who are talking, particularly when we are in noisy places. This topic has important implications for the wearing of face masks! It is really important that we think about how face masks may affect the ability of people to communicate with each other.

Humans and many other animals can hear a wide range of sounds. We can hear low and high notes and both quiet and loud sounds. We are also very good at telling the difference between sounds that are similar, like the speech sounds “argh” and “ah,” and picking apart sounds that are mixed together, like when an orchestra is playing. But how do human hearing abilities compare to those of other animals? In this article, we discover how the inner ear determines hearing abilities. Many other mammals can hear very high notes that we cannot, and some can hear quiet sounds that we cannot. However, humans may be better than any other species at distinguishing similar sounds. We know this because, milliseconds after the sounds around us go into our ears, other sounds come out: sounds that are actually produced by those same ears!

Tinnitus has similarities to chronic neuropathic pain where there are changes in the firing rate of different types of afferent neurons. We postulated that one possible cause of tinnitus is a change in the distribution of spontaneous firing rates in at least one type of afferent auditory nerve fibre in anaesthetised guinea pigs. In control animals there was a bimodal distribution of spontaneous rates, but the position of the second mode was different depending upon whether the fibres responded best to high (> 4 kHz) or low (≤4 kHz) frequency tonal stimulation. The simplest and most reliable way of inducing tinnitus in experimental animals is to administer a high dose of sodium salicylate. The distribution of the spontaneous firing rates was different when salicylate (350 mg/kg) was administered, even when the sample was matched for the distribution of characteristic frequencies in the control population. The proportion of medium spontaneous rate fibres (MSR, 1≤ spikes/s ≤20) increased while the proportion of the highest, high spontaneous firing rate fibres (HSR, > 80 spikes/s) decreased following salicylate. The median rate fell from 64.7 spikes/s (control) to 35.4 spikes/s (salicylate); a highly significant change (Kruskal-Wallis test p < 0.001). When the changes were compared with various models of statistical probability, the most accurate model was one where most HSR fibres decreased their firing rate by 32 spikes/s. Thus, we have shown a reduction in the firing rate of HSR fibres that may be related to tinnitus.

Correlational evidence in humans suggests that selective difficulties hearing in noisy, social settings may reflect premature auditory nerve degeneration. Here, we induced primary cochlear neural degeneration (CND) in adult mice and found direct behavioral evidence for selective detection deficits in background noise. To identify central determinants for this perceptual disorder, we tracked daily changes in ensembles of layer 2/3 auditory cortex parvalbumin-expressing inhibitory neurons and excitatory pyramidal neurons with chronic two-photon calcium imaging. CND induced distinct forms of plasticity in cortical excitatory and inhibitory neurons that culminated in net hyperactivity, increased neural gain, and reduced adaptation to background noise. Ensemble activity measured while mice detected targets in noise could accurately decode whether individual behavioral trials were hits or misses. After CND, random surges of hypercorrelated cortical activity occurring just before target onset reliably predicted impending detection failures, revealing a source of internal cortical noise underlying perceptual difficulties in external noise.Copyright © 2021 Elsevier Inc. All rights reserved. PMID: 33561398 Funding information This work was supported by: NIDCD NIH HHS, United States Grant ID: R01 DC009836

Epidemiological studies identify midlife hearing loss as an independent risk factor for dementia, estimated to account for 9% of cases. We evaluate candidate brain bases for this relationship. These bases include a common pathology affecting the ascending auditory pathway and multimodal cortex, depletion of cognitive reserve due to an impoverished listening environment, and the occupation of cognitive resources when listening in difficult conditions. We also put forward an alternate mechanism, drawing on new insights into the role of the medial temporal lobe in auditory cognition. In particular, we consider how aberrant activity in the service of auditory pattern analysis, working memory, and object processing may interact with dementia pathology in people with hearing loss. We highlight how the effect of hearing interventions on dementia depends on the specific mechanism and suggest avenues for work at the molecular, neuronal, and systems levels to pin this down.Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. PMID: 32871106 Funding information This work was supported by: Medical Research Council, United Kingdom Grant ID: MR/T032553/1 Wellcome Trust, United Kingdom Grant ID: WT106964MA NIDCD NIH HHS, United States Grant ID: R01 DC004290 NIDCD NIH HHS, United States Grant ID: P50 DC000242 Wellcome Trust, United Kingdom Grant ID: 210567/Z/18/Z Wellcome Trust, United Kingdom More Less keyboard_arrow_down

When hearing fails, electrical cochlear implants (eCIs) provide the brain with auditory information. One important bottleneck of CIs is the poor spectral selectivity that results from the wide current spread from each of the electrode contacts. Optical CIs (oCIs) promise to make better use of the tonotopic order of spiral ganglion neurons (SGNs) inside the cochlea by spatially confined stimulation. Here, we established multichannel oCIs based on light-emitting diode (LED) arrays and used them for optical stimulation of channelrhodopsin (ChR)-expressing SGNs in rodents. Power-efficient blue LED chips were integrated onto microfabricated 15-μm-thin polyimide-based carriers comprising interconnecting lines to address individual LEDs by a stationary or mobile driver circuitry. We extensively characterized the optoelectronic, thermal, and mechanical properties of the oCIs and demonstrated stability over weeks in vitro. We then implanted the oCIs into ChR-expressing rats and gerbils, and characterized multichannel optogenetic SGN stimulation by electrophysiological and behavioral experiments. Improved spectral selectivity was directly demonstrated by recordings from the auditory midbrain. Long-term experiments in deafened ChR-expressing rats and in nontreated control animals demonstrated specificity of optogenetic stimulation. Behavioral studies on animals carrying a wireless oCI sound processor revealed auditory percepts. This study demonstrates hearing restoration with improved spectral selectivity by an LED-based multichannel oCI system.Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. PMID: 32718992

Conspecific acceptance thresholds (Reeve 1989 Am. Nat. 133 , 407–435), which have been widely applied to explain ecological behaviour in animals, proposed how sensory information, prior information and the costs of decisions determine actions. Signal detection theory (Green & Swets 1966 Signal detection theory and psychophysics ; SDT), which forms the basis of CAT models, has been widely used in psychological studies to partition the ability to discriminate sensory information from the action made as a result of it. In this article, we will review the application of SDT in interpreting the behaviour of laboratory animals trained in operant conditioning tasks and then consider its potential in ecological studies of animal behaviour in natural environments. Focusing on the nest-mate recognition systems exhibited by social insects, we show how the quantitative application of SDT has the potential to transform acceptance rate data into independent indices of cue sensitivity and decision criterion (also known as the acceptance threshold). However, further tests of the assumptions underlying SDT analysis are required. Overall, we argue that SDT, as conventionally applied in psychological studies, may provide clearer insights into the mechanistic basis of decision making and information processing in behavioural ecology. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

Perceiving speech in background noise presents a significant challenge to listeners. Intelligibility can be improved by seeing the face of a talker. This is of particular value to hearing impaired people and users of cochlear implants. It is well known that auditory-only speech understanding depends on factors beyond audibility. How these factors impact on the audio-visual integration of speech is poorly understood. We investigated audio-visual integration when either the interfering background speech (Experiment 1) or intelligibility of the target talkers (Experiment 2) was manipulated. Clear speech was also contrasted with sine-wave vocoded speech to mimic the loss of temporal fine structure with a cochlear implant. Experiment 1 showed that for clear speech, the visual speech benefit was unaffected by the number of background talkers. For vocoded speech, a larger benefit was found when there was only one background talker. Experiment 2 showed that visual speech benefit depended upon the audio intelligibility of the talker and increased as intelligibility decreased. Degrading the speech by vocoding resulted in even greater benefit from visual speech information. A single “independent noise” signal detection theory model predicted the overall visual speech benefit in some conditions but could not predict the different levels of benefit across variations in the background or target talkers. This suggests that, similar to audio-only speech intelligibility, the integration of audio-visual speech cues may be functionally dependent on factors other than audibility and task difficulty, and that clinicians and researchers should carefully consider the characteristics of their stimuli when assessing audio-visual integration.

A fundamental task of the ascending auditory system is to produce representations that facilitate the recognition of complex sounds. This is particularly challenging in the context of acoustic variability, such as that between different talkers producing the same phoneme. These representations are transformed as information is propagated throughout the ascending auditory system from the inner ear to the auditory cortex (AI). Investigating these transformations and their role in speech recognition is key to understanding hearing impairment and the development of future clinical interventions. Here, we obtained neural responses to an extensive set of natural vowel-consonant-vowel phoneme sequences, each produced by multiple talkers, in three stages of the auditory processing pathway. Auditory nerve (AN) representations were simulated using a model of the peripheral auditory system and extracellular neuronal activity was recorded in the inferior colliculus (IC) and primary auditory cortex (AI) of anaesthetized guinea pigs. A classifier was developed to examine the efficacy of these representations for recognizing the speech sounds. Individual neurons convey progressively less information from AN to AI. Nonetheless, at the population level, representations are sufficiently rich to facilitate recognition of consonants with a high degree of accuracy at all stages indicating a progression from a dense, redundant representation to a sparse, distributed one. We examined the timescale of the neural code for consonant recognition and found that optimal timescales increase throughout the ascending auditory system from a few milliseconds in the periphery to several tens of milliseconds in the cortex. Despite these longer timescales, we found little evidence to suggest that representations up to the level of AI become increasingly invariant to across-talker differences. Instead, our results support the idea that the role of the subcortical auditory system is one of dimensionality expansion, which could provide a basis for flexible classification of arbitrary speech sounds.

Frequency analysis of sound by the cochlea is the most fundamental property of the auditory system. Despite its importance, the resolution of this frequency analysis in humans remains controversial. The controversy persists because the methods used to estimate tuning in humans are indirect and have not all been independently validated in other species. Some data suggest that human cochlear tuning is considerably sharper than that of laboratory animals, while others suggest little or no difference between species. We show here in a single species (ferret) that behavioral estimates of tuning bandwidths obtained using perceptual masking methods, and objective estimates obtained using otoacoustic emissions, both also employed in humans, agree closely with direct physiological measurements from single auditory-nerve fibers. Combined with human behavioral data, this outcome indicates that the frequency analysis performed by the human cochlea is of significantly higher resolution than found in common laboratory animals. This finding raises important questions about the evolutionary origins of human cochlear tuning, its role in the emergence of speech communication, and the mechanisms underlying our ability to separate and process natural sounds in complex acoustic environments.

When presented with two vowels simultaneously, humans are often able to identify the constituent vowels. Computational models exist that simulate this ability, however they predict listener confusions poorly, particularly in the case where the two vowels have the same fundamental frequency. Presented here is a model that is uniquely able to predict the combined representation of concurrent vowels. The given model is able to predict listener's systematic perceptual decisions to a high degree of accuracy.