David McAlpine

Many individuals experience problems that are undetected by standard hearing tests, such as persistent tinnitus and difficulties understanding speech in background noise. Here, we report evidence of altered neural gain in young adults with self-reported listening problems despite exceptional hearing thresholds. Individuals reporting persistent tinnitus—the daily percept of sound in the absence of an external source—exhibited elevated thresholds of the middle ear muscle reflex, suggestive of altered gain in brainstem reflexive circuits, and reduced cortical responses to auditory spatial cues conveyed in the temporal fine structure of low-frequency sounds. Moreover, in both groups, greater self-reported speech-in-noise difficulties were associated with higher magnitude cortical responses—particularly at the highest stimulus intensity—consistent with elevated neural gain. Using a conceptual model, we demonstrate how damage to high-threshold auditory nerve fibres innervating cochlear nuclei can account for reduced activity of binaural neurons sensitive to the temporal fine structure of low-frequency sounds, generating a compensatory increase in neural gain in higher brain centres that impacts listening in complex environments.

The auditory brain excels at extracting predictive regularities from sound, but the neural and temporal mechanisms mediating long-term learning of these regularities remain poorly understood. Here, using a perceptual anchoring paradigm, we investigate whether the dorsolateral prefrontal cortex (dlPFC) is causally required to transform transient regularities into stable internal templates (anchors). We characterized the behavioural dynamics of anchoring to predicable acoustic events using sensitivity (d') and decision bias (c) metrics, alongside growth curve analysis (GCA) to model trial-by-trial learning. Listeners exhibited a robust anchoring effect, showing significantly higher sensitivity in decision strategy for recurring acoustic regularities compared to novel ones. This implicit anchoring was driven selectively by specific features in regular sequences - the local repetition of an acoustic motif - whereas explicit memory indiscriminately encoded the entire acoustic episode. To test for causality, we applied inhibitory continuous theta-burst stimulation (cTBS) to the dlPFC. Crucially, not only did this not impair anchoring, but significantly accelerated the rate of anchoring for predictable patterns, suggesting the dlPFC may act as a source of top-down interference in implicit learning. In contrast to predictable sequences, inhibition of dlPFC disrupted the initial precision of online comparisons for novel sequences, though insulating against the rapid, interference-driven reduction in performance or novel sequences in observed in listeners subjected to a sham cTBS procedure. These findings reveal a functional dissociation. Whilst dlPFC provides an essential buffer for novel sensory comparisons, long-term consolidation of regularities in acoustic sequences relies on a robust implicit pathway independent of prefrontal control.

Sensory systems must represent a vast range of stimulus dimensions and energy whilst subject to metabolic constraints. Efficient-coding theory predicts that neural adaptation re-allocates a relatively limited range of neural activity toward the most informative stimulus values, but it is unclear how subtle peripheral lesions shift this operating point in central circuits. Hearing is a stringent test because sound level varies enormously across environments, yet clinical assessment still relies heavily on tone-detection thresholds that can miss listening deficits in noise. We analyzed extracellular recordings from single neurons in the gerbil auditory midbrain across 14 animals in four experimental groups exposed to unfolding distributions of sound intensities drawn either uniformly from a wide range (24-96 decibels) of sound pressure levels or from contexts in which 80% of levels were restricted to a 12-decibel high-probability range. For each context we summarized each neuron’s rate-intensity input-output function by an effective threshold and gain, and we interpreted the resulting threshold-gain distributions with an information-cost model that trades bits of stimulus information against a penalty on mean spiking. Noise exposure consistent with loss of synapses between inner-ear cells and auditory nerve fibers altered gain modulation across acoustic contexts, with noise-exposed animals showing compressed gain adjustments relative to controls; within the information-cost framework, the clearest hidden-hearing-loss effect was a quiet-context utility advantage distributed across low- and intermediate-threshold neurons, whereas moderate-to-loud contexts showed weaker or absent group differences. Temporary conductive attenuation caused by ear-canal plugging shifted effective thresholds to higher sound levels, with incomplete recovery after plug removal; the corresponding optimization-prior trajectories were consistent with incomplete rapid renormalization but were weaker than the hidden-hearing-loss effect. These results support an efficient-coding interpretation of altered central auditory representations after subtle lesions and provide a quantitative, context-based framework for comparing mechanisms of hearing difficulty beyond threshold-only tests and Fisher information alone. Author Summary: Everyday hearing is an ecological challenge for the auditory system: we must follow speech while background sounds fluctuate and overlap. Standard tests emphasize tone-detection thresholds, but many listeners struggle in noise even when thresholds appear normal. We asked whether subtle peripheral changes shift how the auditory brain trades information for neural effort. We analyzed recordings from single neurons in the gerbil auditory midbrain during sound environments with different loudness statistics, including ones dominated by a narrow intensity range. Using information-theoretic measures, we quantified how much spikes distinguished sound-level categories and related this to the amount of spiking produced. Noise exposure consistent with inner-ear synaptic loss altered gain modulation across acoustic contexts and most strongly improved model-based coding utility in quieter settings, but reduced adaptation and efficiency as sound environments became louder. Temporary ear-canal plugging raised effective response thresholds substantially above both control and synaptopathy groups, with only partial recovery immediately after plug removal. By mapping both manipulations onto a common information-versus-cost scale, we highlight context-dependent metrics that may prove more informative than threshold audiograms for subtle hearing problems.

Navigating complex sensory environments is critical to survival, and brain mechanisms have evolved to cope with the wide range of surroundings we encounter. To determine how listeners learn the statistical properties of acoustic spaces, we assessed their ability to perceive speech in a range of noisy and reverberant rooms. Listeners were also exposed to repetitive transcranial stimulation (rTMS) to disrupt the dorsolateral prefrontal cortex (dlPFC) activity, a region believed to play a role in statistical learning. Our data suggest listeners rapidly adapt to statistical characteristics of an environment to improve speech understanding. This ability is impaired when rTMS is applied bilaterally to the dlPFC. The data demonstrate that speech understanding in noise is best when exposed to a room with reverberant characteristics common to human-built environments, with performance declining for higher and lower reverberation times, including fully anechoic (non-reverberant) environments. Our findings provide evidence for a reverberation “sweet spot” and the presence of brain mechanisms that might have evolved to cope with the acoustic characteristics of listening environments encountered every day.

Measures of autistic traits are only useful – for pre-diagnostic screening, exploring individual differences, and gaining personal insight – if they efficiently and accurately assess autism as currently conceptualised while maintaining psychometric validity across different demographic groups. We recruited 1322 autistic and 1279 non-autistic adults who varied in autism status (non-autistic, diagnosed autistic, self-identifying autistic) and gender (cisgender men, cisgender women, gender diverse) to assess the psychometric properties of the Comprehensive Autistic Trait Inventory, a recently developed measure of autistic traits that examines six trait domains using 42 self-report statements. Factor fit for the six subscales was appropriate, as was total-scale and subscale reliability. Importantly, measurement invariance was demonstrated based on both autism status and gender, indicating that Comprehensive Autistic Trait Inventory scores of these group members can be directly compared. Autistic traits were highly similar between diagnosed and self-identifying autistic adults, while gender-diverse participants showed more autistic traits than their cisgender counterparts. A total-scale discrimination threshold of 147.5 calculated was suggested which corresponded to sensitivity and specificity of 77.20 and 87.41, respectively. Our analysis indicates that the Comprehensive Autistic Trait Inventory is a practical measure of autistic traits in non-autistic and autistic participants that is useful for researchers and clinicians and for affirming self-identity. Lay The Comprehensive Autistic Trait Inventory (CATI) is a free questionnaire designed to measure autistic traits in both autistic and non-autistic adults. The CATI includes 42 items focusing on six areas: Social Interactions, Communication, Social Camouflage, Self-Regulating Behaviours, Cognitive Flexibility, and Sensory Sensitivity. Here, we set out to determine whether the CATI can accurately measure autistic traits in both autistic (both diagnosed and self-identifying) and non-autistic people, as well as people of different genders. We also wanted to explore the extent to which trait scores differed between these groups of individuals. Our study recruited over 2600 participants, including 1322 autistic and 1279 non-autistic adults. Our findings suggest that the CATI works the way it was designed to. It is a reliable and accurate tool for measuring autistic traits, can distinguish between autistic and non-autistic people, and appears appropriate for people of different genders. Notably, we found that people who self-identify as autistic have similar trait scores to those with a clinical diagnosis of autism and that gender-diverse people scored higher on autistic traits compared to cisgender people. Our data suggest that the CATI is a useful tool for measuring autistic traits in autistic and non-autistic people and for understanding the way that autistic people vary from one another. It should be helpful for researchers and clinicians, and support a public understanding of autism.

Navigating complex sensory environments is critical to survival, and brain mechanisms have evolved to cope with the wide range of surroundings we encounter. To determine how listeners learn the statistical properties of acoustic spaces, we assessed their ability to perceive speech in a range of noisy and reverberant rooms. Listeners were also exposed to repetitive transcranial stimulation (rTMS) to disrupt the dorsolateral prefrontal cortex (dlPFC) activity, a region believed to play a role in statistical learning. Our data suggest listeners rapidly adapt to statistical characteristics of an environment to improve speech understanding. This ability is impaired when rTMS is applied bilaterally to the dlPFC. The data demonstrate that speech understanding in noise is best when exposed to a room with reverberant characteristics common to human-built environments, with performance declining for higher and lower reverberation times, including fully anechoic (non-reverberant) environments. Our findings provide evidence for a reverberation “sweet spot” and the presence of brain mechanisms that might have evolved to cope with the acoustic characteristics of listening environments encountered every day.

Autistic people often report a heightened sensitivity to sound. Yet, research into Autistic people’s auditory environments and their impacts on quality of life is limited. We conducted an online survey to understand how auditory environments influence the relationships between Autistic traits and impacts on quality of life (iQoL) due to sound sensitivity. We also sought to determine strategies that Autistic people use to navigate auditory sensitivities in daily life. 296 Autistic adults (58.4% women, 15.9% men, 24.3% non-binary +) aged 18–71 years completed the survey comprising a questionnaire with bespoke items measuring auditory experiences in different environments (e.g., noisy vs. quiet) and measures of Autistic traits and iQoL. Our path analyses revealed a significant indirect effect of aversive auditory environments on the relationships between all domains of Autistic traits and iQoL. Notably, the association between non-verbal social communication trait and iQoL was fully mediated by all forms of auditory environments. Additionally, most (n = 217, 73.5%) Autistic participants reported using earplugs and headphones to manage their sound environments in everyday life. Our study demonstrates that many aspects of auditory environments—beyond noise alone―can negatively impact Autistic people’s QoL. Addressing barriers created by auditory environments through accommodations should improve QoL for Autistic people.

We need to combine sensory data from various sources to make sense of the world around us. This sensory data helps us understand our surroundings, influencing our experiences and interactions within our everyday environments. Recent interest in sensory‐focused approaches to supporting autistic people has fixed on auditory processing—the sense of hearing and the act of listening—and its crucial role in language, communications, and social domains, as well as non‐social autism‐specific attributes, to understand better how sensory processing might differ in autistic people. In this narrative review, we synthesize published research into auditory processing in autistic people and the relationship between auditory processing and autistic attributes in a contextually novel way. The purpose is to understand the relationship between these domains more fully, drawing on evidence gleaned from experiential perspectives through to neurological investigations. We also examine the relationship between auditory processing and diagnosable auditory conditions, such as hyperacusis, misophonia, phonophobia, and intolerance to loud sounds, as well as its relation to sleep, anxiety, and sensory overload. Through reviewing experiential, behavioral and neurological literature, we demonstrate that auditory processes interact with and shape the broader autistic profile—something not previously considered. Through a better understanding of the potential impact of auditory experiences, our review aims to inform future research on investigating the relationship between auditory processing and autistic traits through quantitative measures or using qualitative experiential inquiry to examine this relationship more holistically.

What is noise? When does a sound form part of the acoustic background and when might it come to our attention as part of the foreground? Our brain seems to filter out irrelevant sounds in a seemingly effortless process, but how this is achieved remains opaque and, to date, unparalleled by any algorithm. In this review, we discuss how noise can be both background and foreground, depending on what a listener/brain is trying to achieve. We do so by addressing questions concerning the brain’s potential bias to interpret certain sounds as part of the background, the extent to which the interpretation of sounds depends on the context in which they are heard, as well as their ethological relevance, task-dependence, and a listener’s overall mental state. We explore these questions with specific regard to the implicit, or statistical, learning of sounds and the role of feedback loops between cortical and subcortical auditory structures.

Viral vectors and lipofection‐based gene therapies have dispersion‐dependent transduction/transfection profiles that thwart precise targeting. The study describes the development of focused close‐field gene electrotransfer (GET) technology, refining spatial control of gene expression. Integration of fluidics for precise delivery of “naked” plasmid deoxyribonucleic acid (DNA) in sucrose carrier within the focused electric field enables negative biasing of near‐field conductivity (“conductivity‐clamping”–CC), increasing the efficiency of plasma membrane molecular translocation. This enables titratable gene delivery with unprecedently low charge transfer. The clinic‐ready bionics‐derived CC‐GET device achieved neurotrophin‐encoding miniplasmid DNA delivery to the cochlea to promote auditory nerve regeneration; validated in deafened guinea pig and cat models, leading to improved central auditory tuning with bionics‐based hearing. The performance of CC‐GET is evaluated in the brain, an organ problematic for pulsed electric field‐based plasmid DNA delivery, due to high required currents causing Joule‐heating and damaging electroporation. Here CC‐GET enables safe precision targeting of gene expression. In the guinea pig, reporter expression is enabled in physiologically critical brainstem regions, and in the striatum (globus pallidus region) delivery of a red‐shifted channelrhodopsin and a genetically‐encoded Ca²⁺ sensor, achieved photoactivated neuromodulation relevant to the treatment of Parkinson's Disease and other focal brain disorders.