Ear & Hearing

Cochlear implants (CIs) restore hearing by stimulating auditory neurons to encode amplitude envelopes across frequency bands, providing essential cues for speech recognition. This study investigated how stimulation pulse rate constrains temporal envelope processing and speech cue perception in ten post-lingually deaf CI users by evaluating amplitude modulation (AM) detection thresholds and consonant identification performance across pulse rates. The effects of pulse rate on temporal processing and speech perception were examined using both standard clinical multi-channel strategies and single-channel strategies designed to isolate within-channel envelope representations. Results revealed a significant decline in AM detection and consonant recognition performance at the lowest tested pulse rate of 125 pulses per second (pps), consistent with perceptual constraints on temporal processing at low carrier rates, rather than inadequate envelope sampling. At the highest pulse rate of 4000pps, a non-significant reduction in AM detection was observed which may be consistent with previously reported reductions in amplitude discrimination at high pulse rates. Consonant recognition performance remained stable across clinically relevant pulse rates (250-2000pps), though listener-specific pulse rate effects were observed. Notably, significant correlations were found between single-channel and multi-channel performance in AM detection and consonant recognition tasks. These findings support an important contribution of within-electrode temporal envelope processing to multi-channel speech perception and highlight the clinical relevance of individual variability in pulse rate effects.

Modern cochlear implants (CIs) use pulsatile stimulation to restore hearing for individuals with severe hearing loss. CIs provide robust speech recognition in quiet but poorly represent temporal fine structure (TFS), needed for challenging listening situations. Analog stimulation preserves the acoustic waveform and may better encode TFS, yet it has not been evaluated combined with modern current-focusing strategies. We compared neural responses in the inferior colliculus (IC) evoked by CI stimuli consisting of 100 pulses/s biphasic pulse trains and 100 cycles/s sinusoidal analog stimulation with monopolar, bipolar, and tripolar electrode configurations in urethane-anesthetized guinea pigs. Following cochlear implantation, multiunit activity was recorded from the tonotopic axis of the central nucleus of the IC using 16-channel silicon probes. Detection thresholds, spread of excitation, vector strength, sustained response percentage, and temporal response properties were quantified. Analog stimulation consistently evoked significantly lower activation thresholds than pulsatile stimulation while maintaining comparable or sometimes narrower spatial selectivity across stimulation modes. In contrast, analog stimulation generated lower vector strength, larger tonic response components, and a pronounced level-dependent polarity effect. At low stimulus levels, responses were dominated by the cathodic phase of the sinusoidal waveform, whereas increasing stimulus level responses were elicited by both phases, producing synchronization at twice the stimulus frequency. These findings demonstrate that stimulation waveform strongly influences temporal coding while having relatively little effect on the spatial distribution of neural activation. These results provide a physiological basis for reexamining analog stimulation as an alternative strategy for cochlear implant sound coding.

Auditory brainstem responses (ABRs) are a core part of objective functional evaluations of hearing sensitivity and subcortical auditory transmission. Manual assessments of ABR waveforms are still a primary means by which thresholds and peak amplitudes and latencies are measured, which is time-consuming and prone to user variability. Automated methods have offered promising alternatives for ABR classification, but they have sometimes been limited in accuracy or robustness. Here, we developed and tested a supervised convolutional neural network (CNN) based ABR peak classifier that works across sound levels and sound frequencies that can be run quickly on a personal computer using single or dual-channel ABR inputs. For ABR peaks I, III, IV, and V, the classifier achieved over 95% accuracy. High accuracy was maintained even after noise-exposure causing temporary or permanent threshold shifts, and over 90% of peaks were within 0.041 ms (1 sample) of the manually identified peak. Only a few hundred samples were needed to train the network, making it widely amenable to smaller data studies or where the number of subjects or sessions may be low.

Understanding speech in noisy environments relies strongly on binaural cues such as interaural time differences (ITDs) and interaural level differences (ILDs), which support spatial hearing and the segregation of competing sound sources. When these cues are degraded, listeners experience substantial difficulty in complex acoustic environments. Behavioural measures of binaural benefit, such as binaural masking level differences (BMLDs), binaural intelligibility level differences (BILDs), and spatial release from masking (SRM), are well established in normal-hearing (NH) listeners, but they require an active behavioural response. Neural speech tracking using electroencephalography (EEG) has emerged as a promising approach for quantifying neural processing of continuous speech, yet its sensitivity to spatial hearing cues remains insufficiently characterised. In this study, we investigated the neural correlates of spatial release from masking in NH listeners using EEG-based neural speech tracking. Nineteen participants listened to continuous Dutch speech stories presented with masking noise under two spatial configurations, collocated (S0N0) and spatially separated (S0N90), across multiple signal-to-noise ratios (SNRs). Neural tracking of the speech envelope was quantified using both envelope reconstruction and temporal response function (TRF) analyses. Spatial separation enhanced neural tracking of the target speech envelope, particularly at challenging SNRs where behavioural SRM was also observed. TRF analysis further revealed condition-dependent morphologies, including increased amplitudes and decreased latencies of late cortical components consistent with spatial unmasking effects. These neural differences were most pronounced at low SNRs, where spatial cues provide the greatest perceptual benefit. Together, these findings demonstrate that neural speech tracking captures cortical signatures of spatial unmasking and closely reflects behavioural improvements in speech understanding. Establishing these relationships in NH listeners supports the development of objective neural measures for evaluating binaural benefit in difficult-to-test populations.

PurposeMild therapeutic hypothermia (MTH) preserves cochlear function in animal models and is now entering early-phase human trials for hearing preservation. However, the extent to which the human cochlea can actually be cooled, and the mechanisms underlying MTH, remain unclear, in part because blood perfusion is expected to oppose localized cooling. In this study we evaluated the impact of blood flow on human cochlear temperature exposed to the MTH device using a combined experimental and computational approach. MethodsTemperature measurements were obtained from a human cadaver skull exposed to a commercial MTH device. These data were used to validate a three-dimensional bioheat transfer model incorporating realistic skull anatomy. The validated model was subsequently extended to include physiological blood perfusion in the internal carotid artery; a major heat source located near the cochlea. Finally, the in silico model was further expanded to incorporate the surrounding skin and brain tissues. ResultsIncorporating blood flow in internal carotid artery substantially altered predicted cochlear temperature distributions, highlighting the importance of localized vascular heat transport in the human cochlea during MTH. Although cochlear cooling was attenuated in the presence of perfusion, the therapeutic effects of MTH may not depend solely on the magnitude of local intracochlear temperature reduction. Additional mechanisms, such as reduced facial surface temperature, may also contribute to its efficacy. ConclusionThe validated in silico model provides a physiologically realistic framework for evaluating human cochlear thermal responses, investigating MTH mechanisms, and optimizing temperature-based strategies for hearing preservation.

Objective: To evaluate the efficacy, engagement, and usability of Tune Out, an unguided, self-paced online tinnitus management program, for reducing tinnitus severity in adults with tinnitus. Design: A two-arm, parallel-group randomised controlled trial was conducted with Australian adults reporting diagnosed or self-reported tinnitus. Participants were randomised to immediate access to Tune Out or a waitlist control group. Outcomes were assessed at baseline, 6 weeks, and 12 weeks. The primary outcome was tinnitus severity measured using the Tinnitus Functional Index (TFI). Secondary outcomes included tinnitus handicap, psychological symptoms, program engagement, self-efficacy, and usability. Results: Eighty-eight participants were randomised: 43 to the intervention group and 45 to the waitlist control group. The primary outcome analysis included 63 participants at 12 weeks. A significant Group x Time interaction was observed for TFI total score, indicating greater reductions in tinnitus severity over time in the intervention group compared with waitlist control, F(2, 102.57) = 5.95, p = .004, partial 2= .104. Significant effects were also observed for tinnitus handicap, F(2, 106.76) = 4.12, p = .019, partial 2 = .072. Effects on psychological symptoms were less consistent, although anxiety showed a significant Group x Time interaction, F(2, 116.85) = 3.63, p = .030, partial 2 = .059. At 12 weeks, 23.1% of intervention participants achieved a clinically meaningful reduction in tinnitus severity compared with 5.4% of controls. Program use was highly variable, with a median use of 1.10 hours, and 25.6% of intervention participants recording no use. Usability ratings were favourable among respondents, with a mean System Usability Scale score of 73.13. Conclusions: Tune Out demonstrated preliminary efficacy for reducing tinnitus severity and tinnitus handicap compared with waitlist control. Effects on broader psychological symptoms were less consistent. Although usability was rated positively, low and variable engagement highlights the need for strategies to support uptake and sustained use in unguided digital tinnitus interventions.

This study examined the extent to which goodness of pronunciation (GoP) scores and phonological posterior probabilities capture perceptual ratings of speech severity in individuals with motor speech disorders (MSD). Speech recordings of the word catastrophe were obtained from 489 participants, including 333 neurologically typical controls and 156 individuals with MSD. GoP scores were derived using traditional acoustic features and self-supervised speech representations, including WavLM and XLS-R, across multiple modeling approaches, while phonological posterior probabilities were extracted using Phonet. Model performance was evaluated using Kendall's rank correlations, regression, and receiver operating characteristic analyses against speech-language pathologists' perceptual ratings of sound distortion and intelligibility. Both GoP and phonological posterior probabilities were significantly associated with perceptual ratings. Self-supervised speech representations substantially outperformed traditional acoustic features, with WavLM-based GoP using k-nearest neighbors achieving the strongest performance. Across correlation, regression, and classification analyses, GoP consistently outperformed phonological posterior probabilities for both sound distortion and intelligibility. Age and gender had minimal influence on model-derived measures or their relationships with perceptual ratings. These findings demonstrate the value of self-supervised GoP as an objective measure of speech impairment while highlighting the complementary role of phonological posterior probabilities in characterizing articulatory aspects of motor speech disorders.

Objective: The COVID-19 pandemic markedly altered social activity patterns, healthcare utilization, and the epidemiology of infectious diseases. However, its long-term impact on emergency otolaryngologic conditions remains incompletely understood. This study investigated long-term trends in emergency otolaryngologic conditions before, during, and after the COVID-19 pandemic using comprehensive data from a large urban emergency clinic in Osaka, Japan. Methods: All new otolaryngologic outpatients who visited the Chuo Emergency Medical Clinic (CEMC) in Osaka City between 2019 and 2024were retrospectively analyzed. Annual trends in absolute numbers and relative proportions of emergency otolaryngologic conditions were examined by anatomical region and disease category, using 2019 as the pre-pandemic baseline. Results: A total of 99,324 new otolaryngologic outpatients were analyzed. Overall emergency visits declined sharply to approximately half of baseline in 2020, followed by a gradual but incomplete recovery toward pre-pandemic levels by 2024. Most anatomical categories declined to 45-61% of baseline in 2020 and exhibited gradual yet incomplete recovery through 2023; in stark contrast, laryngeal conditions diverged sharply, surging beyond pre-pandemic levels after 2022. Acute infectious otorhinolaryngologic diseases fell to 23-50% of baseline in 2020 and showed variable recovery (69-103%) by 2024. Notably, laryngitis exceeded the baseline, reaching 132% in 2023, whereas epiglottic edema exhibited only a transient increase approaching the baseline in 2021. Non-infectious emergency conditions generally showed only a marginal decrease in 2020 and remained relatively stable throughout the study period, except for sudden sensorineural hearing loss (SSNHL), which dropped sharply to 39% of the baseline in 2020 and remained persistently reduced through 2024. Traumatic emergencies declined variably to 53-81% of the baseline in 2020, followed by an incomplete recovery, reaching only 55-69% by 2024. Conclusion: Emergency otolaryngologic conditions demonstrated heterogeneous recovery trajectories following the COVID-19 pandemic. While most infectious and traumatic conditions gradually but incompletely normalized, laryngeal conditions showed a distinct post-pandemic surge, and SSNHL remained persistently suppressed. These findings reveal heterogeneous, condition-specific recovery trajectories that reflect both genuine shifts in community pathogen burden, true traumatic incidence, and persistent alterations in healthcare-seeking behaviors, insights essential for resource allocation during future public health emergencies.

Speech comprehension in noisy environments often requires cognitive effort, but listeners may disengage when comprehension becomes impossible. Eye movements have recently emerged as a promising new measure of listening effort, but it remains unclear whether eye movements are sensitive to the full effort profile across easy, difficult, and impossible speech comprehension. Across four experiments, participants listened to sentences at easy, difficult, and impossible levels of multi-talker background babble while pupil size and eye movements were recorded. Pupil size generally followed the expected inverted u-shaped effort profile: low for easy speech, maximal for difficult but still intelligible speech and lower again for impossible speech, although this pattern partly reflected sustained, condition-specific differences and not only sentence-evoked responses. Gaze dispersion - measuring the spread of eye movements - decreased with high temporal selectivity during difficult relative to easy and impossible speech, indicating reduced eye movements during active, effortful listening. However, gaze dispersion was also lower, but less temporally selective, during impossible compared to easy listening, especially in non-baseline-corrected analyses, suggesting that reduced eye movements do not index listening effort uniquely. Instead, eye movements appear to reflect both attentional engagement during difficult listening and disengagement or inward attention when meaningful listening is no longer possible. These findings indicate that pupil size and eye movements provide complementary indices of listening-related cognition, and highlight the integration of listening, cognition, and motor systems.

Background: Speech-in-noise (SIN) perception is a difficult everyday listening task that becomes more difficult with age. Neural tracking of target speech is associated with successful speech perception in clean and noise-degraded listening environments. How aging impacts neural tracking of speech and relates to behavioral decrements in older adults' SIN perception remains unclear. To address these questions, we measured neural speech tracking during a continuous SIN perception task in younger and older adults via multichannel EEG. Method: Participants (n=83) monitored a continuous stream of syllables (~4.5 Hz) presented in quiet and noise conditions during EEG recordings. We assessed neural phase-locking value (PLV) to the acoustic speech envelope to investigate interactions between aging, hearing loss, and stimulus noise on neural synchronization to speech. Results: Compared to younger adults, older adults demonstrated less behavioral sensitivity to noise effects than young adults and had higher overall PLV to target speech. Older adults also showed greater noise-related degradations in neural speech processing relative to younger listeners. Age remained a strong predictor of behavioral responses to speech even after controlling for hearing loss. Covarying for hearing loss removed most age-related effects on neural PLV. Conclusion: Older adults demonstrate overexaggerated neural tracking to ongoing speech presented in quiet and greater noise-related reductions in neurobehavioral speech processing than young adults. Our results support the decline-compensation hypothesis, corroborate unusually large speech envelope encoding in older listeners, and suggest more robust neural synchronization to the speech signal is not always perceptually advantageous.

Understanding brain-behavior relationships requires models capturing the distributed, interactive, and multiscale nature of neural systems. Traditional univariate approaches and single-biomarker models are inherently limited in this context, as they fail to represent dependencies across regions and the hierarchical organization of brain networks. In this study, we propose a graph-based multivariable framework for brain imaging analysis that integrates key organizational principles of brain function-including segregation, integration, modularity, and temporal dynamics-within a unified graph neural network architecture. The framework represents brain data as hierarchical graphs, where node features encode regional activation and temporal variability, and graph structure captures interactions within and between functional modules. The proposed approach is evaluated using functional near-infrared spectroscopy (fNIRS) data as a case study, where subject-specific brain graphs are constructed from task-based recordings acquired shortly after cochlear implant activation to predict speech understanding outcomes one year later. Under leave-one-subject-out validation, the model demonstrates strong predictive performance (R = 0.73, p < 0.001), outperforming previously reported single-biomarker approaches. Perturbation-based analyses further show that predictions are driven by distributed patterns of activity and interaction across regions and modalities, rather than isolated features. These results illustrate the capability of the proposed framework to capture complex brain organization and highlight its potential as a generalizable platform for multivariable analysis and prediction in neuroimaging applications beyond the specific clinical use case considered here.

Speech comprehension under adverse listening conditions benefits from visual speech, but whether visual input can be modulated to improve listening remains unclear. Here we used rapid frequency tagging, a non-invasive sensory stimulation technique, in which the visual tag at 55 Hz over the mouth region of a talking face was amplitude-modulated by the envelope of either the task-relevant or task-irrelevant speech stream. When the visual modulation followed the task-relevant speech envelope, comprehension improved relative to task-irrelevant modulation and to an unmodulated tagging control. MEG responses showed enhanced 55 Hz visual tagging, altered 40 Hz auditory tagging and a non-linear 15 Hz intermodulation. Individual comprehension gains were associated with intermodulation responses in left inferior frontal cortex, linking behavioural benefit to audiovisual interaction. These findings show that task-relevant visual stimulation can improve comprehension by strengthening audiovisual interaction, establishing amplitude-modulated frequency tagging as a tool for probing and supporting comprehension in challenging environments.

Context effects are ubiquitous across sensory systems and reflect a general encoding principle for both simple and complex stimuli. One simple context effect, contraction bias, manifests in two-interval perception tasks as a bias of the perceived magnitude of the first stimulus toward the center of the overall magnitude range. The underlying cause of contraction bias is unclear. One explanation is that a listeners magnitude estimate of the first stimulus is combined with a perceptual anchor, usually the mean stimulus magnitude, biasing it toward the anchor (sensory model). An alternative explanation is that a listeners response criterion shifts, based on the magnitude of the stimulus pair, relative to the mean magnitude of the stimuli range (decision model). Two pitch-discrimination experiments were performed to test these hypotheses in the auditory domain. The first was a forced-choice discrimination task, where listeners were asked to identify the higher or lower tone in a pair. The second was a same-different task where listeners indicated whether or not the two tones in a pair differed in frequency. Contraction bias was observed in the higher-lower discrimination task, even after extensive perceptual training with feedback. In contrast, no contraction bias was observed in the same-different task. Computational models of the sensory and decision hypotheses were fit to data from both experiments. The sensory model captured the pattern of results the higher-lower experiment but erroneously predicted a contraction bias in the same-different task. The decision model produced similar predictions to the sensory model in the higher-lower task but correctly predicted no contraction bias in the same-different task, and produced lower prediction errors and more stable parameter estimates in both paradigms. Overall, the results suggest that the underlying nature of the contraction bias may reflect decision, rather than sensory, biases based on the context.

Face-to-face communication requires listeners to attend, integrate, and weigh multiple communicative signals, including auditory speech, mouth movements, and co-speech gestures. The contribution of these signals may depend on the reliability of auditory input and the informativeness of the available signals. We utilized rapid invisible frequency tagging (RIFT) with EEG to examine how participants attend to and integrate these different signals in clear and adverse listening conditions. Participants watched videos of an actress producing clear or noise-vocoded sentences. Auditory speech was amplitude-modulated at 58Hz, while the luminance of the gesture and mouth regions was frequency-tagged at 63Hz and 65Hz. Degraded speech elicited stronger responses at the auditory tagged frequency, suggesting increased attentional gain to the auditory signal when listening was challenging. In contrast, clear speech elicited stronger responses at the gesture tagged frequency and a stronger 2Hz intermodulation response (65-63Hz), reflecting enhanced nonlinear coupling between mouth movements and gestures. Finally, in degraded speech, the informativeness of mouth movement, but not gesture, was associated with intermodulation strength, suggesting that the informativeness of mouth movements plays a greater role in multisensory interaction when listening is challenging. Our findings demonstrate that both signal reliability and informativeness shape multisensory integration during spoken language comprehension.

Point-of-care ultrasound has transformed bedside diagnostics, yet current systems remain limited by rigid form factors, bulky external electronics and the need for skilled operators. Here we report a conformable ultrasound imaging patch that integrates a 1024-channel CMOS ultrasound application-specific integrated circuit (ASIC) directly beneath a conformable piezocomposite transducer array. The 10 mm X 8 mm, 1024-element ASIC contains on-chip transmit and receive beamforming, reducing the effective off-chip channel count by 16X while preserving image fidelity. Fabricated on a flexible polyimide substrate and bonded using anisotropic conductive film, the patch operates untethered from conventional ultrasound consoles and requires only a laptop for control and data acquisition. The device supports focused, plane-wave and diverging-wave transmission with steering over {+/-}30{degrees} in azimuth and {+/-}15{degrees} in elevation, achieving peak-to-peak acoustic pressures up to 7 MPa at a 4.4-MHz center frequency (mechanical index of 1.7), within diagnostic safety limits. Phantom experiments demonstrate three-dimensional imaging with axial and lateral resolutions (in both XZ and YZ planes) of 0.5 mm and 2 mm, respectively, and accurate contrast reproduction in tissue-mimicking phantoms. Human studies further demonstrate three-dimensional (3D) visualization of the internal jugular vein and carotid artery, as well as rib-shadow-free imaging of pleural motion during respiration. This work establishes a scalable architecture for chronic, wearable ultrasound imaging and highlights the potential of CMOS-integrated, conformable ultrasound systems for continuous physiological monitoring and remote diagnostics.

Listeners discretize the speech signal by assigning sounds to phonetic categories, though there is variability in how individuals accomplish categorization. Having more consistent categorization of sounds may be advantageous for understanding speech-in-noise (SIN). Though, it is unclear how different levels of neural processing in the auditory system reflect these perceptual differences. We recorded brainstem frequency-following responses (FFRs) and cortical event-related potentials (ERPs) while listeners actively labeled vowels along an acoustic-phonetic continuum using a visual analog scale. We computed intertrial consistency of neural responses to index the stability of listeners' neural speech representations across stimulus presentations. We also assessed how faithfully midbrain and cortical responses represented stimulus acoustics using representational dissimilarity matrices (RDMs) computed across all token pairs. Neural RDMs were then compared with acoustic and phonetic category RDMs to assess whether FFRs and ERPs carried gradient vs. categorical information of the speech signal. We found greater behavioral consistency during phoneme labeling was correlated with improved SIN scores. Neurally, we found greater cortical or subcortical consistency predicted greater behavioral consistency. RDMs revealed subcortical responses retained more acoustic details, while cortical responses more closely reflected abstract phoneme categories. Our findings reveal important benefits of perceptual consistency to other domains of speech perception. We find perceptual consistency is driven by more consistent encoding of speech at either a cortical or subcortical level. More consistent sensory processing could provide a more stable readout of the speech signal to higher cortical brain areas which could confer advantages to later perceptual processes downstream.

Substantial progress has been made in recent years on understanding how the human brain parses and processes natural speech. Much of this progress has been based on modeling how brain activity relates to the different acoustic and linguistic features of speech. By fitting and testing models based on those features, one can test hypotheses about the kinds of computations and representations the brain uses to convert speech sounds into understanding. While much of this work has focused on modeling BOLD activity using functional neuroimaging or intracranially recorded electrophysiological signals, the approach has also proven useful with MEG and EEG. Indeed, noninvasive EEG has certain advantages for studying speech processing in terms of translational research and application. Research over the last decade or so has shown that EEG can be successfully modeled based on numerous acoustic, linguistic, and paralinguistic speech features. However, an important unanswered question hangs over all of this work: namely, what constitutes a good model of EEG responses to natural speech? Or, to put it another way, how much variance in EEG recorded during natural speech listening is explainable as having derived from that speech input? The present study aims to tackle this issue. We do so under the assumption that the best model for a person's EEG response to natural speech is a set of EEG responses from other people listening to the same speech. Using this assumption, we construct inter-subject models using EEG from 19 healthy adult native speakers of English who all listened to the same audiobook. The model for each subject involves predicting their EEG data using (dimensionality-reduced) EEG from different numbers of other subjects and then extrapolating to estimate the total explainable variance in the target individual's response to speech. Following this, we show that linear models (temporal response functions) based on several commonly used acoustic and linguistic speech features can predict most - but importantly not all - of the estimated total explainable variance in EEG responses across subjects.

Evaluation of the effectiveness of therapeutic interventions for dentine hypersensitivity is limited by a lack of standardisation and objectivity in measuring the associated pain. To address this, we investigated whether electroencephalography (EEG) can provide an objective, quantitative measure of the condition. Participants with and without dentine hypersensitivity underwent evaporative (air puff) and thermal (cooling probe) tooth stimulation during continuous recording of EEG activity. Sensitivity scores (Schiff Sensitivity score for air puff stimuli, and Visual Analogue Scale score (VAS) for thermal stimuli) were recorded, and participants' responses to the Dentine Hypersensitivity Experience Questionnaire (DHEQ) collected. There were strong positive correlations between the Schiff and VAS scores, and also between both sensitivity scores and the impact of dentine hypersensitivity on quality of life (DHEQ). Additionally, EEG data analysis revealed significant differences in event-related potentials (ERP) following evaporative stimulation between participants with different Schiff scores, and in cortical activity between traces where participants indicated discomfort and those where participants did not indicate discomfort during thermal stimulation trials. Topographical maps of EEG band power during thermal stimulation showed progressive cortical recruitment and focal activation emerging in the 3 seconds prior to indication of discomfort. Comparison of EEG band power between response and no response trials to thermal stimulation showed significantly higher delta frequency band power in response trials than in no-response trials. Peak-to-peak amplitude of cortical response during thermal stimulation correlated with DHEQ and VAS scores, and the probe temperature at which participants indicated discomfort. These findings suggest that components of EEG responses align with other measures of dentine sensitivity (DHEQ, Schiff and VAS scores) and can serve as objective neurophysiological markers for evaluating the severity of dentine hypersensitivity.

Skeletal muscle is a living, perfused soft tissue whose viscoelastic behavior is shaped by both voluntary contraction and hemodynamic state. However, the independent and superimposed contributions of contractile loading and blood flow restriction (BFR) have not been quantified simultaneously in real time. Twenty-six healthy adults underwent multi-frequency ultrasound time-harmonic elastography (THE, 60-80 Hz) of the vastus lateralis under six conditions: rest, 15% and 30% maximal voluntary contraction (MVC) before BFR, passive BFR after 4 min of cuff inflation, and 15% and 30% MVC shortly after cuff release. Shear wave speed (SWS), reflecting elasticity, and penetration rate (PR), reflecting inverse viscous damping, were extracted using the k-MDEV inversion algorithm. BFR significantly elevated SWS at all three contraction levels relative to the corresponding pre-BFR measurements (Holm-corrected p [&le;] 0.011; dz = 0.54-2.13). PR decreased during resting BFR (dz = 1.34, p < 0.001) and at 15% MVC after cuff release (dz = 0.94, p < 0.001), but not at 30% MVC (dz = 0.21, p = 0.294). BFR-related changes reduced the SWS-force slope by 14.5% and the PR-force slope by 40.7%. Men exhibited a greater BFR-induced increase in resting SWS than women. These findings show that THE can distinguish contractile and hemodynamic contributions to skeletal-muscle viscoelasticity and provide complementary information on elastic and dissipative tissue behavior in vivo.

Reported perceptual differences in autism may arise from reduced use of prior context to shape incoming sensory input. Speech perception provides a critical test of this account because stable perception requires listeners to integrate variable acoustic signals with contextual expectations. This study examined context-dependent modulation of speech encoding in autistic and non-autistic adults using the frequency-following response (FFR), a neurophysiological measure of phase-locked auditory encoding. Participants heard English intonational pitch contours presented in repetitive and variable contexts while EEG was recorded. Principal component analysis of FFR metrics yielded components indexing neural encoding fidelity and timing. Non-autistic participants showed enhanced encoding fidelity in more predictable contexts, whereas autistic participants showed reduced context-dependent modulation. Neural encoding timing also showed divergent context effects across groups, suggesting altered balance between feedback-based predictive mechanisms and locally driven adaptation processes. Within the autistic group, greater context-related modulation of encoding fidelity was associated with lower ADOS-2 Social Affect severity but poorer speech-in-noise perception, suggesting that the functional impact of contextual modulation depends on input reliability and task demands. These findings indicate that context-dependent modulation of speech encoding is altered in autism and may contribute to individual differences in auditory and social-communicative function.