Ear & Hearing

Introduction: Auditory brainstem response (ABR) is a standard objective method for estimating hearing threshold, especially in patients who cannot reliably participate in behavioral audiometry. However, ABR interpretation is usually performed by an expert. This study evaluated whether two general-purpose artificial intelligence (AI) multimodal large language model (LLM) chatbots, ChatGPT and Qwen, can accurately estimate ABR hearing thresholds from ABR waveform images. The accuracy was measured by comparisons with the judgements of 3 expert audiologists. Methods: A total of 500 images each containing several ABR waveforms recorded at different stimulus intensities were analyzed. Three expert audiologists established the reference auditory thresholds based on visual identification of wave V at the lowest stimulus intensity, with the most frequent judgment among the three used as the reference. Each waveform image was independently submitted to ChatGPT (version 5.1) and Qwen (version 3Max) using the same standardized prompt and without additional clinical context. Agreement with the expert thresholds was assessed as mean errors and correlations. Sensitivity and specificity for detecting hearing loss (>20 dB nHL) were also calculated. In cases where the AI and expert thresholds nominally matched, corresponding latency measures were also compared. Results: Auditory thresholds derived from both LLMs correlated strongly with expert opinion, with Pearson r = 0.954 for ChatGPT and r = 0.958 for Qwen. ChatGPT showed a mean error of +5.5 dB and Qwen showed a mean error of -2.7 dB. Exact nominal agreement with expert values was achieved in 34.6% of ChatGPT estimates and 35.6% of Qwen estimates; agreement within +/-10 dB was observed in 75.6% and 80.0% of cases, respectively. For hearing-loss classification, ChatGPT achieved 100% sensitivity but low specificity (20.4%), whereas Qwen showed a more balanced profile with 91.6% sensitivity and 67.5% specificity. Curiously, estimates of wave V latency were markedly poor for both LLMs, with systematic underestimation and weak correlations with the expert judgements. Conclusion: ChatGPT and Qwen demonstrated a moderate ability to estimate ABR thresholds from waveform images, although their performance was not good enough for independent clinical use. Both models captured general patterns of hearing loss severity, but there was systematic bias, limited specificity and sensitivity balance, and poor latency estimation. General-purpose multimodal LLMs may have potential as assistive or preliminary tools, but clinically reliable ABR interpretation will likely require specialized, domain-trained AI systems with expert oversight.

ObjectivesThe overall goal of this study was to assess tympanometric and ambient wideband acoustic immittance (WAI) tests and wideband acoustic reflex thresholds (ART) in well-baby and newborn intensive care (NICU) cohorts with three specific objectives: 1) Assess predictive accuracy for WBT and ART for conductive dysfunction in ears referring on the first or second stages of newborn hearing screening; 2) Identify inadequate tests likely due to probe blockages or leaks; and 3) Assess prediction models separately for well-baby and NICU screening outcomes. DesignProspective, observational study of full-term (n=514) and premature newborns (n=239) recruited from well-baby and NICU nursery birth hospital newborn hearing screening program. Wideband tympanometry, ambient absorbance, and acoustic reflexes were tested after Stage 1 transient otoacoustic emissions (TEOAE) screening. The reference standard for Pass or Refer groups was initially defined on the stage 1 TEOAE test result. Pass or Refer groups were then reassigned based on the stage 2 screening ABR for those who referred at Stage 1, and all NICU infants. Multivariate models were developed using reflectance and admittance variables to predict conductive dysfunction relative to the screening reference standard in a randomized sub-group of subjects at Stage 1 and Stage 2 screening. Classification accuracy was evaluated on a second, independent sub-group. Individual tests were classified as having inadequate probe fits if they had excessively low values of sound pressure level or susceptance (leak) or absorbance (blockage). ResultsDifferences in ambient absorbance for Pass v. Refer screening groups revealed the greatest differences and effect sizes occurring in frequency bins between 1.4-2 kHz. Screening failure at both Stage 1 and 2 was most accurately predicted by models using ambient absorbance and power level variables at frequencies between 1-2.8 kHz, including ARTs. Tympanometric admittance variables at the positive-pressure tail for frequencies between 1-2.8 kHz in combination with the ART were more accurate predictors than those at peak pressure or the negative-pressure tail. Multivariate models generalized well to an independent group of infants at both Stage 1 and 2 for both the ambient and tympanometric models. Ambient tests revealed more inadequate tests than tympanometric tests, primarily due to blocked probe tips. Exclusion of ears to detect probe leaks or blockages slightly improved the ambient prediction models, but did not affect tympanometric models. ConclusionWideband acoustic reflex tests improved all models for ambient and tympanometric absorbance. Multivariate prediction models developed for WAI tests were repeatable in an independent group of well and NICU infants, suggesting that the results are generalizable to these populations. Detection of probe blockage or leaks slightly improved prediction for ambient measures. Pressurized tests have the advantage of ensuring probe seals due to the need for a hermetic seal, thus are useful to ensure adequate probe insertion.

BackgroundAuditory steady-state responses (ASSRs) provide an objective method for estimating hearing thresholds in individuals unable to provide behavioural responses. Bone conduction (BC) testing is required to differentiate conductive from sensorineural hearing loss. Accurate BC ASSR threshold estimation relies on "correction" factors, which are not yet well established. This meta-analysis evaluated the reliability of BC ASSR thresholds to estimate hearing thresholds at 500, 1000, 2000 and 4000 Hz. MethodsA systematic search of PubMed, the Cochrane Library, and Embase was conducted to identify studies involving normal-hearing (NH) and hearing-impaired (HI) participants of all ages. Outcomes were (1) the difference between ASSR behavioural and ASSR thresholds, and (2) ASSR thresholds. The risk of bias was evaluated using the Newcastle-Ottawa Scale. The mean and 95% confidence intervals (CI) were calculated for the thresholds at the four frequencies. The certainty of the evidence was assessed using GRADE approach. ResultsOf records identified, 11 records met the inclusion criteria, yielding a total of 27 studies. Sample sizes ranged from 60 to 249 participants across frequencies and age groups. The quality of records ranged from low to high. Data were synthesised using random-effects models due to heterogeneity. In NH adults, the mean differences ({+/-}95% CI) between BC ASSR thresholds and behavioural thresholds were 17.0 ({+/-}4.8), 15.5 ({+/-}6.0), 13.4 ({+/-}3.3), and 12.1 ({+/-}4.1) dB at 500, 1000, 2000, and 4000 Hz, respectively. In NH infants, mean ({+/-}95% CI) BC ASSR thresholds were 17.2 ({+/-}2.2), 10.5 ({+/-}3.6), 26.4 ({+/-}2.7), and 19.9 ({+/-}4.0) dB HL at the same frequencies. The certainty of the evidence was very low. ConclusionsBC ASSR can be a reliable method for estimating BC thresholds. However, age and frequency significantly impact BC ASSR thresholds, highlighting the need to develop of "correction" factors to accurately predict BC behavioural thresholds. RegistrationPROSPERO CRD42023422150.

Background and ObjectivesRecurrent acute otitis media (rAOM; defined as [≥]3 AOM episodes in 6 months or [≥]4 episodes in 12 months) affects 10-15% of children in the United States and is a leading cause of healthcare utilization and antibiotic prescriptions. Prospective identification of children at risk of rAOM could help target interventions and identify new risk factors to guide preventive approaches. We therefore sought to develop predictive models to identify children at risk of rAOM using electronic health records (EHR) data. MethodsWe extracted retrospective EHR data for children who were born at Duke University Health System (DUHS) hospitals between January 1, 2014, and June 30, 2022, and who had at least one AOM episode during the study period. We used LASSO to build predictive models for development of rAOM at each episode and identified factors associated with rAOM. ResultsWe identified 6,566 children who met the study criteria, including 1,634 (24.8%) who met criteria for rAOM. A model using only data available at the first AOM episode had an area under the curve (AUC) of 0.75 (0.73, 0.77) and an Area Under the Precision Recall Curve (AUPRC) of 0.41 (95% CI 0.37, 0.46), indicating moderate discriminative ability. At the time of the first AOM episode, features associated with subsequent rAOM development included age, number of prior antibiotic prescriptions, and diagnosis of gastroesophageal reflux disease (GERD). Further, children who developed rAOM were more likely to experience treatment failure than children who did not meet rAOM criteria across all episodes. ConclusionsOur findings indicate that clinical exposures and patient characteristics documented in the EHR distinguish children who are at risk of developing rAOM. Such models could be deployed within EHR systems to identify children who would benefit from early evaluation by an otolaryngologist and audiologist.

Conductive hearing loss (CHL) with a normal otoscopic exam can be difficult to diagnose because routine clinical measures such as audiometric air-bone gaps (ABGs) can identify a conductive component but often cannot distinguish among specific underlying mechanical pathologies (e.g., stapes fixation versus superior canal dehiscence, which may produce similar audiograms). Wideband tympanometry (WBT) is a fast, noninvasive test that can provide additional mechanical information across a broad range of frequencies (200 Hz to 8 kHz). However, WBT metrics are influenced by variations in ear canal geometry and probe placement and can be challenging to interpret clinically. In this study, we extend prior WBT absorbance-based classification work by estimating the middle ear input impedance at the tympanic membrane (ZME), a WBT-derived metric intended to reduce ear canal effects. To estimate ZME, we fit an analog circuit model of the ear canal, middle ear, and inner ear to raw WBT data collected at tympanometric peak pressure (TPP). Data from 27 normal ears, 32 ears with superior canal dehiscence, and 38 ears with stapes fixation were analyzed. A multinomial logistic regression classifier was trained using principal component analysis (retaining 90% variance) and stratified 5-fold cross-validation with regularization. We compared feature sets based on ABGs alone, ABGs combined with absorbance, and ABGs combined with the magnitude of ZME. The combination of ABGs and the magnitude of ZME produced the best performance, achieving an overall accuracy of 85.6% compared to 80.4% for ABGs alone and 78.4% for ABGs combined with absorbance. These results suggest that incorporating model-derived middle ear impedance features with standard audiometric measures (ABGs) can improve automated pathology classification for stapes fixation and superior canal dehiscence.

Objectives: Patients with Cystic fibrosis (CF) often receive aminoglycosides (AGs) to manage recurrent pulmonary infections, placing them at risk for ototoxicity. Chronic AG use can lead to complex cochlear damage affecting inner and outer hair cells, the stria vascularis, and spiral ganglion neurons. The greatest damage is typically in the basal cochlear region, which encodes high-frequency hearing, with additional involvement of more apical regions. While extended-high-frequency (EHF) hearing loss (EHFHL; 9-16 kHz) is often the earliest sign of AG ototoxicity, speech in noise (SiN) effects are rarely studied. Our overall hypothesis is that SiN perception difficulties in individuals with CF, treated with AGs, are related to combined cochlear and neural damage, primarily in the EHF range but also in the standard frequency (SF; 0.25-8 kHz) range. Three mechanisms that contribute to SiN perception were evaluated in children and young adults: 1) a primary effect of reduced EHF sensitivity, measured by pure-tone audiometry (PTA) and transient-evoked otoacoustic emissions (TEOAEs); 2) a secondary effect of subclinical damage in the SF range, measured by PTA and TEOAEs; and 3) additional neural effects, measured by middle ear muscle reflex (MEMR) threshold (afferent) and growth functions (efferent).Design:A total of 185 participants were enrolled; 101 individuals with CF treated with intravenous AGs and 84 age and sex-matched Controls without hearing concerns or CF. Assessments included EHF and SF PTA; the Bamford-Kowal-Bench (BKB)-SIN test for SiN perception; double-evoked TEOAEs with chirp stimuli from 0.71 to 14.7 kHz; and ipsilateral and contralateral wideband MEMR thresholds and growth functions using broadband stimuli. Results: Reduced sensitivity at EHFs (PTA, TEOAEs) was not associated with impaired SiN perception in the CF group. SF hearing, regardless of EHF status, was the primary predictor of SiN performance in the CF group. Increased MEMR growth was also significantly associated with poorer SiN in the CF group. Conclusions: In CF, impaired SiN perception was primarily predicted by SF hearing impairment, with additional involvement of the efferent auditory pathway through increased MEMR growth. These results build on prior evidence for efferent neural effects due to ototoxic exposures, supporting both sensory (afferent) and neural (efferent) mechanisms that contribute to listening difficulties in CF. Thus, preventive and intervention strategies should consider these combined mechanisms in people with AG ototoxicity to address their SiN problems.

PurposeReal-world evidence (RWE) is of practical significance as it enables the evaluation of whether findings observed in rigorously controlled clinical trial settings are generalizable to routine clinical practice. While Lenire, a bimodal neuromodulation tinnitus treatment device, has demonstrated efficacy and safety within controlled trials, further RWE from clinics is needed to reinforce these results. This is the first real-world study to assess the therapeutic effects of Lenire on tinnitus using the Tinnitus Functional Index (TFI), a multidimensional instrument designed to capture tinnitus severity and treatment responsiveness. The study correlates findings with the Tinnitus Handicap Inventory (THI), a well-established tool that assesses the perceived functional, emotional, and catastrophic impact of tinnitus that was used in previous clinical trials and real-world studies. The use of an alternative validated outcome measure in a real-world study may add more feasible, relevant and patient-centered research findings to the body of evidence for Lenire, while maintaining scientific credibility. MethodsA single-site, single-arm retrospective study examining patients fitted with the Lenire device was conducted. Ninety-seven patients with moderate or greater tinnitus severity used the Lenire device for 12 weeks, for up to 60 minutes a day. The primary outcome was change in tinnitus severity, assessed using the TFI at 6-week (FU1) and 12-week (FU2) follow-ups. The THI was included as a secondary outcome measure. Responder rates and mean score changes between initial assessment and FU1 and FU2 were compared using Z-tests for proportions and t-tests, respectively. Pearsons correlations were used to examine the relationship between the TFI and THI change scores. ResultsAfter just 12 weeks of treatment, 73.4% [95% CI: 62.6%, 84.3%] of patients achieved a clinically significant improvement, defined as a reduction of at least 13 points on the TFI. This improvement was strongly supported by results from the THI, where 84.1% [95% CI: 75.1%, 93.2%] of patients met the minimum clinically important difference of 7 points. Mean score reductions were-25.9 (2.4, SEM) for the TFI and - 28.0 (2.4, SEM) for the THI. Change scores from initial assessment to FU2 on the TFI and THI were highly correlated (r = 0.74, p < 0.001), indicating strong agreement between the two measures in capturing treatment related improvements. All eight TFI subdomains showed reductions ranging from 18.5 to 31.4 points at FU2. ConclusionsThis retrospective study demonstrates that 12 weeks of treatment with the Lenire device resulted in clinically meaningful improvements in tinnitus severity on the TFI which was strongly supported by the THI. The high correlation between TFI and THI change scores indicates strong correlation between the two questionnaires in capturing treatment effects. Furthermore, all eight TFI subdomains showed notable reductions, underscoring the multidimensional impact of the treatment. These findings support the clinical utility of both the TFI and THI as complementary tools for evaluating treatment outcomes and guiding tinnitus management in routine practice.

ObjectiveThe objective of this study is to assess the quality, empathy, and readability of large language model (LLM) responses regarding otologic questions from patients as they compare to verified physician responses in other patient-driven forums. This study aims to predict the potential utility of LLMs in patient-centered communication. Study DesignComparative study SettingsInternet MethodsA sample of 49 otology-related questions posted on Reddit r/AskDocs1 between January 2020 and June 2025 were selected using search terms including "hearing loss," "ear infection," "tinnitus," "ear pain," and "vertigo." Posts were retrieved using Reddits "Top" filter. Each question was answered by a verified doctor on Reddit and three AI LLMs (ChatGPT-4o, ClaudeAI, Google Gemini). Responses were scored by five evaluators. ResultsCommon otologic concerns posed in patient questions were otalgia (38.7%), vertigo (28.6%), tinnitus (24.5%), hearing loss (22.4%), and aural fullness (20.4%). LLM responses were longer than physician responses (mean 145 vs 67 words; p < .05) and rated higher in quality (10.95 vs 9.58), empathy (7.26 vs 5.18), and readability (4.00 vs 3.73); (all p < .05). Evaluators correctly identified AI versus physician responses in 89.4% of cases with higher sensitivity for detecting physician responses (93.5%). By Flesch-Kincaid grade level, ChatGPT produced the most readable content (mean 7.25), while ClaudeAI responses were more complex (11.86; p < .05). ConclusionLLM responses received higher ratings in quality, empathy, and readability than those of physicians in response to a variety of otologic concerns. When appropriately implemented, such systems may enhance access to understandable otologic information and complement clinician-delivered care.

Rise time (RT) is considered to be one of the most significant acoustical characteristics of auditory speech stimuli. A substantial amount of data has been accumulated on the neurophysiological mechanisms of RT processing under different conditions and in different groups of people, but these data have not been systematised. This review focuses on studies that have investigated electroencephalographic (EEG) markers of RT sensitivity. The present literature search was conducted according to the PRISMA statement in PubMed, Web of Science and APA PsychInfo databases. The resultant review comprised 37 studies that considered diverse aspects of RT processing. The review describes the main stimulation parameters affecting electrophysiological markers of RT processing reflected in different components of event-related potentials, brainstem responses and cortical rhythmic activity. The main finding of this review is that the rise time prolongation leads to a decrease in the amplitude of the main ERP components and an increase in their latencies. However, the sensitivity of the EEG markers varied with the earliest components tracking the subtle difference (few tens of microseconds), while the later components coding the larger one (up to 500 ms). Nevertheless, the observed effects may vary and depend on some aspects of the experimental paradigm, age of participants and speech-related problems. Future research may benefit by addressing understudied clinical groups and ERP components such as P1 and N2, dominated in children.

Cochlear implant (CI) users typically experience difficulties perceiving musical harmony due to a restricted spectro-temporal resolution at the electrode-nerve interface, resulting in limited pitch perception. We investigated how stimulus parameters affect discrimination of complex-tone triads (three-voice chords), aiming to identify conditions that maximize perceptual sensitivity. Six post-lingually deafened CI listeners completed a same/different task with harmonic complex tones, while spectral complexity, voice(s) containing a pitch change, and temporal synchrony (simultaneous vs. sequential triad presentation) were manipulated. CI listeners discriminated harmonically relevant one-semitone pitch changes within triads when spectral complexity was reduced to three or five components per voice, with significantly better performance for three-component compared to nine-component tones. Sensitivity was observed for pitch changes in the high voice or in both high and low voices, but not for changes in only the low voice. Single-voice sensitivity predicted simultaneous-triad sensitivity when controlling for spectral complexity and voice with pitch change. Contrary to expectations, sequential triad presentation did not improve discrimination. An analysis of processor pulse patterns suggests that difference-frequency cues encoded in the temporal envelope rather than place-of-excitation cues underlie perceptual triad sensitivity. These findings support reducing spectral complexity to enhance chord discrimination for CI users based on temporal cues.

This study assessed neural responses to continuous speech to classify listening state, cognitive load, and selective auditory attention in complex acoustic environments. EEG was recorded while participants listened to concurrent male and female talkers under two conditions: active listening, where attention was directed to one of two competing speakers (target vs. masker), or passive listening, where attention was diverted to a visual task. Cognitive load was varied by manipulating target-to-masker (TMR) ratio (TMR: +7 dB, -7 dB), with lower TMR representing more demanding listening conditions. Spectral EEG features across frequency bands were ranked with univariate statistics and used to classify listening state (active vs passive) and cognitive load (low vs. high TMR). Auditory attention decoding (AAD) was performed using linear stimulus reconstruction to identify the target talker during active listening. Classification of listening state achieved 90.3% accuracy, and AAD reached 84.4% accuracy, demonstrating robust tracking of attentional engagement. In contrast, classification of cognitive load was near chance, suggesting that more extreme acoustic manipulations may be required to elicit distinct neural signatures. Comparable performance using a reduced set of electrodes near the ear indicates the potential for integration with wearable hearing devices. Overall, these results demonstrate that EEG can distinguish attentional states and selectively track target speech in realistic auditory scenarios. The findings provide a foundation for future applications in monitoring listening behavior, supporting auditory processing, and improving brain-controlled hearing aids in complex acoustic environments. HighlightsO_LIListening state (active vs. passive) can be classified from EEG spectral features. C_LIO_LIAttended speech can be decoded by reconstructing speech envelopes from EEG. C_LIO_LIComparable accuracy is achieved using only electrodes placed around the ears. C_LIO_LIEEG can monitor listening state and track auditory attention in two-speaker settings. C_LI Graphical AbstractEEG signals were recorded while participants listened to two concurrent speech streams, either by actively attending to one speaker or by focusing on an unrelated visual task. Spectral features of the EEG were used to classify listening state (active vs. passive) and cognitive load (low vs. high TMR). Auditory attention decoding (AAD) was performed by reconstructing the speech envelope from the EEG time signal. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/711289v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1079628org.highwire.dtl.DTLVardef@1135404org.highwire.dtl.DTLVardef@1f0d950org.highwire.dtl.DTLVardef@14b4c9a_HPS_FORMAT_FIGEXP M_FIG C_FIG Classification of listening state (active vs. passive): 90.3% accuracy. EEG difference between active and passive listening. Left, power spectrum, right, topographic map (alpha band 8-12 Hz). Classification of cognitive load (low vs high TMR): near chance level. EEG difference between low and high TMR. Left, power spectrum, right, topographic map (alpha band 8-12 Hz). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/711289v1_ufig2.gif" ALT="Figure 2"> View larger version (34K): org.highwire.dtl.DTLVardef@9229b1org.highwire.dtl.DTLVardef@1ef394corg.highwire.dtl.DTLVardef@9adecforg.highwire.dtl.DTLVardef@199f8c2_HPS_FORMAT_FIGEXP M_FIG C_FIG AAD achieved 84.4% accuracy, indicating robust decoding of the attended speaker during active listening, while performance dropped to near chance during passive listening.

BackgroundSpeech cortical mapping (SCM) conducted with widely available functional MRI (fMRI) can yield divergent results compared to the more commonly used navigated TMS (nTMS). The impact of specific fMRI task paradigms and preprocessing choices on reaching similarity with nTMS has not been explored before. ObjectiveTo test how the fMRI experimental task and spatial smoothing of the data compare with nTMS-based results, to subsequently increase the reliability of object naming fMRI for SCM. MethodsThirteen healthy, right-handed Finnish speakers underwent an nTMS-based SCM experiment in which the left hemisphere was stimulated while the subjects overtly named common visually presented stimuli. Standard as well as magnetoencephalography-informed picture-to-TMS intervals were applied. The same participants completed fMRI with overt naming, silent naming, and observation tasks on the same stimuli, analyzed with 0-, 3-, and 6-mm spatial smoothing. nTMS-based error and non-error sites were converted to volumetric density maps, and error-specific maps were derived by subtracting non-error from error density. Spatial similarity between binarized fMRI maps and nTMS maps was quantified using Jaccard index. Within-session fMRI reliability was estimated with voxel- and subjectwise concordance correlation coefficients across two separate runs conducted on the same day. ResultsSimilarity between fMRI and nTMS maps was overall low but depended significantly on data smoothing. Within subjects, mean error-specific Jaccard index was 0.036, with most individuals showing maximal similarity at 6 mm of smoothing. The fMRI task resulting in highest similarity with the nTMS map varied across participants, but at the group level, silent naming with 6-mm smoothing yielded the best correspondence. In general, within-session fMRI reliability increased with greater smoothing. ConclusionThe amount of applied fMRI data smoothing shapes the agreement of fMRI and nTMS maps during SCM. Silent naming fMRI combined with 6-mm data smoothing yielded the highest overlap with nTMS maps, yet the effect of the experimental task was statistically non-significant and the absolute similarity of the maps remained low. These results underline the different views to brain functions provided by direct perturbation of neural functions vs. blood-oxygenation based fMRI, and offer practical guidance when combining fMRI with nTMS in noninvasive speech cortical mapping. HighlightsO_LICorrespondence of fMRI and TMS speech cortical mapping results varied across individuals C_LIO_LIConcordance between the methods was generally low and depended on the fMRI data smoothing C_LIO_LISilent naming task in fMRI, combined with 6-mm data smoothing, yielded highest similarity to nTMS C_LIO_LIWithin-session fMRI reliability increased with greater smoothing C_LI

Prolonged exposure to loud and moderate noise impairs hearing; the lower the noise level, the lower risk of hearing loss is. To date, little is known about how low the noise level can be safe to hearing. This study investigated the risk of exposure to tone at typical conversational levels by measuring auditory brainstem response (ABR). We show that exposing C57 mice to continuous pure tone at 65 dB SPL for 1 hour (TE65) leads to an increase in ABR threshold that is specific to the exposure frequency. Tone exposure also increased the latencies and decreased the amplitude in Waves I and II but not in Waves III and V. Significantly, the changes in amplitude and latency were highly correlated in Wave I and such correlation gradually degraded from Wave I through to Wave V. Our findings suggest that exposure to low level sound can impair hearing and alter the auditory information process in the brain if it is persistent and presented over a sufficient period of time. Significant StatementOur findings established the risk of hearing impairment following the exposure to continuous tone at normal or conversational voice levels. This finding challenges current public health guidelines for hearing protection. Although further clarification is required, our studies prompt that the regular use of ABR testing is a potential protocol for diagnosing hearing impairment in patients experiencing hidden hearing loss (HHL).

This study provides the first neurophysiological evidence of how cochlear implant (CI) input affects predictive processing during audiovisual language comprehension in deaf individuals. Using EEG, we compared 18 CI users with 18 normal-hearing (NH) controls during sentence comprehension where final word predictability was determined by high or low semantic constraint (HC vs. LC) of the preceding sentence frame. Between sentence frame and final word, a 800 ms silent gap was introduced. Mouth visibility was manipulated during sentence frames (visible or digitally occluded; V+ vs. V-), while the final words were always presented with the mouth visible. In NH participants, lower-beta power (12-15 Hz) in left frontal and central sensors decreased for HC vs. LC contexts during the pre-target silent gap, but only when the mouths was visible, suggesting active prediction generation. In CI users, this lower beta power decrease was absent. After final word presentation, both groups showed N400 predictability effects, indicating preserved prediction evaluation. However, CI users exhibited extended N400 effects in the V+ condition, suggesting additional processing demands. Across all participants, pre-target beta modulations correlated with language production abilities, supporting prediction-by-production frameworks. Within CI users, poorer audiometric thresholds correlated with larger N400 constraint effects, possibly indicating greater reliance on contextual prediction to compensate for degraded sensory input. These findings demonstrate that CI-mediated perception alters the neural mechanisms of prediction generation. The link between production skills and predictive mechanisms suggests that strengthening expressive language abilities may enhance predictive processing in CI users.

Functional near infrared spectroscopy (fNIRS) is increasingly used in hearing and communication research, with advantages such as robustness to movement artifacts, improved spatial resolution, and flexibility of contexts in which it can be applied. At the same time, the field is progressively moving towards more continuous, naturalistic listening paradigms resulting in the widespread adoption of speech tracking analyses such as temporal response functions (TRFs) in electroencephalography (EEG) and magnetoencephalography (MEG) studies. However, it remains unclear whether these analyses can be applied to slower haemodynamic signals measured by fNIRS. In the present study, we investigated whether a TRF framework can similarly be applied to fNIRS data recorded during continuous speech perception. Eight participants listened to speech simultaneously while fNIRS signals were acquired in a hyperscanning setup. Speech features were regressed onto the haemodynamic responses to test the feasibility and interpretability of fNIRS-based TRFs. Prediction correlations between observed and modelled fNIRS signals across speech features were higher than those typically reported for EEG- and comparable to those reported for MEG-TRF studies. Moreover, these correlations did not overlap with a null distribution generated from triallJmismatched fNIRS data, confirming statistical significance and were slightly greater than those obtained from a conventional GLM approach. Our findings support that TRF estimation method can yield meaningful and statistically significant responses from fNIRS data. HighlightsO_LITRF modelling can be meaningfully applied to fNIRS data acquired during speech listening tasks. C_LIO_LIPrediction correlations between actual and modelled fNIRS signals were above chance level, with values comparable to previous EEG/MEG studies. C_LIO_LITRFs explained more fNIRS variance than a conventional GLM approach. C_LI

ObjectiveTo test the effect of Isoflurane on synaptic transmission of cortico-cortical and thalamocortical projections to the auditory cortex, and investigate how it modulates cortical sensory information processing to produce unconsciousness. MethodsUsing murine auditory thalamocortical brain slices, afferent pathways from the medial geniculate body (MGB) and layer 1 of the proximal cortex were stimulated to evoke excitatory postsynaptic potentials (eEPSPs) in cortical neurons. Whole-cell recordings were made from pyramidal and fast-spiking neurons in layer 2/3 and layer 5. eEPSPs were evaluated along with intrinsic membrane properties in response to stimulation of both pathways with and without isoflurane. ResultsIsoflurane administration resulted in significant eEPSP amplitude reduction following stimulation of both thalamic and cortical pathways, in layer 2/3 (p=0.015, p<0.001) and layer 5 (p<0.001, p<0.001) pyramidal neurons; while it only significantly reduced eEPSP amplitude in fast-spiking interneurons with cortical stimulation (p<0.001). Overall, isoflurane preferentially suppressed synaptic responses to cortico-cortical stimulation compared to thalamocortical (p=0.0002). Under isoflurane, cortico-cortical compared to thalamocortical stimulation evoked eEPSPs with reduced 10-90% rise time in both layer 2/3 and 5 pyramidal neurons, and shorter latency layer 5 neurons. Paired pulse ratio was not changed by isoflurane application, although an interesting loss of depression trend appear in layer 5 pyramidal neurons stimulated by cortical activation. Additional intrinsic neuronal measurements revealed that isoflurane reduced spike threshold significantly in both layer 2/3 and layer 5 neurons, reduced spike latency in layer 2/3 neurons, and input resistance in layer 5 neurons. However, these intrinsic neuronal changes were not seen in fast-spiking interneurons. All isoflurane induced changes were reversible during wash out. ConclusionsApplication of 1% isoflurane to brain slices significantly reduced the amplitudes of eEPSPs and modulated intrinsic neuronal properties. The effects on eEPSP amplitude were greater for cortical stimulation compared to thalamic stimulation. Isoflurane modulated intrinsic neuronal firing properties in pyramidal neurons, but not in fast-spiking interneurons.

The neural response of the brainstem to brief sounds, known as the auditory brainstem response (ABR), is widely employed in the laboratory and the clinic to diagnose hearing loss. In contrast to behavioral methods that assess hearing using responses to sounds on a trial-by-trial basis, current ABR approaches are limited to analyzing the average ABR over hundreds of trials. Historically, trial-by-trial ABR analysis has not been possible owing to each trials small signal-to-noise ratio. Here we overcome this limitation and show how to classify individual ABR trials as detected or undetected. We use the distribution of single-trial ABRs to assess supra-threshold hearing and to define psychophysics-like thresholds, which we call auditory brainstem detection (ABD) thresholds. ABD thresholds decrease as more of the ABR epoch is taken into account, whereas traditional ABR thresholds do not change. Above the ABD thresholds and below 90 dB SPL, signal detection is significantly improved by utilizing more of the ABR epoch. Our method also allows us to rank the supra-threshold hearing ability of individual subjects. Despite having normal ABR thresholds, some subjects appear to have supra-threshold hearing deficits. The trial-by-trial method demonstrates that signal detection by the ensemble of auditory neurons in the brainstem is intrinsically stochastic not only at low stimulus levels, but also at levels up to 100 dB SPL. Significance StatementNeural responses to sound can be measured by electrodes placed on a subjects head and are commonly used in the laboratory and the clinic to assess hearing. Although the auditory system must distinguish each sound stimulus from intrinsic noise, current methods for ana-lyzing the response of the brainstem to sound only utilize the average response to hundreds of stimuli. Here we overcome this constraint by showing how to classify an individual sound stimulus as detected or undetected based on each auditory brainstem response. This ap-proach can assess hearing at all stimulus levels, indicates that subjects with normal hearing thresholds can exhibit supra-threshold hearing loss, and potentially extends the types of hearing deficits that can be diagnosed using auditory evoked potentials.

Speech perception difficulties in noise are common among older adults and individuals with hearing impairment, even when audiometric thresholds appear normal. We examined how aging, cochlear synaptopathy (CS), and outer hair cell (OHC) damage affect speech encoding and phoneme discrimination. Envelope-following responses (EFRs) to rectangular amplitude-modulated (RAM) tones and speech-like phoneme pairs were recorded in quiet using EEG, and behavioral discrimination was assessed in quiet, ipsilateral, and contralateral noise. Stimuli were designed to target temporal envelope (TENV) or temporal fine structure (TFS) encoding. Results showed that RAM-EFR amplitudes decreased gradually with age, consistent with emerging CS, while magnitudes of high-frequency TENV-based EFRs in quiet were most reduced in older hearing-impaired listeners with combined CS and OHC damage. In contrast, EFRs targeting low-frequency TENV encoding in quiet remained preserved. Behaviorally, phoneme discrimination of TFS contrasts worsened with OHC loss and age in quiet and contralateral noise, respectively, while there was no significant effect of age on the discrimination of TENV contrasts. Considering that high-frequency contrasts are discriminated via place-based spectral cues, low-frequency contrasts rely on TFS, and the EFR reflects primarily TENV, this framework explains why EFRs decline for high-frequency cues without perceptual loss, while EFRs remain stable for low-frequency cues even as TFS-based discrimination deteriorates. These findings highlight the need for further investigation into how neural coding deficits relate to perceptual outcomes. Combining electro-physiological and behavioral measures might provide a sensitive framework for detecting subclinical auditory deficits to earlier diagnose age-related and hidden hearing loss. HighlightsO_LISpeech-evoked EEG shows OHC loss-related decline of high-CF enve- lope encoding. C_LIO_LISpeech-evoked EEG shows low-CF envelope encoding stays intact with age. C_LIO_LIFine-structure contrast discrimination worsens with OHC loss in quiet. C_LIO_LIFine-structure contrast discrimination worsens with age in contralateral noise. C_LIO_LIHigh-frequency place-based spectral cues discrimination remains robust with age. C_LIO_LIPeripheral coding strength is not directly reflected at behavioral level. C_LI

In humans, the first year of life is characterized by rapid developmental changes, including substantial brain maturation. As a result, neural responses to auditory stimuli undergo marked changes during this period. In this study, we followed 69 infants across their first year of life and recorded high-density electroencephalography (hdEEG) at 2 weeks, 6 months, and 12 months postpartum. Infants were presented with pure beep tones to examine the development of neural responses to auditory stimulation. We analysed event-related potentials (ERPs), inter-trial phase coherence (ITPC), and time-frequency (TF) responses to the beep tones and controlled for arousal state during stimulus presentation. We found that with increasing age, neural responses became more pronounced and showed reduced trial-to-trial variability. Phase synchronization increased from 2 weeks to later developmental stages in a broad low-frequency range (0 to 11 Hz), indicating improved temporal alignment of brain responses over time. However, phase synchronization decreased from 6 to 12 months, suggesting a developmental transition towards more differentiated brain activity. Taken together, these findings demonstrate that auditory maturation during the first year of life follows a non-linear trajectory driven by dynamic changes in neural synchronization, reflecting the progressive refinement of functional neural circuits. Our results thus provide a critical benchmark for understanding the neural dynamics underlying sensory development during this period. Impact StatementLongitudinal high-density EEG recordings reveal that neural responses to auditory stimuli undergo non-linear developmental changes during the first year of life, driven by dynamic shifts in neural synchronization that reflect progressive refinement of auditory neural processing.

Comprehending how forces are applied to an object during manipulation can help provide important insights into the quality of behavior in daily tasks. We have developed the Bead Maze Hand Function test to objectively measure the quality of hand function in children. This test aims to measure how well an individual performs the activity by integrating measures of time and force control. The main objective of this study was to examine associations between a common clinical measure, the Box and Block Score (BBS), and variables on the Bead Maze Hand Function test that were either time-based or force-based. The sample was composed of neurotypical developing adolescent participants (N=23). We found that the time (duration) on the double curve wire (most complex) was the best predictor of BBT. Furthermore, we found that force-based variables were weak predictors of the clinical, time-based BBS. These findings support the integration of time and force-based metrics to holistically quantify the quality of motor behavior. Linking these metrics into a unified score may serve as a better way to analyze adolescent motor behavior and predict future motor or neurodegenerative conditions.