OBJECTIVE To validate measurement of predicted earmold wideband real-ear-to-coupler difference (wRECD) using an integrated pressure level (IPL) calibrated transducer and the incorporation of an acoustically measured tubing length correction. DESIGN Unilateral earmold SPL wRECD using varied hearing aid tubing length and the proposed predicted earmold IPL wRECD measurement procedure were completed on all participants and compared. STUDY SAMPLE 22 normal hearing adults with normal middle ear status were recruited. RESULTS There were no clinically significant differences between probe-microphone and predicted earmold IPL wRECD measurements between 500 and 2500 Hz. Above 5000 Hz, the predicted earmold IPL wRECD exceeded earmold SPL wRECDs due to lack of standing wave interference. Test-retest reliability of IPL wRECD measurement exceeded the reliability of earmold SPL wRECD measurement across all assessed frequencies, with the greatest improvements in the high frequencies. The acoustically measured tubing length correction largely accounted for acoustic effects of the participant's earmold. CONCLUSIONS IPL-based measurements provide a promising alternative to probe-microphone earmold wRECD procedures. Predicted earmold IPL wRECD is measured without probe-microphone placement, agrees well with earmold SPL wRECDs and is expected to extend the valid bandwidth of wRECD measurement.

Introduction Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder. Objectives The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels. Methods The study retrospectively collected data from 134 children referred for ADP assessment from 2015 to 2021. Labels were provided by expert audiologists for training ML models and derived features from clinical assessments. Two ensemble learning techniques, Random Forest (RF) and Xgboost, were employed, and Shapley Additive Explanations (SHAP) were used to understand the contribution of each derived feature on the model's prediction. Results The RF model was found to have higher accuracy (90%) than the Xgboost model for this dataset. The study found that features derived from behavioral tests performed better compared to physiological test features, as shown by the SHAP. Conclusion The study aimed to use machine learning (ML) algorithms to reduce subjectivity in audiological assessments used to diagnose APD in children and identify sub-groups in the clinical population for selective interventions. Significance The study suggests that this work may facilitate the future development of APD clinical diagnosis software.

BACKGROUND:The application of machine learning algorithms for assessing the auditory brainstem response has gained interest over recent years with a considerable number of publications in the literature. In this systematic review, we explore how machine learning has been used to develop algorithms to assess auditory brainstem responses. A clear and comprehensive overview is provided to allow clinicians and researchers to explore the domain and the potential translation to clinical care.METHODS:The systematic review was performed based on PRISMA guidelines. A search was conducted of PubMed, IEEE-Xplore, and Scopus databases focusing on human studies that have used machine learning to assess auditory brainstem responses. The duration of the search was from January 1, 1990, to April 3, 2021. The Covidence systematic review platform (www.covidence.org) was used throughout the process.RESULTS:A total of 5812 studies were found through the database search and 451 duplicates were removed. The title and abstract screening process further reduced the article count to 89 and in the proceeding full-text screening, 34 articles met our full inclusion criteria.CONCLUSION:Three categories of applications were found, namely neurologic diagnosis, hearing threshold estimation, and other (does not relate to neurologic or hearing threshold estimation). Neural networks and support vector machines were the most commonly used machine learning algorithms in all three categories. Only one study had conducted a clinical trial to evaluate the algorithm after development. Challenges remain in the amount of data required to train machine learning models. Suggestions for future research avenues are mentioned with recommended reporting methods for researchers.

Many hearing difficulties can be explained as a loss of audibility, a problem easily detected and treated using standard audiological procedures. Yet, hearing can be much poorer (or more impaired) than audibility predicts because of deficits in the suprathreshold mechanisms that encode the rapidly changing, spectral, temporal, and binaural aspects of the sound. The ability to evaluate these mechanisms requires well-defined stimuli and strict adherence to rigorous psychometric principles. This project reports on the comparison between a laboratory-based and a mobile system’s results for psychoacoustic assessment in adult listeners with normal hearing. A description of both systems employed is provided. Psychoacoustic tests include frequency discrimination, amplitude modulation detection, binaural encoding, and temporal gap detection. Results reported by the mobile system were not significantly different from those collected with the laboratory-based system for most of the tests and were consistent with those reported in the literature. The mobile system has the potential to be a feasible option for the assessment of suprathreshold auditory encoding abilities.

Objective: Children with auditory processing disorder (APD) are reported to have abnormal auditory brainstem responses (ABR) but little is understood about their cochlear integrity. Poor cochlear integrity can affect neural responses. In this study, cochlear and auditory brainstem integrity was investigated in children with APD. Method: Twenty children with APD, sixteen typically developing children and twenty adults participated in this study. Click evoked electrocochleography (ECochG) and ABRs were recorded from all the participants. Cochlear responses were analyzed using a) latency and amplitude of summating potential; action potential, b) trans-mission time between summating potential and action potential, c) summating potential/action potential amplitude ratio and d) action potential latency difference to condensation and rarefaction polarity. Amplitude in the ABR components was examined. Results: Children with APD showed similar cochlear function to the typically developing children. There were no significant differences in wave I amplitude between children with APD and typically developing children. However, wave V amplitude was significantly reduced in children with APD compared to typically developing children. Conclusion: In the absence of any functional differences in the cochlea, children with APD can show poor amplitude in the later components of the ABR. The ABR anomalies observed in children with APD arise due to poor neural processing, possibly after the first auditory synapse.

INTRODUCTION:Auditory brainstem responses (ABRs) offer a unique opportunity to assess the neural integrity of the peripheral auditory nervous system in individuals presenting with listening difficulties. ABRs are typically recorded and analyzed by an audiologist who manually measures the timing and quality of the waveforms. The interpretation of ABRs requires considerable experience and training, and inappropriate interpretation can lead to incorrect judgments about the integrity of the system. Machine learning (ML) techniques may be a suitable approach to automate ABR interpretation and reduce human error.OBJECTIVES:The main objective of this paper was to identify a suitable ML technique to automate the analysis of ABR responses recorded as a part of the electrophysiological testing in the Auditory Processing Disorder clinical test battery.METHODS:ABR responses recorded during routine clinical assessment from 136 children being evaluated for auditory processing difficulties were analyzed using several common ML algorithms: Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Gradient Boosting (GB), Extreme Gradient Boosting (Xgboost), and Neural Networks (NN). A variety of signal feature extraction techniques were used to extract features from the ABR waveforms as inputs to the ML algorithms. Statistical significance testing and confusion matrices were used to identify the most robust model capable of accurately identifying neurological abnormalities present in ABRs.RESULTS:Clinically significant features in the time-frequency representation of the signal were identified. The ML model trained using the Xgboost algorithm was identified as the most robust model with an accuracy of 92% compared to other models.CONCLUSION:The findings of the present study demonstrate that it is possible to develop accurate ML models to automate the process of analyzing ABR waveforms recorded at suprathreshold levels. There is currently no ML-based application to screen children with listening difficulties. Therefore, it is expected that this work will be translated into an evaluation tool that can be used by audiologists in the clinic. Furthermore, this work may aid future researchers in exploring ML paradigms to improve clinical test batteries used by audiologists in achieving accurate diagnoses.

Introduction: Auditory Processing Disorder (APD) present in 2-3 % of school-aged children worldwide, disrupts the ability to perceive and understand auditory information [1]. Neurophysiologic evidence of APD can be seen through evaluation of the auditory brainstem response (ABR) at the supra threshold level [2] but requires extensive training and can be labor intensive. A machine learning (ML) model was recently developed at Western University to automate ABR analysis with an accuracy of 92% [3]. Further development of the model was however limited by a lack of clinical datasets. Active learning (AL) techniques can be used to intelligently train and enhance the performance of ML models with fewer required datasets [4]. The present work aimed to improve the accuracy of the previously developed ML model by utilizing an AL strategy. Methods: Signal features were extracted from the auditory waveforms of 136 children (age range: 5-16 years, male: 88, and female: 48) suspected of APD and used to develop a ML model capable of detecting abnormal ABRs with an accuracy of 92% [3]. Next, AL techniques were used to improve the accuracy of the model. In AL, the learner (ML model) queries the oracle, or the human annotator, for the labels that it is uncertain to classify/ predict. Once it receives the labels in question, it updates the samples and retrains the model. This iterative procedure allows the model to learn from the queries and use its newly acquired knowledge to improve its accuracy. In designing the active learning loop, a Query by Committee (QBC) technique with pool-based sampling [4] was used. In QBC, a group of ML models with competing hypotheses is used to identify the most informative instance to be queried. Results: The accuracy of the model was improved to 97% (an increase of 5%) following 50 AL queries (Fig. 1). In addition, the AL technique required 127 clinical waveforms to reach this accuracy, whereas the previous supervised learning technique required 231 waveforms. Conclusion: APD is a rare disorder with limited availability of clinical data needed to train ML models. Here, the use of active learning (AL) was found to be a suitable approach to improve the accuracy of a supervised learning model while requiring a smaller number of clinical datasets. Acknowledgment: This work was supported by the Ontario Research Fund and the Natural Sciences and Engineering Council of Canada.

Objective: To assess the performance of an active transcutaneous implantable-bone conduction device (TI-BCD), and to evaluate the benefit of device digital signal processing (DSP) features in challenging listening environments. Design: Participants were tested at 1- and 3-month post-activation of the TI-BCD. At each session, aided and unaided phoneme perception was assessed using the Ling-6 test. Speech reception thresholds (SRTs) and quality ratings of speech and music samples were collected in noisy and reverberant environments, with and without the DSP features. Self-assessment of the device performance was obtained using the Abbreviated Profile of Hearing Aid Benefit (APHAB) questionnaire. Study sample: Six adults with conductive or mixed hearing loss. Results: Average SRTs were 2.9 and 12.3 dB in low and high reverberation environments, respectively, which improved to -1.7 and 8.7 dB, respectively with the DSP features. In addition, speech quality ratings improved by 23 points with the DSP features when averaged across all environmental conditions. Improvement scores on APHAB scales revealed a statistically significant aided benefit. Conclusions: Noise and reverberation significantly impacted speech recognition performance and perceived sound quality. DSP features (directional microphone processing and adaptive noise reduction) significantly enhanced subjects' performance in these challenging listening environments.

This paper evaluated the performance of an envelope enhancement (EE) algorithm subjectively by children with auditory processing disorder (APD), and objectively through computational models. Speech intelligibility data was collected from children with APD, for unprocessed and envelope-enhanced speech in the presence of stationary and non-stationary background noise at different signal to noise ratios (SNRs), both with and without noise reduction (NR) algorithms as a front-end to the EE algorithm. Furthermore, intrusive and non-intrusive objective speech intelligibility metrics were derived to predict the perceptual impact of this EE algorithm. Subjective data for stationary noise conditions revealed that the combination of NR and EE algorithms significantly improved the speech intelligibility scores at poor SNRs. In contrast, the same combination was ineffective in improving speech intelligibility in non-stationary noise conditions. Taken together, subjective results suggest that exaggerating the envelope cues improves speech identification scores for children with APD. However, the benefit obtained varies depending upon the type and level of the background noise. Both intrusive and non-intrusive objective speech intelligibility estimators exhibited good correlation with the subjective data, with the intrusive metric demonstrating better generalization capabilities. Implications of these results for hearing aid applications for children with APD is discussed.

Objectives: We sought to investigate whether children referred to our audiology clinic with a complaint of listening difficulty, that is, suspected of auditory processing disorder (APD), have difficulties localizing sounds in noise and whether they have reduced benefit from spatial release from masking. Design: Forty-seven typically hearing children in the age range of 7 to 17 years took part in the study. Twenty-one typically developing (TD) children served as controls, and the other 26 children, referred to our audiology clinic with listening problems, were the study group: suspected APD (sAPD). The ability to localize a speech target (the word "baseball") was measured in quiet, broadband noise, and speech-babble in a hemi-anechoic chamber. Participants stood at the center of a loudspeaker array that delivered the target in a diffused noise-field created by presenting independent noise from four loudspeakers spaced 90 degrees apart starting at 45 degrees. In the noise conditions, the signal-to-noise ratio was varied between -12 and 0 dB in 6-dB steps by keeping the noise level constant at 66 dB SPL and varying the target level. Localization ability was indexed by two metrics, one assessing variability in lateral plane [lateral scatter (Lscat)] and the other accuracy in the front/back dimension [front/back percent correct (FBpc)]. Spatial release from masking (SRM) was measured using a modified version of the Hearing in Noise Test (HINT). In this HINT paradigm, speech targets were always presented from the loudspeaker at 0 degrees, and a single noise source was presented either at 0 degrees, 90 degrees, or 270 degrees at 65 dB A. The SRM was calculated as the difference between the 50% correct HINT speech reception threshold obtained when both speech and noise were collocated at 0 degrees and when the noise was presented at either 90 degrees or 270 degrees. Results: As expected, in both groups, localization in noise improved as a function of signal-to-noise ratio. Broadband noise caused significantly larger disruption in FBpc than in Lscat when compared with speech babble. There were, however, no group effects or group interactions, suggesting that the children in the sAPD group did not differ significantly from TD children in either localization metric (Lscat and FBpc). While a significant SRM was observed in both groups, there were no group effects or group interactions. Collectively, the data suggest that children in the sAPD group did not differ significantly from the TD group for either binaural measure investigated in the study. Conclusions: As is evident from a few poor performers, some children with listening difficulties may have difficulty in localizing sounds and may not benefit from spatial separation of speech and noise. However, the heterogeneity in APD and the variability in our data do not support the notion that localization is a global APD problem. Future studies that employ a case study design might provide more insights.

Objective: The purpose of this study was to examine developmental trends in spectral ripple discrimination (SRD) and to compare the performance of typically developing children to children with auditory processing disorder (APD). Study design: Cross-sectional study. Study sample: Fifteen children with APD, as well as 17 typically developing children and 14 adults reporting no listening or academic difficulties participated. Results: Typically developing children showed poor SRD thresholds compared to adults, indicating prolonged maturation of spectral shape recognition. Both typically developing children and APD children showed a maturational trend in SRD, but a General Linear Model fit to their thresholds showed that children with APD displayed SRD thresholds that were significantly poorer than those of typically developing children when controlling for age. This suggests that in APD children, SRD maturation lags behind typically developing children. Conclusion: Poor spectral ripple discrimination may explain some of the listening difficulties experienced by children with APD.

The medial olivocochlear reflex (MOCR) has been implicated in several auditory processes. The putative role of the MOCR in improving speech perception in noise is particularly relevant for children who complain of listening difficulties (LiD). The hypothesis that the MOCR may be impaired in individuals with LiD or auditory processing disorder has led to several investigations but without consensus. In two related studies, we compared the MOCR functioning of children with LiD and typically developing (TD) children in the same age range (7-17 years). In Study 1, we investigated ipsilateral, contralateral, and bilateral MOCR using forward-masked click-evoked otoacoustic emissions (CEOAEs; n = 17 TD, 17 LiD). In Study 2, we employed three OAE types: CEOAEs (n = 16 TD, 21 LiD), stimulus frequency OAEs (n = 21 TD, 30 LiD), and distortion product OAEs (n = 17 TD, 22 LiD) in a contralateral noise paradigm. Results from both studies suggest that the MOCR functioning is not significantly different between the two groups. Some likely reasons for differences in findings among published studies could stem from the lack of strict data quality measures (e.g., high signal-to-noise ratio, control for the middle ear muscle reflex) that were enforced in the present study. The inherent variability of the MOCR, the subpar reliability of current MOCR methods, and the heterogeneity in auditory processing deficits that underlie auditory processing disorder make detecting clinically relevant differences in MOCR function impractical using current methods.

Individuals with auditory neuropathy spectrum disorder (ANSD) or auditory processing disorders (APDs) often suffer from temporal processing deficits leading to degraded speech perception. The situation becomes worse in the presence of background noise. Evidence exists that the exaggeration of speech envelope may enhance intelligibility, although a comprehensive evaluation of envelope enhancement algorithms is lacking. In the present study, two schemes of envelope enhancement algorithms, with and without an additional noise reduction algorithm, were applied to sentence-level-stimuli in different background noise conditions. The algorithms were assessed objectively using the Hearing Aid Speech Perception Index (HASPI). Results showed that the envelope enhancement algorithms are effective in improving the predicted speech intelligibility score under certain Signal-to-Noise Ratio (SNR) conditions.

Background: The ASHA recommends including electrophysiological measures in an auditory processing disorder (APD) assessment battery, but few audiologists do so, potentially because of limited published evidence for its utility. Purpose: This study compared the auditory brainstem responses (ABRs) of children with APD with age-matched children and adults. Study Sample: This study retrospectively examined the records of 108 children suspected of APD (sAPD) who had click-evoked ABRs recorded as part of their clinical assessment. Twenty adults and 22 typically developing (TD) children were recruited as controls. Data collection and Analysis: Click-evoked ABRs were recorded at slow (13.3 clicks/sec) and faster (57.7 clicks/sec) stimulation rates. ABRs were analyzed using typical clinical measures (latencies and interpeak intervals for waves I, III, and V) and using a model proposed by Ponton et al that offered a more detailed analysis of axonal conduction time and synaptic transmission delay. Results: Both clinical measures and the Ponton model analysis showed no significant differences between TD children and adults. Children sAPD showed absolute latencies that were significantly prolonged when compared with adults but not when compared with TD children. But individual children sAPD showed clinically significant delays (>2 standard deviations of TD children's data). Examination of responses delineating axonal versus synaptic transmission showed significant delays in synaptic transmission in the group of children sAPD in comparison to TD children and adults. These results suggest that a significant portion of children with listening difficulties showed evidence of reduced or atypical brainstem functioning. Examining the responses for axonal and synaptic delays revealed evidence of a synaptic pattern of abnormalities in a significant portion (37.03%) of children sAPD. Such observations could provide objective evidence of factors potentially contributing to listening difficulties that are frequently reported in children identified with APD. Conclusions: Children sAPD often showed abnormalities in the ABR, suggesting a neurophysiologic origin of their reported difficulties, frequently originating at or before the first synapse. This study provides supportive evidence for the value of click-evoked ABRs in comprehensive auditory processing assessment batteries.

Purpose A growing body of evidence indicates that treatment of hearing loss by provision of hearing aids leads to improvements in auditory and visual working memory. The purpose of this study was to assess whether similar working memory benefits are observed following provision of cochlear implants (CIs). Method Fifteen adults with postlingually acquired severe bilateral sensorineural hearing loss completed the prospective longitudinal study. Participants were candidates for bilateral cochlear implantation with some aidable hearing in each ear. Implantation surgeries were carried out sequentially, approximately 1 year apart. Working memory was measured with the visual Reading Span Test (Daneman & Carpenter, 1980) at 5 time points: pre-operatively following a 6-month bilateral hearing aid trial, after 6 and 12 months of bimodal (CI plus contralateral hearing aid) listening experience following the 1st CI surgery and activation, and again after 6 and 12 months of bilateral CI listening experience following the 2nd CI surgery and activation. Results Compared to the preoperative baseline, CI listening experience yielded significant improvements in participants' ability to recall test words in the correct serial order after 12 months in the bimodal condition. Individual performance outcomes were variable, but almost all participants showed increases in task performance over the course of the study. Conclusions These results suggest that, similar to appropriate interventions with hearing aids, treatment of hearing loss with CIs can yield working memory benefits. A likely mechanism is the freeing of cognitive resources previously devoted to effortful listening.

Early childhood is a period of tremendous growth in both language ability and brain maturation. To understand the dynamic interplay between neural activity and spoken language development, we used resting-state EEG recordings to explore the relation between alpha oscillations (7-10 Hz) and oral language ability in 4- to 6-yearold children with typical development (N = 41). Three properties of alpha oscillations were investigated: a) alpha power using spectral analysis, b) flexibility of the alpha frequency quantified via the oscillation's momentto-moment fluctuations, and c) scaling behavior of the alpha oscillator investigated via the long-range temporal correlation in the alpha-amplitude time course. All three properties of the alpha oscillator correlated with children's oral language abilities. Higher language scores were correlated with lower alpha power, greater flexibility of the alpha frequency, and longer temporal correlations in the alpha-amplitude time course. Our findings demonstrate a cognitive role of several properties of the alpha oscillator that has largely been overlooked in the literature.

The test battery typically used for the diagnosis of auditory processing disorder (APD) is highly heterogeneous, with an emphasis on the central auditory nervous system. As such, the peripheral auditory system is typically only screened for the presence of an overt hearing loss. Our previous work suggested that children suspected of APD (sAPD) have atypically sharp cochlear tuning when measured using stimulus frequency otoacoustic emission (SFOAE) group delay. In the present work, we extend our previous findings and test the hypothesis that cochlear tuning influences auditory brainstem response (ABR) latencies. Our hypothesis is based on filter theory, which suggests that a sharper filter will take longer to build-up and ring longer. We predicted that sharper cochlear filters in sAPD should result in delayed ABR wave latencies and will be associated with poorer performance on speech perception tests. Preliminary data from 16 sAPD and 6 typically developing children show a positive correlation between cochlear tuning and ABR peak I latency. Cochlear tuning explains a significant proportion of the variance in ABR peak I latency (R2 = 0.25). Further behavioral results and implications for inclusion of auditory peripheral examination in APD tests will be discussed.

BACKGROUND:Previous studies have suggested elevated reflex thresholds in children with auditory processing disorders (APDs). However, some aspects of the child's ear such as ear canal volume and static compliance of the middle ear could possibly affect the measurements of reflex thresholds and thus impact its interpretation. Sound levels used to elicit reflexes in a child's ear may be higher than predicted by calibration in a standard 2-cc coupler, and lower static compliance could make visualization of very small changes in impedance at threshold difficult. For this purpose, it is important to evaluate threshold data with consideration of differences between children and adults. PURPOSE:A set of studies were conducted. The first compared reflex thresholds obtained using standard clinical procedures in children with suspected APD to that of typically developing children and adults to test the replicability of previous studies. The second study examined the impact of ear canal volume on estimates of reflex thresholds by applying real-ear corrections. Lastly, the relationship between static compliance and reflex threshold estimates was explored. RESEARCH DESIGN:The research is a set of case-control studies with a repeated measures design. STUDY SAMPLE:The first study included data from 20 normal-hearing adults, 28 typically developing children, and 66 children suspected of having an APD. The second study included 28 normal-hearing adults and 30 typically developing children. DATA COLLECTION AND ANALYSIS:In the first study, crossed and uncrossed reflex thresholds were measured in 5-dB step size. Reflex thresholds were analyzed using repeated measures analysis of variance (RM-ANOVA). In the second study, uncrossed reflex thresholds, real-ear correction, ear canal volume, and static compliance were measured. Reflex thresholds were measured using a 1-dB step size. The effect of real-ear correction and static compliance on reflex threshold was examined using RM-ANOVA and Pearson correlation coefficient, respectively. RESULTS:Study 1 replicated previous studies showing elevated reflex thresholds in many children with suspected APD when compared to data from adults using standard clinical procedures, especially in the crossed condition. The thresholds measured in children with suspected APD tended to be higher than those measured in the typically developing children. There were no significant differences between the typically developing children and adults. However, when real-ear calibrated stimulus levels were used, it was found that children's thresholds were elicited at higher levels than in the adults. A significant relationship between reflex thresholds and static compliance was found in the adult data, showing a trend for higher thresholds in ears with lower static compliance, but no such relationship was found in the data from the children. CONCLUSIONS:This study suggests that reflex measures in children should be adjusted for real-ear-to-coupler differences before interpretation. The data in children with suspected APD support previous studies suggesting abnormalities in reflex thresholds. The lack of correlation between threshold and static compliance estimates in children as was observed in the adults may suggest a nonmechanical explanation for age and clinically related effects.

Children as young as 5 yr old localize sounds as accurately as adults in quiet in the frontal hemifield. However, children's ability to localize in noise and in the front/back (F/B) dimension are scantily studied. To address this, the first part of this study investigated localization-in-noise ability of children vs young adults in two maskers: broadband noise (BBN) and speech-babble (SB) at three signal-to-noise ratios: -12, -6, and 0 dB. In the second part, relationship between binaural medial olivocochlear system (MOC) function and localization-in-noise was investigated. In both studies, 21 children and 21 young adults participated. Results indicate, while children are able to differentiate sounds arriving in the F/B dimension on par with adults in quiet and in BBN, larger differences were found for SB. Accuracy of children's localization in noise (for both maskers) in the lateral plane was also poorer than adults'. Significant differences in binaural MOC interaction (mBIC; the difference between the sum of two monaural- and binaural-MOC strength) between adults and children were also found. For reasons which are not clear, adult F/B localization in BBN correlates better with mBIC while children's F/B localization in SB correlated better with binaural MOC strength.

Objective: Previous data suggested that children with suspected auditory processing disorders (APD) often show elevated or absent acoustic reflex thresholds, especially in crossed conditions (e.g. Allen & Allan, 2014). This study further explored these effects by measuring acoustic reflex growth functions (ARGF). Design: Crossed and uncrossed ARGF slopes were obtained by linear fits between reflex amplitudes and increases in activator level from threshold to 15 dB above it. Study sample: Normal-hearing adults, typically developing children and children with reported listening difficulties and suspected of having an APD, participated. Results: The ARGF slopes were shallower in crossed than in uncrossed conditions for all groups but the magnitude of the effect was significantly greater in the children with suspected APD. There were no differences between the typically developing children and the adults. Conclusions: The results suggest shallower ARGFs in children with suspected APD. Given the role of the acoustic reflex in facilitating hearing speech in noise these findings may begin to shed light on physiologic explanations for some of the difficulties that are reported by children with suspected APD.