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Hearing loss is associated with multiple physical, cognitive, and psychosocial co-morbidities. Achievement of safe healthcare in the context of these complex co-morbidities necessitates accurate hearing and coordination across specialties. This paper discusses the potentials for and barriers to an interprofessional approach to integrating hearing screening and treatment across all healthcare settings.The paper reviews the relationship between hearing loss and other health care concerns to emphasise the need for an inclusive, coordinated, interprofessional approach; discusses interprofessional and patient/family centred coordinated care as essential to achieving quality care; and introduces the Age Friendly Health System initiative as a framework that could be leveraged to move towards comprehensive hearing healthcare.The literature highlights prior work identifying gaps in quality care and the need for new and innovative approaches to evolve interdisciplinary and interprofessional collaborations to achieve comprehensive healthcare. The literature also provides support for using the Age-Friendly initiative as a point of leverage.Bringing together thought leaders from the health care provider community, World Health Organisation, age-friendly cities movement, and field of architecture to coordinate the integration of hearing healthcare into Age Friendly Health Systems initiatives has potential to achieve comprehensive hearing healthcare across healthcare settings. (198).

Islene Araujo de Carvalho and coauthors discuss the WHO guidelines on integrated care for older people.

The frequency-following response with origin in the auditory brainstem represents the pitch contour of voice and can be recorded with electrodes from the scalp. MEG studies also revealed a cortical contribution to the high gamma oscillations at the fundamental frequency (f0) of a vowel stimulus. Therefore, studying the cortical component of the frequency-following response could provide insights into how pitch information is encoded at the cortical level. Comparing how aging affects the different responses may help to uncover the neural mechanisms underlying speech understanding deficits in older age. We simultaneously recorded EEG and MEG responses to the syllable /ba/. MEG beamformer analysis localized sources in bilateral auditory cortices and the midbrain. Time-frequency analysis showed a faithful representation of the pitch contour between 106 Hz and 138 Hz in the cortical activity. A cross-correlation revealed a latency of 20 ms. Furthermore, stimulus onsets elicited cortical 40-Hz responses. Both the 40-Hz and the f0 response amplitudes increased in older age and were larger in the right hemisphere. The effects of aging and laterality of the f0 response were evident in the MEG only, suggesting that both effects were characteristics of the cortical response. After comparing f0 and N1 responses in EEG and MEG, we estimated that approximately one-third of the scalp-recorded f0 response could be cortical in origin. We attributed the significance of the cortical f0 response to the precise timing of cortical neurons that serve as a time-sensitive code for pitch.

The Fifth Eriksholm Workshop on “Hearing Impairment and Cognitive Energy” was convened to develop a consensus among interdisciplinary experts about what is known on the topic, gaps in knowledge, the use of terminology, priorities for future research, and implications for practice. The general term cognitive energy was chosen to facilitate the broadest possible discussion of the topic. It goes back to Titchener (1908) who described the effects of attention on perception; he used the term psychic energy for the notion that limited mental resources can be flexibly allocated among perceptual and mental activities. The workshop focused on three main areas: (1) theories, models, concepts, definitions, and frameworks; (2) methods and measures; and (3) knowledge translation. We defined effort as the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a task, with listening effort applying more specifically when tasks involve listening. We adapted Kahneman’s seminal (1973) Capacity Model of Attention to listening and proposed a heuristically useful Framework for Understanding Effortful Listening (FUEL). Our FUEL incorporates the well-known relationship between cognitive demand and the supply of cognitive capacity that is the foundation of cognitive theories of attention. Our FUEL also incorporates a motivation dimension based on complementary theories of motivational intensity, adaptive gain control, and optimal performance, fatigue, and pleasure. Using a three-dimensional illustration, we highlight how listening effort depends not only on hearing difficulties and task demands but also on the listener’s motivation to expend mental effort in the challenging situations of everyday life.

Even though speech signals trigger coding in the cochlea to convey speech information to the central auditory structures, little is known about the neural mechanisms involved in such processes. The purpose of this study was to understand the encoding of formant cues and how it relates to vowel recognition in listeners. Neural representations of formants may differ across listeners; however, it was hypothesized that neural patterns could still predict vowel recognition. To test the hypothesis, the frequency-following response (FFR) and vowel recognition were obtained from 38 normal-hearing listeners using four different vowels, allowing direct comparisons between behavioral and neural data in the same individuals. FFR was employed because it provides an objective and physiological measure of neural activity that can reflect formant encoding. A mathematical model was used to describe vowel confusion patterns based on the neural responses to vowel formant cues. The major findings were (1) there were large variations in the accuracy of vowel formant encoding across listeners as indexed by the FFR, (2) these variations were systematically related to vowel recognition performance, and (3) the mathematical model of vowel identification was successful in predicting good vs poor vowel identification performers based exclusively on physiological data.

Purpose This study evaluated the relationship between working memory (WM) and speech recognition in noise with different noise types as well as in the presence of visual cues. Method Seventy-six adults with bilateral, mild to moderately severe sensorineural hearing loss (mean age: 69 years) participated. Using a cross-sectional design, 2 measures of WM were taken: a reading span measure, and Word Auditory Recognition and Recall Measure (Smith, Pichora-Fuller, & Alexander, 2016). Speech recognition was measured with the Multi-Modal Lexical Sentence Test for Adults (Kirk et al., 2012) in steady-state noise and 4-talker babble, with and without visual cues. Testing was under unaided conditions. Results A linear mixed model revealed visual cues and pure-tone average as the only significant predictors of Multi-Modal Lexical Sentence Test outcomes. Neither WM measure nor noise type showed a significant effect. Conclusion The contribution of WM in explaining unaided speech recognition in noise was negligible and not influenced by noise type or visual cues. We anticipate that with audibility partially restored by hearing aids, the effects of WM will increase. For clinical practice to be affected, more significant effect sizes are needed.

The aims of this study were to: 1) quantify the amount of change in signal-to-noise ratio (SNR) as a result of compression and noise reduction (NR) processing in devices from three hearing aid (HA) manufacturers and 2) use the SNR changes to predict changes in speech perception. We hypothesised that the SNR change would differ across processing type and manufacturer, and that improvements in SNR would relate to improvements in performance.SNR at the output of the HAs was quantified using a phase-inversion technique. A linear mixed model was used to determine whether changes in SNR across HA conditions were predictive of changes in aided speech perception in noise.Two groups participated: 25 participants had normal-hearing and 25 participants had mild to moderately severe sensorineural hearing loss.The HAs programmed for both groups changed the SNR by a small, but statistically significant amount. Significant interactions in SNR changes were observed between HA devices and processing types. However, the change in SNR was not predictive of changes in speech perception.Although observed significant changes in SNR resulting from compression and NR did not convert to changes in speech perception, these algorithms may serve other purposes.

Here:, we describe some of the ways in which aging negatively affects the way sensory input is transduced and processed within the aging brain and how cognitive work is involved when listening to a less-than-perfect signal. We also describe how audiologic rehabilitation, including hearing aid amplification and listening training, is used to reduce the amount of cognitive resources required for effective auditory communication and conclude with an example of how listening effort is being studied in research laboratories for the purpose(s) of informing clinical practice.

This commentary explores the role of public health programs and themes on hearing health care. Ongoing engagement within the hearing professional community is needed to determine how to change the landscape and identify important features in the evolution of population hearing health care. Why and how to leverage existing public health programs and develop new programs to improve hearing health in older individuals is an important topic. Hearing professionals are encouraged to reflect on these themes and recommendations and join the discussion about the future of hearing science on a population level.

Sensory abilities decline with age. More than 5% of the world's population, approximately 360 million people, have disabling hearing loss. In adults, disabling hearing loss is defined by thresholds greater than 40 dBHL in the better hearing ear.Hearing disability is an important issue in geriatric medicine because it is associated with numerous health issues, including accelerated cognitive decline, depression, increased risk of dementia, poorer balance, falls, hospitalizations, and early mortality. There are also social implications, such as reduced communication function, social isolation, loss of autonomy, impaired driving ability, and financial decline. Furthermore, the onset of hearing loss is gradual and subtle, first affecting the detection of high-pitched sounds and with difficulty understanding speech in noisy but not in quiet environments. Consequently, delays in recognizing and seeking help for hearing difficulties are common. Age-related hearing loss has no known cure, and technologies (hearing aids, cochlear implants, and assistive devices) improve thresholds but do not restore hearing to normal. Therefore, health care for persons with hearing loss and people within their communication circles requires education and counseling (e.g., increasing knowledge, changing attitudes, and reducing stigma), behavior change (e.g., adapting communication strategies), and environmental modifications (e.g., reducing noise). In this article, we consider the causes, consequences, and magnitude of hearing loss from a life-course perspective. We examine the concept of "hearing health," how to achieve it, and implications for policy and practice.

Performance improvement during an hour of auditory perceptual training is accompanied by rapid physiological changes. These changes may reflect learning or simply task repetition independent of learning. We assessed the contribution of learning and task repetition to changes in auditory evoked potentials during a difficult speech identification task and an easy tone identification task. We posited that only task repetition effects would occur in the tone task but that task repetition and learning would interact in the speech task. Speech identification improved with practice (increased sensitivity d' with a constant response bias β). This behavioral improvement coincided with a decrease in the amplitude of sensory evoked responses (N1, P2) and a decrease in the amplitude of a slow wave (peak=320 ms after onset) over the left frontal and parietal sites. Results show rapid physiological changes associated with learning, distinct from changes related to task repetition.

Older adults, even with clinically normal hearing sensitivity, have auditory perceptual deficits relative to their younger counterparts. This difficulty may in part, be related to a decline in the neural representation of frequency. The purpose of this study was to examine the effect of age on behavioral and physiological measures of frequency representation. Thirty two adults (ages 22–77), with hearing thresholds ⩽25 dB HL at octave frequencies 0.25–8.0 kHz, participated in this experiment. Frequency discrimination difference limens (FDLs) were obtained at 500 and 1000 Hz using a two-interval, two-alternative forced choice procedure. Linear regression analyses showed significant declines in FDLs at both frequencies as age increased. Frequency-following responses (FFRs) were elicited by 500 and 1000 Hz tonebursts, as well as at frequencies within and outside those FDLs. Linear regression of FFR phase coherence and FFR amplitude at frequencies at and slightly below 1000 Hz showed significant decreases as age increased. Therefore, pitch discrimination, as measured by FDLs, and neural representation of frequency, as reflected by FFR, declined as age increased. Although perception and neural representation concurrently declined, one was not predictive of the other.

Perceptual learning is sometimes characterized by rapid improvements in performance within the first hour of training (fast perceptual learning), which may be accompanied by changes in sensory and/or response pathways. Here, we report rapid physiological changes in the human auditory system that coincide with learning during a 1-hour test session in which participants learned to identify two consonant vowel syllables that differed in voice onset time. Within each block of trials, listeners were also presented with a broadband noise control stimulus to determine whether changes in auditory evoked potentials were specific to the trained speech cue. The ability to identify the speech sounds improved from the first to the fourth block of trials and remained relatively constant thereafter. This behavioral improvement coincided with a decrease in N1 and P2 amplitude, and these learning-related changes differed from those observed for the noise stimulus. These training-induced changes in sensory evoked responses were followed by an increased negative peak (between 275 and 330 msec) over fronto-central sites and by an increase in sustained activity over the parietal regions. Although the former was also observed for the noise stimulus, the latter was specific to the speech sounds. The results are consistent with a top–down nonspecific attention effect on neural activity during learning as well as a more learning-specific modulation, which is coincident with behavioral improvements in speech identification.

Experiencing repeatedly presented auditory stimuli during magnetoencephalographic (MEG) recording may affect how the sound is processed in the listener’s brain and may modify auditory evoked responses over the time course of the experiment. Amplitudes of N1 and P2 responses have been proposed as indicators for the outcome of training and learning studies. In this context the effect of merely sound experience on N1 and P2 responses was studied during two experimental sessions on different days with young, middle-aged, and older participants passively listening to speech stimuli and a noise sound. N1 and P2 were characterized as functionally distinct responses with P2 sources located more anterior than N1 in auditory cortices. N1 amplitudes decreased continuously during each recording session, but completely recovered between sessions. In contrast, P2 amplitudes were fairly constant within a session but increased from the first to the second day of MEG recording. Whereas N1 decrease was independent of age, the amount of P2 amplitude increase diminished with age. Temporal dynamics of N1 and P2 amplitudes were interpreted as reflecting neuroplastic changes along different time scales. The long lasting increase in P2 amplitude indicates that the auditory P2 response is potentially an important physiological correlate of perceptual learning, memory, and training.

Speech-evoked auditory event-related potentials (ERPs) provide insight into the neural mechanisms underlying speech processing. For this reason, ERPs are of great value to hearing scientists and audiologists. This article will provide an overview of ERPs frequently used to examine the processing of speech and other sound stimuli. These ERPs include the P1-N1-P2 complex, acoustic change complex, mismatch negativity, and P3 responses. In addition, we focus on the application of these speech-evoked potentials for the assessment of (1) the effects of hearing loss on the neural encoding of speech allowing for behavioral detection and discrimination; (2) improvements in the neural processing of speech with amplification (hearing aids, cochlear implants); and (3) the impact of auditory training on the neural processing of speech. Studies in these three areas are reviewed and implications for audiologists are discussed.

Older adults often have difficulty understanding speech in a noisy environment or with multiple speakers. In such situations, binaural hearing improves the signal-to-noise ratio. How does this binaural advantage change with increasing age? Using magnetoencephalography, we recorded cortical activity evoked by changes in interaural phase differences of amplitude-modulated tones. These responses occurred for frequencies up to 1225 Hz in young subjects but only up to 940 Hz in middle-aged and 760 Hz in older adults. Behavioral thresholds also decreased with increasing age but were more variable, likely because some older adults make effective use of compensatory mechanisms. The reduced frequency range for binaural hearing became significant in middle age, before decline in hearing sensation and the morphology of cortical responses, which became apparent only in the older subjects. This study provides evidence from human physiological data for the early onset of biological aging in binaural hearing.

It is well documented that aging adversely affects the ability to perceive time-varying acoustic cues. Here we review how physiological measures are being used to explore the effects of aging (and concomitant hearing loss) on the neural representation of temporal cues. Also addressed are the implications of current research findings on the rehabilitation of older hearing-impaired adults. LEARNER OUTCOMES: (1) Identify one evoked potential that reflects age-related physiological changes in the brain. (2) List three contributing factors for why older adults have difficult understanding speech in noise. (3) Give an example of a top-down approach to auditory rehabilitation.

The perception of complex acoustic signals such as speech and music depends on the interaction between peripheral and central auditory processing. As information travels from the cochlea to primary and associative auditory cortices, the incoming sound is subjected to increasingly more detailed and refined analysis. These various levels of analyses are thought to include low-level automatic processes that detect, discriminate and group sounds that are similar in physical attributes such as frequency, intensity, and location as well as higher-level schema-driven processes that reflect listeners' experience and knowledge of the auditory environment. In this review, we describe studies that have used event-related brain potentials in investigating the processing of complex acoustic signals (e.g., speech, music). In particular, we examine the role of hearing loss on the neural representation of sound and how cognitive factors and learning can help compensate for perceptual difficulties. The notion of auditory scene analysis is used as a conceptual framework for interpreting and studying the perception of sound. La percepción de señales acústicas complejas, tales como el lenguaje y la música, dependen de la interacción entre el procesamiento auditivo central y periférico. Conforme la información viaja de la cóclea a la corteza auditiva primaria y de asociación, el sonido entrante se somete un análisis progresivamente más detallado y refinado. Se cree que estos varios niveles de análisis incluyen procesos automáticos de bajo nivel que detectan, discriminan y agrupan los sonidos que son similares en cuanto a los atributos físicos, como la frecuencia, la intensidad y la localización, así como procesos dirigidos por esquemas de más alto nivel, que reflejan la experiencia y el conocimiento del sujeto del ambiente auditivo. En esta revisión, describimos estudios que han utilizado potenciales cerebrales relacionados con el evento, para investigar el procesamiento de señales acústicas complejas (p.e., lenguaje, música). En particular, examinamos el papel de las pérdidas auditivas sobre la representación neural del sonido y de cómo los factores cognitivos y el aprendizaje pueden ayudar a compensar las dificultades perceptivas. La noción de un análisis de la escena auditiva se utiliza como un marco conceptual, para interpretar y estudiar la percepción del sonido.

The ability to perceive time-varying acoustic changes deteriorates with advancing age. To learn more about the mechanisms underlying such perceptual deficits, we used magnetoencephalography (MEG) to examine the physiological response to interaural phase differences (IPD) in young, middle-aged, and older adults. Stimulus onset evoked P1m–N1m–P2m cortical responses, as did the change in interaural phase. There were no significant age-related latency differences in the detection of sound “onset”; however, the ability to detect “changes” within the stimulus deteriorated with increased age. Peak latencies were prolonged for the “change” response when compared to the “onset” response, suggesting that the physiological detection of IPDs requires more time than detecting sound “onset”. These results provide physiological evidence of impaired temporal processing in the elderly that is likely unrelated to hearing loss or cognitive ability because brain activity was measured passively in response to audible low frequency stimuli.

Auditory-evoked potentials are being used to examine training-related changes in the human central auditory system, and there is converging evidence that focused listening training, using various training methods and different types of stimuli alters evoked neural activity. Such training-related changes are often described in terms of PHYSIOLOGICAL PLASTICITY, a process whereby the neural representation of the acoustic cue is modified with training. In this review, the concept of plasticity is discussed from a broader perspective. Specifically addressed is how electrophysiological methods are being used to study physiological modifications that occur with training, and how this information might contribute to the rehabilitation of people who wear hearing aids and cochlear implants.

Auditory evoked cortical responses to changes in the interaural phase difference (IPD) were recorded using magnetoencephalography (MEG). Twelve normal-hearing young adults were tested with amplitude-modulated tones with carrier frequencies of 500, 1000, 1250, and 1500 Hz. The onset of the stimuli evoked P1m-N1m-P2m cortical responses, as did the changes in the interaural phase. Significant responses to IPD changes were identified at 500 and 1000 Hz in all subjects and at 1250 Hz in nine subjects, whereas responses were absent in all subjects at 1500 Hz, indicating a group mean threshold for detecting IPDs of 1250 Hz. Behavioral thresholds were found at 1200 Hz using an adaptive two alternative forced choice procedure. Because the physiological responses require phase information, through synchronous bilateral inputs at the level of the auditory brainstem, physiological "change" detection thresholds likely reflect the upper limit of phase synchronous activity in the brainstem. The procedure has potential applications in investigating impaired binaural processing because phase statistic applied to single epoch MEG data allowed individual thresholds to be obtained.

Hearing aid amplification can be used as a model for studying the effects of auditory stimulation on the central auditory system (CAS). We examined the effects of stimulus presentation level on the physiological detection of sound in unaided and aided conditions. P1, N1, P2, and N2 cortical evoked potentials were recorded in sound field from 13 normal-hearing young adults in response to a 1000-Hz tone presented at seven stimulus intensity levels. As expected, peak amplitudes increased and peak latencies decreased with increasing intensity for unaided and aided conditions. However, there was no significant effect of amplification on latencies or amplitudes. Taken together, these results demonstrate that 20 dB of hearing aid gain affects neural responses differently than 20 dB of stimulus intensity change. Hearing aid signal processing is discussed as a possible contributor to these results. This study demonstrates (1) the importance of controlling for stimulus intensity when evoking responses in aided conditions, and (2) the need to better understand the interaction between the hearing aid and the CAS.

The extent to which audibility determines speech recognition depends on a number of signal and listener factors. This study focused on three factors: age, background noise modulation, and linear versus wide-dynamic compression amplification. Three audiometrically matched groups of older listeners with hearing loss were tested to determine at what age performance declined relative to that expected on the basis of audibility. Recognition fell below predicted scores by greater amounts as age increased. Scores were higher for steady versus amplitude-modulated noise. Scores for WDRC-amplified speech were slightly lower than for linearly amplified speech across all groups and noise conditions. We found no interaction between age and type of noise. The small reduction in scores for amplitude-modulated compared to steady noise and lack of age interaction suggests that the substantial deficit seen with age in multitalker babble for previous studies was due to some effect not elicited here, such as informational masking. La medida en la cuál la audibilidad determina el reconocimiento del lenguaje depende de un número de factores relacionados con la señal y el oyente. Este estudio se concentró en tres factores: edad, modulación del ruido de fondo, y amplificación lineal versus amplificación de compresión dinámica amplia. Se evaluaron tres grupos pareados audiométricamente con oyentes mayores con hipoacusia, para determinar a qué edad declina el desempeño auditivo en relación al esperado, con base en la audibilidad. El reconocimiento cayó por debajo de los puntajes de predicción en cantidades mayores conforme aumenta la edad. Los puntajes fueron mayores para ruidos estables versus ruidos de amplitud modulada. Los puntajes para lenguaje amplificado con WDRC fueron levemente menores que para lenguaje linealmente amplificado, en todos los grupos y condiciones de ruido. No se encontró interacción entre la edad y el tipo de ruido. La pequeña reducción en los puntajes para amplitud modulada comparada con el ruido estable y la falta de interacción con la edad sugieren que el déficit sustancial visto con la edad, en medio de balbuceo de hablantes múltiples en estudio previos, se debía a algún efecto no provocado aquí, tal como el enmascaramiento de información.

OBJECTIVE Clinicians encounter patients who report experiencing hearing difficulty (HD) even when audiometric thresholds fall within normal limits. When there is no evidence of audiometric hearing loss, it generates debate over possible biomedical and psychosocial etiologies. It is possible that self-reported HDs relate to variables within and/or outside the scope of audiology. The purpose of this study is to identify how often, on a population basis, people with normal audiometric thresholds self-report HD and to identify factors associated with such HDs. DESIGN This was a cross-sectional investigation of participants in the Beaver Dam Offspring Study. HD was defined as a self-reported HD on a four-item scale despite having pure-tone audiometric thresholds within normal limits (

Purpose The purpose of this article is to review recent research from our laboratory on the topic of aging, and the ear–brain system, as it relates to hearing aid use and auditory rehabilitation. The material described here was presented as part of the forum on the brain and hearing aids, at the 2014 HEaling Across the Lifespan (HEAL) conference. Method The method involves a narrative review of previously reported electroencephalography (EEG) and magnetoencephalography (MEG) data from our laboratory as they relate to the (a) neural detection of amplified sound and (b) ability to learn new sound contrasts. Conclusions Results from our studies add to the mounting evidence that there are central effects of biological aging as well as peripheral pathology that affect a person's neural detection and use of sound. What is more, these biological effects can be seen as early as middle age. The accruing evidence has implications for hearing aid use because effective communication relies not only on sufficient detection of sound but also on the individual's ability to learn to make use of these sounds in ever-changing listening environments.

Purpose This study investigated (a) the effect of amplification on cortical auditory evoked potentials (CAEPs) at different signal levels when signal-to-noise ratios (SNRs) were equated between unaided and aided conditions, and (b) the effect of absolute signal level on aided CAEPs when SNR was held constant. Method CAEPs were recorded from 13 young adults with normal hearing. A 1000-Hz pure tone was presented in unaided and aided conditions with a linear analog hearing aid. Direct audio input was used, allowing recorded hearing aid noise floor to be added to unaided conditions to equate SNRs between conditions. An additional stimulus was created through scaling the noise floor to study the effect of signal level. Results Amplification resulted in delayed N1 and P2 peak latencies relative to the unaided condition. An effect of absolute signal level (when SNR was constant) was present for aided CAEP area measures, such that larger area measures were found at higher levels. Conclusion Results of this study further demonstrate that factors in addition to SNR must also be considered before CAEPs can be used to clinically to measure aided thresholds.

This study investigated how depth variations in the tip of the probe tube affected spectral measures of speech recorded in the external ear canal. Consonant-vowel nonsense syllables were recorded with a probe tube microphone system in 10 adult participants with normal middle ear function. Recordings were made with the probe tube tip placed 1 mm, 5 mm, and 10 mm beyond the medial tip of a custom earmold. The effect of probe depth was evaluated on spectral levels (one-third octave and one-twelfth octave band). Extending the probe tube 10 mm past the medial tip of the earmold gave the most accurate results, with relatively lower sound levels for either the 1-mm or 5-mm insertion depth. In general, the effect of insertion depth was minimal at frequencies below 3 to 4 kHz, although this varied with the specific phoneme and the width of the analysis bands. The authors found no significant difference between 1- and 5-mm insertion depths, suggesting that as long as the tip of the probe tube is sufficiently close to the tympanic membrane to capture the highest frequency of interest, it makes little difference if it is less than 5 mm beyond the earmold tip.

Hearing aids help compensate for disorders of the ear by amplifying sound; however, their effectiveness also depends on the central auditory system's ability to represent and integrate spectral and temporal information delivered by the hearing aid. The authors report that the neural detection of time-varying acoustic cues contained in speech can be recorded in adult hearing aid users using the acoustic change complex (ACC). Seven adults (50–76 years) with mild to severe sensorineural hearing participated in the study. When presented with 2 identifiable consonant-vowel (CV) syllables (“shee” and “see”), the neural detection of CV transitions (as indicated by the presence of a P1-N1-P2 response) was different for each speech sound. More specifically, the latency of the evoked neural response coincided in time with the onset of the vowel, similar to the latency patterns the authors previously reported in normal-hearing listeners.

Despite much research focusing on hearing aid and cochlearimplant devices, their engineering, and how they might be modified toensurebetteruse,researchstillcannotfullyexplainwhytwoindividualswiththe same configuration of hearing loss demonstrate significantly differentimprovements in speech understanding with similar hearing devices. Onepotential source of performance variability might be the central auditorysystem. Here we review the use of speech-evoked cortical potentials toinvestigate issues of performance variability and auditory rehabilitation.Specifically addressed are issues pertaining to the neural detection of time-varying speech cues, auditory training, and aging. KEYWORDS: Auditory evoked potentials, neural plasticity, hearing aidacclimatization, cochlear implants, auditory training, auditoryrehabilitation Learning Outcomes: As a result of this activity, the reader will be able to (1) describe how hearing involves bothperipheral and central mechanisms and that hearing loss (as well as the reintroduction of sound) alters centralauditory function, and (2) explain that the aforementioned experience-related biological changes probablycontribute to a person’s ability to make use of a hearing aid or cochlear implant.

A recurring problem in aging research is separating the effects of age per se from the effects of high-frequency hearing loss. One approach is to present test stimuli in the presence of a high-pass masker to control confounding differences in high-frequency audibility across age groups. However, there is evidence that such maskers may affect older and younger listeners differently. In this study, pure-tone thresholds were measured for younger and older listeners in the presence of high-pass maskers. The age groups were carefully selected based on similar unmasked thresholds at each frequency. Thresholds were measured in quiet and in seven masker conditions. Both younger and older listeners showed increased threshold shift below the masker passband as the masker level increased. The degree of threshold shift was not greater for older versus younger listeners. Results suggest that high-pass maskers may be used to reduce high-frequency sensitivity differences between younger and older listeners without introducing differential masking effects.

Objective : To examine the effects of aging and age-related hearing loss on the perception and neural representation of a time-varying speech cue. Methods : P1, N1 and P2 cortical responses were recorded from younger and older normal-hearing adults, as well as older adults with age-related hearing loss. Synthetic speech tokens representing 10 ms increments along a /ba/–/pa/ voice-onset-time (VOT) continuum were used to evoke the responses. Each participant's ability to discriminate the speech tokens was also assessed. Results : Compared with younger participants, older adults with and without hearing loss had more difficulty discriminating 10 ms VOT contrasts. In addition, both older groups elicited abnormal neural response patterns. There were no significant age-related findings for P1 latency; however, N1 latencies were prolonged for both older groups in response to stimuli with increased VOT durations. Also, P2 latencies were delayed for both older groups. The presence of age-related hearing loss resulted in a significant increase in N1 amplitude in response to voiceless stimuli. Conclusions : Aging and age-related hearing loss alter temporal response properties in the central auditory system. Because both older groups had difficulty discriminating these same speech stimuli, we conclude that some of the perceptual difficulties described by older adults might be due to age-related changes regulating excitatory and inhibitory processes. Significance : Some of the speech understanding difficulties expressed by elderly adults may be related to impaired temporal precision in the aging auditory system. This might explain why older adults frequently complain that wearing a hearing aid makes speech louder, but does not necessarily improve their ability to understand speech.

Age-related deficits in speech understanding are well documented. Because speech is a complex signal, containing time-varying acoustic cues, it is frequently hypothesized that aging adversely affects the ability to process temporal cues. This study examined the neural representation and perception of voice-onset-time, a temporal cue that distinguishes voiced /b/ from voiceless /p/ sounds. We found that older adults had more difficulty than younger listeners discriminating voice-onset contrasts. In addition, these same speech stimuli evoked abnormal neural responses in older adults. That is, compared with younger listeners, N1 and P2 long-latency auditory evoked responses were prolonged for older adults. Collectively, these results suggest speech perception difficulties described by older adults may be related to age-related changes regulating excitatory and inhibitory processes.

Physiological correlates of speech acoustics are particularly important to study in humans because it is uncertain whether animals process speech the same way humans do. Studying the physiology of speech processing in humans, however, typically requires the use of noninvasive physiological measures. This is what we attempted in a recent study (Won, Tremblay, Clinard, Wright, Sagi, and Svirsky, JASA 2016) which examined the hypothesis that neural representations of formant frequencies may help predict vowel recognition. To test the hypothesis, the frequency-following response (FFR) and vowel recognition were obtained from 38 normal-hearing listeners using four different vowels. This allowed direct comparisons between behavioral and neural data in the same individuals. FFR was used because it reflects temporal encoding of formant frequencies below about 1500 Hz. Four synthetic vowels with formant frequencies below 1500 Hz were used. Duration was 70 ms for all vowels to eliminate temporal cues and to make id...

A significant issue in the use of the mismatch negativity evoked potential (MMN) concerns its low signal-to-noise ratio (SNR). One can improve the noise level by increasing the number of samples included in the averaged response. However, improvement achieved in this way assumes that the signal, the MMN, remains stable for extended test times, an assumption which has not been tested. If the MMN is not stable, or exhibits habituation over the test session, then SNR would be adversely affected. MMN response magnitude was measured in 5-min intervals over the course of a test session in response to various speech syllable contrasts. Significant long-term habituation of MMN was observed for all three subject populations tested: young adults, school-age children, and guinea pigs. The time course of the habituation and the stimulus conditions under which it occurs have important implications for research and clinical applications of the MMN. Recording procedures that minimize habituation effects may be used to advantage to improve the signal-to-noise ratio of the MMN.

Experience-related changes in central nervous system (CNS) activity have been observed in the adult brain of many mammalian species, including humans. In humans, late-onset profound unilateral deafness creates an opportunity to study plasticity in the adult CNS consequent to monaural auditory deprivation. CNS activity was assessed by measuring long-latency auditory evoked potentials (AEPs) recorded from teens and adults with late-onset (post-childhood) profound unilateral deafness. Compared to monaurally stimulated normal-hearing subjects, the AEPs recorded from central electrode sites located over auditory cortical areas showed significant increases in inter-hemispheric waveform cross-correlation coefficients, and in inter-hemispheric AEP peak amplitude correlations. These increases provide evidence of substantial changes from the normal pattern of asymmetrical (contralateral > ipsilateral amplitude) and asynchronous (contralateral earlier than ipsilateral) central auditory system activation in the normal-hearing population to a much more symmetrical and synchronous activation in the unilaterally deaf. These cross-sectional analyses of AEP data recorded from the unilaterally deaf also suggest that the changes in cortical activity occur gradually and continue for at least 2 years after the onset of hearing loss. Analyses of peak amplitude correlations suggest that the increased inter-hemispheric symmetry may be a consequence of changes in the generators producing the N (approximately 100 ms peak latency) potential. These experience-related changes in central auditory system activity following late-onset profound unilateral deafness thus provide evidence of the presence and the time course of auditory system plasticity in the adult brain.

To determine whether the N1-P2 complex reflects training-induced changes in neural activity associated with improved voice-onset-time (VOT) perception.Auditory cortical evoked potentials N1 and P2 were obtained from 10 normal-hearing young adults in response to two synthetic speech variants of the syllable /ba/. Using a repeated measures design, subjects were tested before and after training both behaviorally and neurophysiologically to determine whether there were training-related changes. In between pre- and post-testing sessions, subjects were trained to distinguish the -20 and -10 msec VOT /ba/ syllables as being different from each other. Two stimulus presentation rates were used during electrophysiologic testing (390 msec and 910 msec interstimulus interval).Before training, subjects perceived both the -20 msec and -10 msec VOT stimuli as /ba/. Through training, subjects learned to identify the -20 msec VOT stimulus as "mba" and -10 msec VOT stimulus as "ba." As subjects learned to correctly identify the difference between the -20 msec and -10 msec VOT syllabi, an increase in N1-P2 peak-to-peak amplitude was observed. The effects of training were most obvious at the slower stimulus presentation rate.As perception improved, N1-P2 amplitude increased. These changes in waveform morphology are thought to reflect increases in neural synchrony as well as strengthened neural connections associated with improved speech perception. These findings suggest that the N1-P2 complex may have clinical applications as an objective physiologic correlate of speech-sound representation associated with speech-sound training.

Here we report that training-associated changes in neural activity can precede behavioral learning. This finding suggests that speech-sound learning occurs at a pre-attentive level which can be measured neurophysiologically (in the absence of a behavioral response) to assess the efficacy of training. Children with biologically based perceptual learning deficits as well as people who wear cochlear implants or hearing aids undergo various forms of auditory training. The effectiveness of auditory training can be difficult to assess using behavioral methods because these populations are communicatively impaired and may have attention and/or cognitive deficits. Based on our findings, if neurophysiological changes are seen during auditory training, then the training method is effectively altering the neural representation of the speech/sounds and changes in behavior are likely to follow.

Hearing aids are used to improve sound audibility for people with hearing loss, but the ability to make use of the amplified signal, especially in the presence of competing noise, can vary across people. Here we review how neuroscientists, clinicians, and engineers are using various types of physiological information to improve the design and use of hearing aids.

Behavioral perceptual abilities and neurophysiologic changes observed after listening training can generalize to other stimuli not used in the training paradigm, thereby demonstrating behavioral "transfer of learning" and plasticity in underlying physiologic processes. Nine normal-hearing monolingual English-speaking adults were trained to identify a prevoiced labial stop sound (one that is not used phonemically in the English language). After training, the subjects were asked to discriminate and identify a prevoiced alveolar stop. Mismatch negativity cortical evoked responses (MMN) were recorded to both labial and alveolar stimuli before and after training. Behavioral performance and MMNs also were evaluated in an age-matched control group that did not receive training. Listening training improved the experimental group's ability to discriminate and identify an unfamiliar VOT contrast. That enhanced ability transferred from one place of articulation (labial) to another (alveolar). The behavioral training effects were reflected in the MMN, which showed an increase in duration and area when elicited by the training stimuli as well as a decrease in onset latency when elicited by the transfer stimuli. Interestingly, changes in the MMN were largest over the left hemisphere. The results demonstrate that training can generalize to listening situations beyond those used in training sessions, and that the preattentive central neurophysiology underlying perceptual learning are altered through auditory training.

At the heart of most rehabilitation programs for people with hearing loss is the use of amplification. The purpose of hearing aid amplification is to improve a person's access to sound. Depending on the degree and configuration of the individual's hearing loss, the hearing aid is tasked with increasing sound levels at different frequency regions to ensure that incoming speech frequencies are reaching the ear at sufficient levels to compensate for the individual's hearing loss. However, a perceptual event is dependent not only on the audibility of the signal at the level of the ear, but also on how that sound is biologically coded, integrated, and used. As described by Tremblay and Miller in this special issue, this complex ear-brain neural network system starts with sound leaving the hearing aid. At this stage the acoustics of the amplified signal has been altered by the hearing aid. It is this modified signal that is being encoded at subsequent stages of processing: the ear, brainstem, midbrain, and the cortex. The integrity of the signal, and the biological codes, are therefore assumed to contribute to the resultant perceptual event and it is for this reason that the brain can be considered an essential component to rehabilitation. Yet, little is known about how the brain processes amplified sound or how it contributes to perception and the successful use of hearing aid amplification (see Figure 1).

A passively elicited cortical potential that reflects the brain's discrimination of small acoustic contrasts was measured in response to two slightly different speech stimuli in adult human subjects. Behavioral training in the discrimination of those speech stimuli resulted in a significant change in the duration and magnitude of the cortical potential. The results demonstrate that listening training can change the neurophysiologic responses of the central auditory system to just-perceptible differences in speech.