Functional changes in inter- and intra-hemispheric cortical processing underlying degraded speech perception

Spatial Hearing in Children With and Without Hearing Loss: Where and What the Speech Is Matters for Local Speech Intelligibility

PURPOSE

This study examined children's ability to perceive speech from multiple locations on the horizontal plane. Children with hearing loss were compared to normal-hearing peers while using amplification with and without advanced noise management.

METHOD

Participants were 21 children with normal hearing (9-15 years) and 12 children with moderate symmetrical hearing loss (11-15 years). Word recognition, nonword detection, and word recall were assessed. Stimuli were presented randomly from multiple discrete locations in multitalker noise. Children with hearing loss were fit with devices having separate omnidirectional and noise management programs. The noise management feature is designed to preserve audibility in noise by rapidly analyzing input from all locations and reducing the noise management when speech is detected from locations around the hearing aid user.

RESULTS

Significant effects of left/right and front/back lateralization occurred as well as effects of hearing loss and hearing aid noise management. Children with normal hearing experienced a left-side advantage for word recognition and a right-side advantage for nonword detection. Children with hearing loss demonstrated poorer performance overall on all tasks with better word recognition from the back, and word recall from the right, in the omnidirectional condition. With noise management, performance improved from the front compared to the back for all three tasks and from the right for word recognition and word recall.

CONCLUSIONS

The shape of children's local speech intelligibility on the horizontal plane is not omnidirectional. It is task dependent and shaped further by hearing loss and hearing aid signal processing. Front/back shifts in children with hearing loss are consistent with the behavior of hearing aid noise management, while the right-side biases observed in both groups are consistent with the effects of specialized speech processing in the left hemisphere of the brain.

Functional benefits of continuous vs. categorical listening strategies on the neural encoding and perception of noise-degraded speech

Acoustic information in speech changes continuously, yet listeners form discrete perceptual categories to ease the demands of perception. Being a more continuous/gradient as opposed to a discrete/categorical listener may be further advantageous for understanding speech in noise by increasing perceptual flexibility and resolving ambiguity. The degree to which a listener's responses to a continuum of speech sounds are categorical versus continuous can be quantified using visual analog scaling (VAS) during speech labeling tasks. Here, we recorded event-related brain potentials (ERPs) to vowels along an acoustic-phonetic continuum (/u/ to /a/) while listeners categorized phonemes in both clean and noise conditions. Behavior was assessed using standard two alternative forced choice (2AFC) and VAS paradigms to evaluate categorization under task structures that promote discrete (2AFC) vs. continuous (VAS) hearing, respectively. Behaviorally, identification curves were steeper under 2AFC vs. VAS categorization but were relatively immune to noise, suggesting robust access to abstract, phonetic categories even under signal degradation. Behavioral slopes were positively correlated with listeners' QuickSIN scores, suggesting a behavioral advantage for speech in noise comprehension conferred by gradient listening strategy. At the neural level, electrode level data revealed P2 peak amplitudes of the ERPs were modulated by task and noise; responses were larger under VAS vs. 2AFC categorization and showed larger noise-related delay in latency in the VAS vs. 2AFC condition. More gradient responders also had smaller shifts in ERP latency with noise, suggesting their neural encoding of speech was more resilient to noise degradation. Interestingly, source-resolved ERPs showed that more gradient listening was also correlated with stronger neural responses in left superior temporal gyrus. Our results demonstrate that listening strategy (i.e., being a discrete vs. continuous listener) modulates the categorical organization of speech and behavioral success, with continuous/gradient listening being more advantageous to speech in noise perception.

Two are better than one: Differences in cortical EEG patterns during auditory and visual verbal working memory processing between Unilateral and Bilateral Cochlear Implanted children

Despite the proven effectiveness of cochlear implant (CI) in the hearing restoration of deaf or hard-of-hearing (DHH) children, to date, extreme variability in verbal working memory (VWM) abilities is observed in both unilateral and bilateral CI user children (CIs). Although clinical experience has long observed deficits in this fundamental executive function in CIs, the cause to date is still unknown. Here, we have set out to investigate differences in brain functioning regarding the impact of monaural and binaural listening in CIs compared with normal hearing (NH) peers during a three-level difficulty n-back task undertaken in two sensory modalities (auditory and visual). The objective of this pioneering study was to identify electroencephalographic (EEG) marker pattern differences in visual and auditory VWM performances in CIs compared to NH peers and possible differences between unilateral cochlear implant (UCI) and bilateral cochlear implant (BCI) users. The main results revealed differences in theta and gamma EEG bands. Compared with hearing controls and BCIs, UCIs showed hypoactivation of theta in the frontal area during the most complex condition of the auditory task and a correlation of the same activation with VWM performance. Hypoactivation in theta was also observed, again for UCIs, in the left hemisphere when compared to BCIs and in the gamma band in UCIs compared to both BCIs and NHs. For the latter two, a correlation was found between left hemispheric gamma oscillation and performance in the audio task. These findings, discussed in the light of recent research, suggest that unilateral CI is deficient in supporting auditory VWM in DHH. At the same time, bilateral CI would allow the DHH child to approach the VWM benchmark for NH children. The present study suggests the possible effectiveness of EEG in supporting, through a targeted approach, the diagnosis and rehabilitation of VWM in DHH children.

Short- and long-term neuroplasticity interact during the perceptual learning of concurrent speech

Plasticity from auditory experience shapes the brain's encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ~ 45 min training sessions recorded simultaneously with high-density electroencephalography (EEG). We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. Although both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200 ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings reinforce the domain-general benefits of musicianship but reveal that successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity, which first emerge at a cortical level.

Categorical perception of lexical tones in Chinese people with post-stroke aphasia

This study used the categorical perception (CP) paradigm, a fine-grained perceptual method, to investigate the perceptual performance of lexical tones in Chinese people with post-stroke aphasia (PWA). Twenty patients with post-stroke aphasia (10 Broca's and 10 Wernicke's) and ten neurologically intact age-matched control participants were recruited to complete both identification and discrimination tasks of the Mandarin Tone 1-2 continuum. In addition, all participants completed tests on their auditory comprehension ability and working memory. The results showed that both Broca's and Wernicke's patients exhibited reduced sensitivity to within-category and between-category information but preserved CP of lexical tones. The degree of CP of lexical tones related to working memory in aphasic patients. Furthermore, lower-level acoustic processing underpinned higher-level phonological processing on the CP of lexical tones since both patient groups' unbalanced pitch processing ability extended to their CP of lexical tones. These findings are significant for researchers and clinicians in speech-language rehabilitation, clinical psychology, and cognitive communication.

Leading and following: Noise differently affects semantic and acoustic processing during naturalistic speech comprehension

Despite the distortion of speech signals caused by unavoidable noise in daily life, our ability to comprehend speech in noisy environments is relatively stable. However, the neural mechanisms underlying reliable speech-in-noise comprehension remain to be elucidated. The present study investigated the neural tracking of acoustic and semantic speech information during noisy naturalistic speech comprehension. Participants listened to narrative audio recordings mixed with spectrally matched stationary noise at three signal-to-ratio (SNR) levels (no noise, 3 dB, -3 dB), and 60-channel electroencephalography (EEG) signals were recorded. A temporal response function (TRF) method was employed to derive event-related-like responses to the continuous speech stream at both the acoustic and the semantic levels. Whereas the amplitude envelope of the naturalistic speech was taken as the acoustic feature, word entropy and word surprisal were extracted via the natural language processing method as two semantic features. Theta-band frontocentral TRF responses to the acoustic feature were observed at around 400 ms following speech fluctuation onset over all three SNR levels, and the response latencies were more delayed with increasing noise. Delta-band frontal TRF responses to the semantic feature of word entropy were observed at around 200 to 600 ms leading to speech fluctuation onset over all three SNR levels. The response latencies became more leading with increasing noise and decreasing speech comprehension and intelligibility. While the following responses to speech acoustics were consistent with previous studies, our study revealed the robustness of leading responses to speech semantics, which suggests a possible predictive mechanism at the semantic level for maintaining reliable speech comprehension in noisy environments.

Comprehension of acoustically degraded speech in Alzheimer's disease and primary progressive aphasia

Successful communication in daily life depends on accurate decoding of speech signals that are acoustically degraded by challenging listening conditions. This process presents the brain with a demanding computational task that is vulnerable to neurodegenerative pathologies. However, despite recent intense interest in the link between hearing impairment and dementia, comprehension of acoustically degraded speech in these diseases has been little studied. Here we addressed this issue in a cohort of 19 patients with typical Alzheimer's disease and 30 patients representing the three canonical syndromes of primary progressive aphasia (non-fluent/agrammatic variant primary progressive aphasia; semantic variant primary progressive aphasia; logopenic variant primary progressive aphasia), compared to 25 healthy age-matched controls. As a paradigm for the acoustically degraded speech signals of daily life, we used noise-vocoding: synthetic division of the speech signal into frequency channels constituted from amplitude-modulated white noise, such that fewer channels convey less spectrotemporal detail thereby reducing intelligibility. We investigated the impact of noise-vocoding on recognition of spoken three-digit numbers and used psychometric modelling to ascertain the threshold number of noise-vocoding channels required for 50% intelligibility by each participant. Associations of noise-vocoded speech intelligibility threshold with general demographic, clinical and neuropsychological characteristics and regional grey matter volume (defined by voxel-based morphometry of patients' brain images) were also assessed. Mean noise-vocoded speech intelligibility threshold was significantly higher in all patient groups than healthy controls, and significantly higher in Alzheimer's disease and logopenic variant primary progressive aphasia than semantic variant primary progressive aphasia (all P < 0.05). In a receiver operating characteristic analysis, vocoded intelligibility threshold discriminated Alzheimer's disease, non-fluent variant and logopenic variant primary progressive aphasia patients very well from healthy controls. Further, this central hearing measure correlated with overall disease severity but not with peripheral hearing or clear speech perception. Neuroanatomically, after correcting for multiple voxel-wise comparisons in predefined regions of interest, impaired noise-vocoded speech comprehension across syndromes was significantly associated (P < 0.05) with atrophy of left planum temporale, angular gyrus and anterior cingulate gyrus: a cortical network that has previously been widely implicated in processing degraded speech signals. Our findings suggest that the comprehension of acoustically altered speech captures an auditory brain process relevant to daily hearing and communication in major dementia syndromes, with novel diagnostic and therapeutic implications.

Explainable machine learning reveals the relationship between hearing thresholds and speech-in-noise recognition in listeners with normal audiograms

Some individuals complain of listening-in-noise difficulty despite having a normal audiogram. In this study, machine learning is applied to examine the extent to which hearing thresholds can predict speech-in-noise recognition among normal-hearing individuals. The specific goals were to (1) compare the performance of one standard (GAM, generalized additive model) and four machine learning models (ANN, artificial neural network; DNN, deep neural network; RF, random forest; XGBoost; eXtreme gradient boosting), and (2) examine the relative contribution of individual audiometric frequencies and demographic variables in predicting speech-in-noise recognition. Archival data included thresholds (0.25-16 kHz) and speech recognition thresholds (SRTs) from listeners with clinically normal audiograms (n = 764 participants or 1528 ears; age, 4-38 years old). Among the machine learning models, XGBoost performed significantly better than other methods (mean absolute error; MAE = 1.62 dB). ANN and RF yielded similar performances (MAE = 1.68 and 1.67 dB, respectively), whereas, surprisingly, DNN showed relatively poorer performance (MAE = 1.94 dB). The MAE for GAM was 1.61 dB. SHapley Additive exPlanations revealed that age, thresholds at 16 kHz, 12.5 kHz, etc., on the order of importance, contributed to SRT. These results suggest the importance of hearing in the extended high frequencies for predicting speech-in-noise recognition in listeners with normal audiograms.

Short- and long-term experience-dependent neuroplasticity interact during the perceptual learning of concurrent speech

Plasticity from auditory experiences shapes brain encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ∼45 minute training sessions recorded simultaneously with high-density EEG. We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. While both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200 ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings confirm domain-general benefits for musicianship but reveal successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity that first emerge at a cortical level.

The effect of noise on the cortical activity patterns of speech processing in adults with single-sided deafness

The most common complaint in people with single-sided deafness (SSD) is difficulty in understanding speech in a noisy environment. Moreover, the neural mechanism of speech-in-noise (SiN) perception in SSD individuals is still poorly understood. In this study, we measured the cortical activity in SSD participants during a SiN task to compare with a speech-in-quiet (SiQ) task. Dipole source analysis revealed left hemispheric dominance in both left- and right-sided SSD group. Contrary to SiN listening, this hemispheric difference was not found during SiQ listening in either group. In addition, cortical activation in the right-sided SSD individuals was independent of the location of sound whereas activation sites in the left-sided SSD group were altered by the sound location. Examining the neural-behavioral relationship revealed that N1 activation is associated with the duration of deafness and the SiN perception ability of individuals with SSD. Our findings indicate that SiN listening is processed differently in the brains of left and right SSD individuals.

Left Lateralization of the Cortical Auditory-Evoked Potential Reflects Aided Processing and Speech-in-Noise Performance of Older Listeners With a Hearing Loss

OBJECTIVES

We analyzed the lateralization of the cortical auditory-evoked potential recorded previously from aided hearing-impaired listeners as part of a study on noise-mitigating hearing aid technologies. Specifically, we asked whether the degree of leftward lateralization in the magnitudes and latencies of these components was reduced by noise and, conversely, enhanced/restored by hearing aid technology. We further explored if individual differences in lateralization could predict speech-in-noise abilities in listeners when tested in the aided mode.

DESIGN

The study followed a double-blind within-subjects design. Nineteen older adults (8 females; mean age = 73.6 years, range = 56 to 86 years) with moderate to severe hearing loss participated. The cortical auditory-evoked potential was measured over 400 presentations of a synthetic /da/ stimulus which was delivered binaurally in a simulated aided mode using shielded ear-insert transducers. Sequences of the /da/ syllable were presented from the front at 75 dB SPL-C with continuous speech-shaped noise presented from the back at signal-to-noise ratios of 0, 5, and 10 dB. Four hearing aid conditions were tested: (1) omnidirectional microphone (OM) with noise reduction (NR) disabled, (2) OM with NR enabled, (3) directional microphone (DM) with NR disabled, and (4) DM with NR enabled. Lateralization of the P1 component and N1P2 complex was quantified across electrodes spanning the mid-coronal plane. Subsequently, listener speech-in-noise performance was assessed using the Repeat-Recall Test at the same signal-to-noise ratios and hearing aid conditions used to measure cortical activity.

RESULTS

As expected, both the P1 component and the N1P2 complex were of greater magnitude in electrodes over the left compared to the right hemisphere. In addition, N1 and P2 peaks tended to occur earlier over the left hemisphere, although the effect was mediated by an interaction of signal-to-noise ratio and hearing aid technology. At a group level, degrees of lateralization for the P1 component and the N1P2 complex were enhanced in the DM relative to the OM mode. Moreover, linear mixed-effects models suggested that the degree of leftward lateralization in the N1P2 complex, but not the P1 component, accounted for a significant portion of variability in speech-in-noise performance that was not related to age, hearing loss, hearing aid processing, or signal-to-noise ratio.

CONCLUSIONS

A robust leftward lateralization of cortical potentials was observed in older listeners when tested in the aided mode. Moreover, the degree of lateralization was enhanced by hearing aid technologies that improve the signal-to-noise ratio for speech. Accounting for the effects of signal-to-noise ratio, hearing aid technology, semantic context, and audiometric thresholds, individual differences in left-lateralized speech-evoked cortical activity were found to predict listeners' speech-in-noise abilities. Quantifying cortical auditory-evoked potential component lateralization may then be useful for profiling listeners' likelihood of communication success following clinical amplification.

Continuous dynamics in behavior reveal interactions between perceptual warping in categorization and speech-in-noise perception

Introduction

Spoken language comprehension requires listeners map continuous features of the speech signal to discrete category labels. Categories are however malleable to surrounding context and stimulus precedence; listeners' percept can dynamically shift depending on the sequencing of adjacent stimuli resulting in a warping of the heard phonetic category. Here, we investigated whether such perceptual warping-which amplify categorical hearing-might alter speech processing in noise-degraded listening scenarios.

Methods

We measured continuous dynamics in perception and category judgments of an acoustic-phonetic vowel gradient via mouse tracking. Tokens were presented in serial vs. random orders to induce more/less perceptual warping while listeners categorized continua in clean and noise conditions.

Results

Listeners' responses were faster and their mouse trajectories closer to the ultimate behavioral selection (marked visually on the screen) in serial vs. random order, suggesting increased perceptual attraction to category exemplars. Interestingly, order effects emerged earlier and persisted later in the trial time course when categorizing speech in noise.

Discussion

These data describe interactions between perceptual warping in categorization and speech-in-noise perception: warping strengthens the behavioral attraction to relevant speech categories, making listeners more decisive (though not necessarily more accurate) in their decisions of both clean and noise-degraded speech.

Different neuroanatomical correlates for temporal and spectral supra-threshold auditory tasks and speech in noise recognition in older adults with hearing impairment

Varying degrees of pure-tone hearing loss in older adults are differentially associated with cortical volume (CV) and thickness (CT) within and outside of the auditory pathway. This study addressed the question to what degree supra-threshold auditory performance (i.e., temporal compression and frequency selectivity) as well as speech in noise (SiN) recognition are associated with neurostructural correlates in a sample of 59 healthy older adults with mild to moderate pure-tone hearing loss. Using surface-based morphometry on T1-weighted MRI images, CT, CV, and surface area (CSA) of several regions-of-interest were obtained. The results showed distinct neurostructural patterns for the different tasks in terms of involved regions as well as morphometric parameters. While pure-tone averages (PTAs) positively correlated with CT in a right hemisphere superior temporal sulcus and gyrus cluster, supra-threshold auditory perception additionally extended significantly to CV and CT in left and right superior temporal clusters including Heschl's gyrus and sulcus, the planum polare and temporale. For SiN recognition, we found significant correlations with an auditory-related CT cluster and furthermore with language-related areas in the prefrontal cortex. Taken together, our results show that different auditory abilities are differently associated with cortical morphology in older adults with hearing impairment. Still, a common pattern is that greater PTAs and poorer supra-threshold auditory performance as well as poorer SiN recognition are all related to cortical thinning and volume loss but not to changes in CSA. These results support the hypothesis that mostly CT undergoes alterations in the context of auditory decline, while CSA remains stable.

Modulation of auditory temporal processing, speech in noise perception, auditory-verbal memory, and reading efficiency by anodal tDCS in children with dyslexia

Dyslexia is a neurodevelopmental disorder that is prevalent in children. It is estimated that 30-50% of individuals diagnosed with dyslexia also manifest an auditory perceptual deficit characteristic of auditory processing disorder (APD). Some studies suggest that defects in basic auditory processing can lead to phonological defects as the most prominent cause of dyslexia. Thus, in some cases, there may be interrelationships between dyslexia and some of the aspects of central auditory processing. In recent years, transcranial direct current stimulation (tDCS) has been used as a safe method for the modulation of central auditory processing aspects in healthy adults and reading skills in children with dyslexia. Therefore, the objectives of our study were to investigate the effect of tDCS on the modulation of different aspects of central auditory processing, aspects of reading, and the relationship between these two domains in dyslexic children with APD. A within-subjects design was employed to investigate the effect of two electrode arrays (the anode on the left STG (AC)/cathode on the right shoulder and anode on the left STG/cathode on the right STG) on auditory temporal processing; speech-in-noise perception, short-term auditory memory; and high-frequency word, low-frequency word, pseudoword, and text reading. The results of this clinical trial showed the modulation of the studied variables in central auditory processing and the accuracy and speed of reading variables compared to the control and sham statuses in both electrode arrays. Our results also showed that the improvement of the accuracy and speed of text reading, as well as the accuracy of pseudoword reading were related to the improvement of speech in noise perception and temporal processing. The results of this research can be effective in clarifying the basis of the neurobiology of dyslexia and, in particular, the hypothesis of the role of basic auditory processing and subsequently the role of the auditory cortex in dyslexia. These results might provide a framework to facilitate behavioral rehabilitation in dyslexic children with APD.

Impact of Noise on Sound Processing at Lower Auditory System: An Electrophysiological Study

The importance of signal-to-noise ratio (SNR) is well documented in behavioral speech perception experiments and psychophysical measurements. Studies on ABR related to the encoding of signals in ipsilateral noise are very limited. The present study aimed to systematically investigate the effect of various SNRs on the latency and amplitude of ABR to a range of stimuli & to compare the latency and amplitude of ABR recorded in various ipsilateral SNRs in children and adults. We recorded auditory brain stem responses (ABR) in children and young adults for clicks, a speech token /da/ of 40 ms duration, and for a 1000 Hz tone burst in the presence of a broad band noise and quiet. There were four SNR conditions (+ 10 dB SNR, 0 dB SNR and -10 dB SNR), and the level of noise was varied, while the stimulus level was fixed at 60 dB HL. The results showed that SNR affects the latency and amplitude of the wave V peak differentially for the different stimuli. A difference in the performance of children and adults was also observed. SNR measurements using ABR provide an objective index of brainstem ability to process sound in the presence of background noise. This measure is important and can be used to assess the sound-in-noise processing ability in the difficult-to-test population such as infants and children where measures of signal-to-noise tests cannot be administered.

Familiarity of Background Music Modulates the Cortical Tracking of Target Speech at the "Cocktail Party"

The "cocktail party" problem-how a listener perceives speech in noisy environments-is typically studied using speech (multi-talker babble) or noise maskers. However, realistic cocktail party scenarios often include background music (e.g., coffee shops, concerts). Studies investigating music's effects on concurrent speech perception have predominantly used highly controlled synthetic music or shaped noise, which do not reflect naturalistic listening environments. Behaviorally, familiar background music and songs with vocals/lyrics inhibit concurrent speech recognition. Here, we investigated the neural bases of these effects. While recording multichannel EEG, participants listened to an audiobook while popular songs (or silence) played in the background at a 0 dB signal-to-noise ratio. Songs were either familiar or unfamiliar to listeners and featured either vocals or isolated instrumentals from the original audio recordings. Comprehension questions probed task engagement. We used temporal response functions (TRFs) to isolate cortical tracking to the target speech envelope and analyzed neural responses around 100 ms (i.e., auditory N1 wave). We found that speech comprehension was, expectedly, impaired during background music compared to silence. Target speech tracking was further hindered by the presence of vocals. When masked by familiar music, response latencies to speech were less susceptible to informational masking, suggesting concurrent neural tracking of speech was easier during music known to the listener. These differential effects of music familiarity were further exacerbated in listeners with less musical ability. Our neuroimaging results and their dependence on listening skills are consistent with early attentional-gain mechanisms where familiar music is easier to tune out (listeners already know the song's expectancies) and thus can allocate fewer attentional resources to the background music to better monitor concurrent speech material.

Prediction of Speech Intelligibility by Means of EEG Responses to Sentences in Noise

Objective

Understanding speech in noisy conditions is challenging even for people with mild hearing loss, and intelligibility for an individual person is usually evaluated by using several subjective test methods. In the last few years, a method has been developed to determine a temporal response function (TRF) between speech envelope and simultaneous electroencephalographic (EEG) measurements. By using this TRF it is possible to predict the EEG signal for any speech signal. Recent studies have suggested that the accuracy of this prediction varies with the level of noise added to the speech signal and can predict objectively the individual speech intelligibility. Here we assess the variations of the TRF itself when it is calculated for measurements with different signal-to-noise ratios and apply these variations to predict speech intelligibility.

Methods

For 18 normal hearing subjects the individual threshold of 50% speech intelligibility was determined by using a speech in noise test. Additionally, subjects listened passively to speech material of the speech in noise test at different signal-to-noise ratios close to individual threshold of 50% speech intelligibility while an EEG was recorded. Afterwards the shape of TRFs for each signal-to-noise ratio and subject were compared with the derived intelligibility.

Results

The strongest effect of variations in stimulus signal-to-noise ratio on the TRF shape occurred close to 100 ms after the stimulus presentation, and was located in the left central scalp region. The investigated variations in TRF morphology showed a strong correlation with speech intelligibility, and we were able to predict the individual threshold of 50% speech intelligibility with a mean deviation of less then 1.5 dB.

Conclusion

The intelligibility of speech in noise can be predicted by analyzing the shape of the TRF derived from different stimulus signal-to-noise ratios. Because TRFs are interpretable, in a manner similar to auditory evoked potentials, this method offers new options for clinical diagnostics.

Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Different studies have suggested that during speech processing readers with dyslexia present atypical levels of neural entrainment as well as atypical functional hemispherical asymmetries in comparison with typical readers. In this study, we evaluated these differences in children and the variation with age before and after starting with formal reading instruction. Synchronized neural auditory processing activity was quantified based on auditory steady-state responses (ASSRs) from EEG recordings. The stimulation was modulated at syllabic and phonemic fluctuation rates present in speech. We measured the brain activation patterns and the hemispherical asymmetries in children at three age points (5, 7, and 9 years old). Despite the well-known heterogeneity during developmental stages, especially in children and in dyslexia, we could extract meaningful common oscillatory patterns. The analyses included (1) the estimations of source localization, (2) hemispherical preferences using a laterality index, measures of neural entrainment, (3) signal-to-noise ratios (SNRs), and (4) connectivity using phase coherence measures. In this longitudinal study, we confirmed that the existence of atypical levels of neural entrainment and connectivity already exists at pre-reading stages. Overall, these measures reflected a lower ability of the dyslectic brain to synchronize with syllabic rate stimulation. In addition, our findings reinforced the hypothesis of a later maturation of the processing of beta rhythms in dyslexia. This investigation emphasizes the importance of longitudinal studies in dyslexia, especially in children, where neural oscillatory patterns as well as differences between typical and atypical developing children can vary in the span of a year.

Ear Asymmetry and Contextual Influences on Speech Perception in Hearing-Impaired Patients

The left hemisphere preference for verbal stimuli is well known, with a right ear (RE) advantage obtained when competing verbal stimuli are presented simultaneously, at comfortable intensities, to both ears. Speech perception involves not only the processing of acoustic peripheral information but also top–down contextual influences, filling the gaps in the incoming information that is particularly degraded in hearing-impaired individuals. This study aimed to analyze the potential asymmetry of those contextual influences on a simple speech perception task in hearing-impaired patients in light of hemispheric asymmetry. Contextual influences on disyllabic word perception scores of 60 hearing-impaired patients were compared between left ear (LE) and RE, in a balanced design, involving two repetitions of the same task. Results showed a significantly greater contextual influence on the RE versus the LE and, for the second repetition versus the first one, without any interaction between the two. Furthermore, the difference in contextual influences between RE and LE increased significantly with the RE advantage measured by a dichotic listening test in the absence of any significant correlation with hearing threshold asymmetry. Lastly, the contextual influence asymmetry decreased significantly as age increased, which was mainly due to a greater increase, with age, of contextual influences on the LE versus the RE. Those results agree with the literature reporting a relative right-shift of hemispheric asymmetry observed with age in speech in noise perception tasks in normal hearing subjects and the clinical reports of generally better audiometric speech scores obtained in RE versus LE.

Atypical processing in neural source analysis of speech envelope modulations in adolescents with dyslexia

Different studies have suggested that language and developmental disorders such as dyslexia are associated with a disturbance of auditory entrainment and of the functional hemispheric asymmetries during speech processing. These disorders typically result from an issue in the phonological component of language that causes problems to represent and manipulate the phonological structure of words at the syllable and/or phoneme level. We used Auditory Steady-State Responses (ASSRs) in EEG recordings to investigate the brain activation and hemisphere asymmetry of theta, alpha, beta and low-gamma range oscillations in typical readers and readers with dyslexia. The aim was to analyse whether the group differences found in previous electrode level studies were caused by a different source activation pattern or conversely was an effect that could be found on the active brain sources. We could not find differences in the brain locations of the main active brain sources. However, we observed differences in the extracted waveforms. The group average of the first DSS component of all signal-to-noise ratios of ASSR at source level was higher than the group averages at the electrode level. These analyses included a lower alpha synchronisation in adolescents with dyslexia and the possibility of compensatory mechanisms in theta, beta and low-gamma frequency bands. The main brain auditory sources were located in cortical regions around the auditory cortex. Thus, the differences observed in auditory EEG experiments would, according to our findings, have their origin in the intrinsic oscillatory mechanisms of the brain cortical sources related to speech perception.

Reduced Semantic Context and Signal-to-Noise Ratio Increase Listening Effort As Measured Using Functional Near-Infrared Spectroscopy

OBJECTIVES

Understanding speech-in-noise can be highly effortful. Decreasing the signal-to-noise ratio (SNR) of speech increases listening effort, but it is relatively unclear if decreasing the level of semantic context does as well. The current study used functional near-infrared spectroscopy to evaluate two primary hypotheses: (1) listening effort (operationalized as oxygenation of the left lateral PFC) increases as the SNR decreases and (2) listening effort increases as context decreases.

DESIGN

Twenty-eight younger adults with normal hearing completed the Revised Speech Perception in Noise Test, in which they listened to sentences and reported the final word. These sentences either had an easy SNR (+4 dB) or a hard SNR (-2 dB), and were either low in semantic context (e.g., "Tom could have thought about the sport") or high in context (e.g., "She had to vacuum the rug"). PFC oxygenation was measured throughout using functional near-infrared spectroscopy.

RESULTS

Accuracy on the Revised Speech Perception in Noise Test was worse when the SNR was hard than when it was easy, and worse for sentences low in semantic context than high in context. Similarly, oxygenation across the entire PFC (including the left lateral PFC) was greater when the SNR was hard, and left lateral PFC oxygenation was greater when context was low.

CONCLUSIONS

These results suggest that activation of the left lateral PFC (interpreted here as reflecting listening effort) increases to compensate for acoustic and linguistic challenges. This may reflect the increased engagement of domain-general and domain-specific processes subserved by the dorsolateral prefrontal cortex (e.g., cognitive control) and inferior frontal gyrus (e.g., predicting the sensory consequences of articulatory gestures), respectively.

Validation of the Iowa Test of Consonant Perception

Speech perception (especially in background noise) is a critical problem for hearing-impaired listeners and an important issue for cognitive hearing science. Despite a plethora of standardized measures, few single-word closed-set tests uniformly sample the most frequently used phonemes and use response choices that equally sample phonetic features like place and voicing. The Iowa Test of Consonant Perception (ITCP) attempts to solve this. It is a proportionally balanced phonemic word recognition task designed to assess perception of the initial consonant of monosyllabic consonant-vowel-consonant (CVC) words. The ITCP consists of 120 sampled CVC words. Words were recorded from four different talkers (two female) and uniformly sampled from all four quadrants of the vowel space to control for coarticulation. Response choices on each trial are balanced to equate difficulty and sample a single phonetic feature. This study evaluated the psychometric properties of ITCP by examining reliability (test-retest) and validity in a sample of online normal-hearing participants. Ninety-eight participants completed two sessions of the ITCP along with standardized tests of words and sentence in noise (CNC words and AzBio sentences). The ITCP showed good test-retest reliability and convergent validity with two popular tests presented in noise. All the materials to use the ITCP or to construct your own version of the ITCP are freely available [Geller, McMurray, Holmes, and Choi (2020). https://osf.io/hycdu/].

Dichotic listening deficits in amblyaudia are characterized by aberrant neural oscillations in auditory cortex

OBJECTIVE

Children diagnosed with auditory processing disorder (APD) show deficits in processing complex sounds that are associated with difficulties in higher-order language, learning, cognitive, and communicative functions. Amblyaudia (AMB) is a subcategory of APD characterized by abnormally large ear asymmetries in dichotic listening tasks.

METHODS

Here, we examined frequency-specific neural oscillations and functional connectivity via high-density electroencephalography (EEG) in children with and without AMB during passive listening of nonspeech stimuli.

RESULTS

Time-frequency maps of these "brain rhythms" revealed stronger phase-locked beta-gamma (~35 Hz) oscillations in AMB participants within bilateral auditory cortex for sounds presented to the right ear, suggesting a hypersynchronization and imbalance of auditory neural activity. Brain-behavior correlations revealed neural asymmetries in cortical responses predicted the larger than normal right-ear advantage seen in participants with AMB. Additionally, we found weaker functional connectivity in the AMB group from right to left auditory cortex, despite their stronger neural responses overall.

CONCLUSION

Our results reveal abnormally large auditory sensory encoding and an imbalance in communication between cerebral hemispheres (ipsi- to -contralateral signaling) in AMB.

SIGNIFICANCE

These neurophysiological changes might lead to the functionally poorer behavioral capacity to integrate information between the two ears in children with AMB.

Data-driven machine learning models for decoding speech categorization from evoked brain responses

Objective.Categorical perception (CP) of audio is critical to understand how the human brain perceives speech sounds despite widespread variability in acoustic properties. Here, we investigated the spatiotemporal characteristics of auditory neural activity that reflects CP for speech (i.e. differentiates phonetic prototypes from ambiguous speech sounds).Approach.We recorded 64-channel electroencephalograms as listeners rapidly classified vowel sounds along an acoustic-phonetic continuum. We used support vector machine classifiers and stability selection to determine when and where in the brain CP was best decoded across space and time via source-level analysis of the event-related potentials.Main results. We found that early (120 ms) whole-brain data decoded speech categories (i.e. prototypical vs. ambiguous tokens) with 95.16% accuracy (area under the curve 95.14%;F1-score 95.00%). Separate analyses on left hemisphere (LH) and right hemisphere (RH) responses showed that LH decoding was more accurate and earlier than RH (89.03% vs. 86.45% accuracy; 140 ms vs. 200 ms). Stability (feature) selection identified 13 regions of interest (ROIs) out of 68 brain regions [including auditory cortex, supramarginal gyrus, and inferior frontal gyrus (IFG)] that showed categorical representation during stimulus encoding (0-260 ms). In contrast, 15 ROIs (including fronto-parietal regions, IFG, motor cortex) were necessary to describe later decision stages (later 300-800 ms) of categorization but these areas were highly associated with the strength of listeners' categorical hearing (i.e. slope of behavioral identification functions).Significance.Our data-driven multivariate models demonstrate that abstract categories emerge surprisingly early (∼120 ms) in the time course of speech processing and are dominated by engagement of a relatively compact fronto-temporal-parietal brain network.

Data-driven machine learning models for decoding speech categorization from evoked brain responses

Objective.Categorical perception (CP) of audio is critical to understand how the human brain perceives speech sounds despite widespread variability in acoustic properties. Here, we investigated the spatiotemporal characteristics of auditory neural activity that reflects CP for speech (i.e. differentiates phonetic prototypes from ambiguous speech sounds).Approach.We recorded 64-channel electroencephalograms as listeners rapidly classified vowel sounds along an acoustic-phonetic continuum. We used support vector machine classifiers and stability selection to determine when and where in the brain CP was best decoded across space and time via source-level analysis of the event-related potentials.Main results. We found that early (120 ms) whole-brain data decoded speech categories (i.e. prototypical vs. ambiguous tokens) with 95.16% accuracy (area under the curve 95.14%;F1-score 95.00%). Separate analyses on left hemisphere (LH) and right hemisphere (RH) responses showed that LH decoding was more accurate and earlier than RH (89.03% vs. 86.45% accuracy; 140 ms vs. 200 ms). Stability (feature) selection identified 13 regions of interest (ROIs) out of 68 brain regions [including auditory cortex, supramarginal gyrus, and inferior frontal gyrus (IFG)] that showed categorical representation during stimulus encoding (0-260 ms). In contrast, 15 ROIs (including fronto-parietal regions, IFG, motor cortex) were necessary to describe later decision stages (later 300-800 ms) of categorization but these areas were highly associated with the strength of listeners' categorical hearing (i.e. slope of behavioral identification functions).Significance.Our data-driven multivariate models demonstrate that abstract categories emerge surprisingly early (∼120 ms) in the time course of speech processing and are dominated by engagement of a relatively compact fronto-temporal-parietal brain network.

Processing of Degraded Speech in Brain Disorders

The speech we hear every day is typically "degraded" by competing sounds and the idiosyncratic vocal characteristics of individual speakers. While the comprehension of "degraded" speech is normally automatic, it depends on dynamic and adaptive processing across distributed neural networks. This presents the brain with an immense computational challenge, making degraded speech processing vulnerable to a range of brain disorders. Therefore, it is likely to be a sensitive marker of neural circuit dysfunction and an index of retained neural plasticity. Considering experimental methods for studying degraded speech and factors that affect its processing in healthy individuals, we review the evidence for altered degraded speech processing in major neurodegenerative diseases, traumatic brain injury and stroke. We develop a predictive coding framework for understanding deficits of degraded speech processing in these disorders, focussing on the "language-led dementias"-the primary progressive aphasias. We conclude by considering prospects for using degraded speech as a probe of language network pathophysiology, a diagnostic tool and a target for therapeutic intervention.

Pre- and post-target cortical processes predict speech-in-noise performance

Understanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. There is a variance in individuals' ability to understand SiN that cannot be explained by simple hearing profiles, which suggests that central factors may underlie the variance in SiN ability. Here, we elucidated a few cortical functions involved during a SiN task and their contributions to individual variance using both within- and across-subject approaches. Through our within-subject analysis of source-localized electroencephalography, we investigated how acoustic signal-to-noise ratio (SNR) alters cortical evoked responses to a target word across the speech recognition areas, finding stronger responses in left supramarginal gyrus (SMG, BA40 the dorsal lexicon area) with quieter noise. Through an individual differences approach, we found that listeners show different neural sensitivity to the background noise and target speech, reflected in the amplitude ratio of earlier auditory-cortical responses to speech and noise, named as an internal SNR. Listeners with better internal SNR showed better SiN performance. Further, we found that the post-speech time SMG activity explains a further amount of variance in SiN performance that is not accounted for by internal SNR. This result demonstrates that at least two cortical processes contribute to SiN performance independently: pre-target time processing to attenuate neural representation of background noise and post-target time processing to extract information from speech sounds.

Auditory cortex is susceptible to lexical influence as revealed by informational vs. energetic masking of speech categorization

Speech perception requires the grouping of acoustic information into meaningful phonetic units via the process of categorical perception (CP). Environmental masking influences speech perception and CP. However, it remains unclear at which stage of processing (encoding, decision, or both) masking affects listeners' categorization of speech signals. The purpose of this study was to determine whether linguistic interference influences the early acoustic-phonetic conversion process inherent to CP. To this end, we measured source level, event related brain potentials (ERPs) from auditory cortex (AC) and inferior frontal gyrus (IFG) as listeners rapidly categorized speech sounds along a /da/ to /ga/ continuum presented in three listening conditions: quiet, and in the presence of forward (informational masker) and time-reversed (energetic masker) 2-talker babble noise. Maskers were matched in overall SNR and spectral content and thus varied only in their degree of linguistic interference (i.e., informational masking). We hypothesized a differential effect of informational versus energetic masking on behavioral and neural categorization responses, where we predicted increased activation of frontal regions when disambiguating speech from noise, especially during lexical-informational maskers. We found (1) informational masking weakens behavioral speech phoneme identification above and beyond energetic masking; (2) low-level AC activity not only codes speech categories but is susceptible to higher-order lexical interference; (3) identifying speech amidst noise recruits a cross hemispheric circuit (AC_left → IFG_right) whose engagement varies according to task difficulty. These findings provide corroborating evidence for top-down influences on the early acoustic-phonetic analysis of speech through a coordinated interplay between frontotemporal brain areas.

Subcortical rather than cortical sources of the frequency-following response (FFR) relate to speech-in-noise perception in normal-hearing listeners

Scalp-recorded frequency-following responses (FFRs) reflect a mixture of phase-locked activity across the auditory pathway. FFRs have been widely used as a neural barometer of complex listening skills, especially speech-in noise (SIN) perception. Applying individually optimized source reconstruction to speech-FFRs recorded via EEG (FFR_EEG), we assessed the relative contributions of subcortical [auditory nerve (AN), brainstem/midbrain (BS)] and cortical [bilateral primary auditory cortex, PAC] source generators with the aim of identifying which source(s) drive the brain-behavior relation between FFRs and SIN listening skills. We found FFR strength declined precipitously from AN to PAC, consistent with diminishing phase-locking along the ascending auditory neuroaxis. FFRs to the speech fundamental (F0) were robust to noise across sources, but were largest in subcortical sources (BS > AN > PAC). PAC FFRs were only weakly observed above the noise floor and only at the low pitch of speech (F0≈100 Hz). Brain-behavior regressions revealed (i) AN and BS FFRs were sufficient to describe listeners' QuickSIN scores and (ii) contrary to neuromagnetic (MEG) FFRs, neither left nor right PAC FFR_EEG related to SIN performance. Our findings suggest subcortical sources not only dominate the electrical FFR but also the link between speech-FFRs and SIN processing in normal-hearing adults as observed in previous EEG studies.

Hearing loss is associated with gray matter differences in older adults at risk for and with Alzheimer's disease

Using data from the COMPASS-ND study we investigated associations between hearing loss and hippocampal volume as well as cortical thickness in older adults with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's dementia (AD). SCD participants with greater pure-tone hearing loss exhibited lower hippocampal volume, but more cortical thickness in the left superior temporal gyrus and right pars opercularis. Greater speech-in-noise reception thresholds were associated with lower cortical thickness bilaterally across much of the cortex in AD. The AD group also showed a trend towards worse speech-in-noise thresholds compared to the SCD group.

Difficulties with Speech-in-Noise Perception Related to Fundamental Grouping Processes in Auditory Cortex

In our everyday lives, we are often required to follow a conversation when background noise is present (“speech-in-noise” [SPIN] perception). SPIN perception varies widely—and people who are worse at SPIN perception are also worse at fundamental auditory grouping, as assessed by figure-ground tasks. Here, we examined the cortical processes that link difficulties with SPIN perception to difficulties with figure-ground perception using functional magnetic resonance imaging. We found strong evidence that the earliest stages of the auditory cortical hierarchy (left core and belt areas) are similarly disinhibited when SPIN and figure-ground tasks are more difficult (i.e., at target-to-masker ratios corresponding to 60% rather than 90% performance)—consistent with increased cortical gain at lower levels of the auditory hierarchy. Overall, our results reveal a common neural substrate for these basic (figure-ground) and naturally relevant (SPIN) tasks—which provides a common computational basis for the link between SPIN perception and fundamental auditory grouping.

Decoding Hearing-Related Changes in Older Adults' Spatiotemporal Neural Processing of Speech Using Machine Learning

Speech perception in noisy environments depends on complex interactions between sensory and cognitive systems. In older adults, such interactions may be affected, especially in those individuals who have more severe age-related hearing loss. Using a data-driven approach, we assessed the temporal (when in time) and spatial (where in the brain) characteristics of cortical speech-evoked responses that distinguish older adults with or without mild hearing loss. We performed source analyses to estimate cortical surface signals from the EEG recordings during a phoneme discrimination task conducted under clear and noise-degraded conditions. We computed source-level ERPs (i.e., mean activation within each ROI) from each of the 68 ROIs of the Desikan-Killiany (DK) atlas, averaged over a randomly chosen 100 trials without replacement to form feature vectors. We adopted a multivariate feature selection method called stability selection and control to choose features that are consistent over a range of model parameters. We use parameter optimized support vector machine (SVM) as a classifiers to investigate the time course and brain regions that segregate groups and speech clarity. For clear speech perception, whole-brain data revealed a classification accuracy of 81.50% [area under the curve (AUC) 80.73%; F1-score 82.00%], distinguishing groups within ∼60 ms after speech onset (i.e., as early as the P1 wave). We observed lower accuracy of 78.12% [AUC 77.64%; F1-score 78.00%] and delayed classification performance when speech was embedded in noise, with group segregation at 80 ms. Separate analysis using left (LH) and right hemisphere (RH) regions showed that LH speech activity was better at distinguishing hearing groups than activity measured in the RH. Moreover, stability selection analysis identified 12 brain regions (among 1428 total spatiotemporal features from 68 regions) where source activity segregated groups with >80% accuracy (clear speech); whereas 16 regions were critical for noise-degraded speech to achieve a comparable level of group segregation (78.7% accuracy). Our results identify critical time-courses and brain regions that distinguish mild hearing loss from normal hearing in older adults and confirm a larger number of active areas, particularly in RH, when processing noise-degraded speech information.

Effects of Signal Type and Noise Background on Auditory Evoked Potential N1, P2, and P3 Measurements in Blast-Exposed Veterans

OBJECTIVES

Veterans who have been exposed to high-intensity blast waves frequently report persistent auditory difficulties such as problems with speech-in-noise (SIN) understanding, even when hearing sensitivity remains normal. However, these subjective reports have proven challenging to corroborate objectively. Here, we sought to determine whether use of complex stimuli and challenging signal contrasts in auditory evoked potential (AEP) paradigms rather than traditional use of simple stimuli and easy signal contrasts improved the ability of these measures to (1) distinguish between blast-exposed Veterans with auditory complaints and neurologically normal control participants, and (2) predict behavioral measures of SIN perception.

DESIGN

A total of 33 adults (aged 19-56 years) took part in this study, including 17 Veterans exposed to high-intensity blast waves within the past 10 years and 16 neurologically normal control participants matched for age and hearing status with the Veteran participants. All participants completed the following test measures: (1) a questionnaire probing perceived hearing abilities; (2) behavioral measures of SIN understanding including the BKB-SIN, the AzBio presented in 0 and +5 dB signal to noise ratios (SNRs), and a word-level consonant-vowel-consonant test presented at +5 dB SNR; and (3) electrophysiological tasks involving oddball paradigms in response to simple tones (500 Hz standard, 1000 Hz deviant) and complex speech syllables (/ba/ standard, /da/ deviant) presented in quiet and in four-talker speech babble at a SNR of +5 dB.

RESULTS

Blast-exposed Veterans reported significantly greater auditory difficulties compared to control participants. Behavioral performance on tests of SIN perception was generally, but not significantly, poorer among the groups. Latencies of P3 responses to tone signals were significantly longer among blast-exposed participants compared to control participants regardless of background condition, though responses to speech signals were similar across groups. For cortical AEPs, no significant interactions were found between group membership and either stimulus type or background. P3 amplitudes measured in response to signals in background babble accounted for 30.9% of the variance in subjective auditory reports. Behavioral SIN performance was best predicted by a combination of N1 and P2 responses to signals in quiet which accounted for 69.6% and 57.4% of the variance on the AzBio at 0 dB SNR and the BKB-SIN, respectively.

CONCLUSIONS

Although blast-exposed participants reported far more auditory difficulties compared to controls, use of complex stimuli and challenging signal contrasts in cortical and cognitive AEP measures failed to reveal larger group differences than responses to simple stimuli and easy signal contrasts. Despite this, only P3 responses to signals presented in background babble were predictive of subjective auditory complaints. In contrast, cortical N1 and P2 responses were predictive of behavioral SIN performance but not subjective auditory complaints, and use of challenging background babble generally did not improve performance predictions. These results suggest that challenging stimulus protocols are more likely to tap into perceived auditory deficits, but may not be beneficial for predicting performance on clinical measures of SIN understanding. Finally, these results should be interpreted with caution since blast-exposed participants did not perform significantly poorer on tests of SIN perception.

Effects of Noise on the Behavioral and Neural Categorization of Speech

We investigated whether the categorical perception (CP) of speech might also provide a mechanism that aids its perception in noise. We varied signal-to-noise ratio (SNR) [clear, 0 dB, -5 dB] while listeners classified an acoustic-phonetic continuum (/u/ to /a/). Noise-related changes in behavioral categorization were only observed at the lowest SNR. Event-related brain potentials (ERPs) differentiated category vs. category-ambiguous speech by the P2 wave (~180-320 ms). Paralleling behavior, neural responses to speech with clear phonetic status (i.e., continuum endpoints) were robust to noise down to -5 dB SNR, whereas responses to ambiguous tokens declined with decreasing SNR. Results demonstrate that phonetic speech representations are more resistant to degradation than corresponding acoustic representations. Findings suggest the mere process of binning speech sounds into categories provides a robust mechanism to aid figure-ground speech perception by fortifying abstract categories from the acoustic signal and making the speech code more resistant to external interferences.

Effects of Directional Microphone and Noise Reduction on Subcortical and Cortical Auditory-Evoked Potentials in Older Listeners With Hearing Loss

OBJECTIVES

Understanding how signal processing influences neural activity in the brain with hearing loss is relevant to the design and evaluation of features intended to alleviate speech-in-noise deficits faced by many hearing aid wearers. Here, we examine whether hearing aid processing schemes that are designed to improve speech-in-noise intelligibility (i.e., directional microphone and noise reduction) also improve electrophysiological indices of speech processing in older listeners with hearing loss.

DESIGN

The study followed a double-blind within-subjects design. A sample of 19 older adults (8 females; mean age = 73.6 years, range = 56-86 years; 17 experienced hearing aid users) with a moderate to severe sensorineural hearing impairment participated in the experiment. Auditory-evoked potentials associated with processing in cortex (P1-N1-P2) and subcortex (frequency-following response) were measured over the course of two 2-hour visits. Listeners were presented with sequences of the consonant-vowel syllable /da/ in continuous speech-shaped noise at signal to noise ratios (SNRs) of 0, +5, and +10 dB. Speech and noise stimuli were pre-recorded using a Knowles Electronics Manikin for Acoustic Research (KEMAR) head and torso simulator outfitted with hearing aids programmed for each listener's loss. The study aid programs were set according to 4 conditions: (1) omnidirectional microphone, (2) omnidirectional microphone with noise reduction, (3) directional microphone, and (4) directional microphone with noise reduction. For each hearing aid condition, speech was presented from a loudspeaker located at 1 m directly in front of KEMAR (i.e., 0° in the azimuth) at 75 dB SPL and noise was presented from a matching loudspeaker located at 1 m directly behind KEMAR (i.e., 180° in the azimuth). Recorded stimulus sequences were normalized for speech level across conditions and presented to listeners over electromagnetically shielded ER-2 ear-insert transducers. Presentation levels were calibrated to match the output of listeners' study aids.

RESULTS

Cortical components from listeners with hearing loss were enhanced with improving SNR and with use of a directional microphone and noise reduction. On the other hand, subcortical components did not show sensitivity to SNR or microphone mode but did show enhanced encoding of temporal fine structure of speech for conditions where noise reduction was enabled.

CONCLUSIONS

These results suggest that auditory-evoked potentials may be useful in evaluating the benefit of different noise-mitigating hearing aid features.

Decoding of single-trial EEG reveals unique states of functional brain connectivity that drive rapid speech categorization decisions

OBJECTIVE

Categorical perception (CP) is an inherent property of speech perception. The response time (RT) of listeners' perceptual speech identification is highly sensitive to individual differences. While the neural correlates of CP have been well studied in terms of the regional contributions of the brain to behavior, functional connectivity patterns that signify individual differences in listeners' speed (RT) for speech categorization is less clear. In this study, we introduce a novel approach to address these questions.

APPROACH

We applied several computational approaches to the EEG, including graph mining, machine learning (i.e., support vector machine), and stability selection to investigate the unique brain states (functional neural connectivity) that predict the speed of listeners' behavioral decisions.

MAIN RESULTS

We infer that (i) the listeners' perceptual speed is directly related to dynamic variations in their brain connectomics, (ii) global network assortativity and efficiency distinguished fast, medium, and slow RTs, (iii) the functional network underlying speeded decisions increases in negative assortativity (i.e., became disassortative) for slower RTs, (iv) slower categorical speech decisions cause excessive use of neural resources and more aberrant information flow within the CP circuitry, (v) slower responders tended to utilize functional brain networks excessively (or inappropriately) whereas fast responders (with lower global efficiency) utilized the same neural pathways but with more restricted organization.

SIGNIFICANCE

Findings show that neural classifiers (SVM) coupled with stability selection correctly classify behavioral RTs from functional connectivity alone with over 92% accuracy (AUC  =  0.9). Our results corroborate previous studies by supporting the engagement of similar temporal (STG), parietal, motor, and prefrontal regions in CP using an entirely data-driven approach.

Noise-Induced Change of Cortical Temporal Processing in Cochlear Implant Users

OBJECTIVES

Cochlear implant (CI) users typically report impaired ability to understand speech in noise. Speech understanding in CI users decreases with noise due to reduced temporal processing ability, and speech perceptual errors involve stop consonants distinguished by voice onset time (VOT). The current study examined the effects of noise on various speech perception tests while at the same time used cortical auditory evoked potentials (CAEPs) to quantify the change of neural processing of speech sounds caused by noise. We hypothesized that the noise effects on VOT processing can be reflected in N1/P2 measures, the neural changes relate to behavioral speech perception performances.

METHODS

Ten adult CI users and 15 normal-hearing (NH) people participated in this study. CAEPs were recorded from 64 scalp electrodes in both quiet and noise (signal-to-noise ratio +5 dB) and in passive and active (requiring consonant discrimination) listening. Speech stimulus was synthesized consonant-vowels with VOTs of 0 and 50 ms. N1-P2 amplitudes and latencies were analyzed as a function of listening condition. For the active condition, the P3b also was analyzed. Behavioral measures included a variety of speech perception tasks.

RESULTS

For good performing CI users, performance in most speech test was lower in the presence of noise masking. N1 and P2 latencies became prolonged with noise masking. The P3b amplitudes were smaller in CI groups compared to NH. The degree of P2 latency change (0 vs. 50 ms VOT) was correlated with consonant perception in noise.

CONCLUSION

The effects of noise masking on temporal processing can be reflected in cortical responses in CI users. N1/P2 latencies were more sensitive to noise masking than amplitude measures. Additionally, P2 responses appear to have a better relationship to speech perception in CI users compared to N1.

Auditory-frontal Channeling in α and β Bands is Altered by Age-related Hearing Loss and Relates to Speech Perception in Noise

Difficulty understanding speech-in-noise (SIN) is a pervasive problem faced by older adults particularly those with hearing loss. Previous studies have identified structural and functional changes in the brain that contribute to older adults' speech perception difficulties. Yet, many of these studies use neuroimaging techniques that evaluate only gross activation in isolated brain regions. Neural oscillations may provide further insight into the processes underlying SIN perception as well as the interaction between auditory cortex and prefrontal linguistic brain regions that mediate complex behaviors. We examined frequency-specific neural oscillations and functional connectivity of the EEG in older adults with and without hearing loss during an active SIN perception task. Brain-behavior correlations revealed listeners who were more resistant to the detrimental effects of noise also demonstrated greater modulation of α phase coherence between clean and noise-degraded speech, suggesting α desynchronization reflects release from inhibition and more flexible allocation of neural resources. Additionally, we found top-down β connectivity between prefrontal and auditory cortices strengthened with poorer hearing thresholds despite minimal behavioral differences. This is consistent with the proposal that linguistic brain areas may be recruited to compensate for impoverished auditory inputs through increased top-down predictions to assist SIN perception. Overall, these results emphasize the importance of top-down signaling in low-frequency brain rhythms that help compensate for hearing-related declines and facilitate efficient SIN processing.

Age-related hearing loss increases full-brain connectivity while reversing directed signaling within the dorsal-ventral pathway for speech

Speech comprehension difficulties are ubiquitous to aging and hearing loss, particularly in noisy environments. Older adults' poorer speech-in-noise (SIN) comprehension has been related to abnormal neural representations within various nodes (regions) of the speech network, but how senescent changes in hearing alter the transmission of brain signals remains unspecified. We measured electroencephalograms in older adults with and without mild hearing loss during a SIN identification task. Using functional connectivity and graph-theoretic analyses, we show that hearing-impaired (HI) listeners have more extended (less integrated) communication pathways and less efficient information exchange among widespread brain regions (larger network eccentricity) than their normal-hearing (NH) peers. Parameter optimized support vector machine classifiers applied to EEG connectivity data showed hearing status could be decoded (> 85% accuracy) solely using network-level descriptions of brain activity, but classification was particularly robust using left hemisphere connections. Notably, we found a reversal in directed neural signaling in left hemisphere dependent on hearing status among specific connections within the dorsal-ventral speech pathways. NH listeners showed an overall net "bottom-up" signaling directed from auditory cortex (A1) to inferior frontal gyrus (IFG; Broca's area), whereas the HI group showed the reverse signal (i.e., "top-down" Broca's → A1). A similar flow reversal was noted between left IFG and motor cortex. Our full-brain connectivity results demonstrate that even mild forms of hearing loss alter how the brain routes information within the auditory-linguistic-motor loop.

[Hearing and cognition: neurocognitive test batteries in otorhinolaryngology]

BACKGROUND

Hearing and cognition are closely related to each other. Particularly in suboptimal listening situations, cognitive abilities become important to enable speech comprehension. Besides, studies have indicated that hearing impairment is associated with a more rapid mental decline compared to persons with normal hearing. However, hearing loss also has an impact on neurocognitive testing, which is generally based on auditive stimuli. With increasing age, the risk of sensory but also of cognitive impairments increases. So far this comorbidity receives little consideration in otorhinolaryngology.

MATERIALS AND METHODS

The paper presents an overview and evaluation of widely used German neurocognitive test batteries for older patients, with regard to the different test modalities and their focus.

RESULTS

A multitude of different neurocognitive screening tests and detailed test batteries are available, particularly in the field of dementia. So far, sensory deficits have not been considered in neurocognitive testing, neither concerning application nor interpretation. Normative data adapted to the hearing impaired are still missing.

CONCLUSION

With regard to demographic changes and the well-known bias between hearing and cognition, screening of neurocognitive functions should be implemented in basic otorhinolaryngologic diagnostics. More comprehensive test batteries might be useful for research purposes or speech therapy.

Afferent-efferent connectivity between auditory brainstem and cortex accounts for poorer speech-in-noise comprehension in older adults

Speech-in-noise (SIN) comprehension deficits in older adults have been linked to changes in both subcortical and cortical auditory evoked responses. However, older adults' difficulty understanding SIN may also be related to an imbalance in signal transmission (i.e., functional connectivity) between brainstem and auditory cortices. By modeling high-density scalp recordings of speech-evoked responses with sources in brainstem (BS) and bilateral primary auditory cortices (PAC), we show that beyond attenuating neural activity, hearing loss in older adults compromises the transmission of speech information between subcortical and early cortical hubs of the speech network. We found that the strength of afferent BS→PAC neural signaling (but not the reverse efferent flow; PAC→BS) varied with mild declines in hearing acuity and this "bottom-up" functional connectivity robustly predicted older adults' performance in a SIN identification task. Connectivity was also a better predictor of SIN processing than unitary subcortical or cortical responses alone. Our neuroimaging findings suggest that in older adults (i) mild hearing loss differentially reduces neural output at several stages of auditory processing (PAC > BS), (ii) subcortical-cortical connectivity is more sensitive to peripheral hearing loss than top-down (cortical-subcortical) control, and (iii) reduced functional connectivity in afferent auditory pathways plays a significant role in SIN comprehension problems.

The Lateralization of Speech-Brain Coupling Is Differentially Modulated by Intrinsic Auditory and Top-Down Mechanisms

The lateralization of neuronal processing underpinning hearing, speech, language, and music is widely studied, vigorously debated, and still not understood in a satisfactory manner. One set of hypotheses focuses on the temporal structure of perceptual experience and links auditory cortex asymmetries to underlying differences in neural populations with differential temporal sensitivity (e.g., ideas advanced by Zatorre et al. (2002) and Poeppel (2003). The Asymmetric Sampling in Time theory (AST) (Poeppel, 2003), builds on cytoarchitectonic differences between auditory cortices and predicts that modulation frequencies within the range of, roughly, the syllable rate, are more accurately tracked by the right hemisphere. To date, this conjecture is reasonably well supported, since - while there is some heterogeneity in the reported findings - the predicted asymmetrical entrainment has been observed in various experimental protocols. Here, we show that under specific processing demands, the rightward dominance disappears. We propose an enriched and modified version of the asymmetric sampling hypothesis in the context of speech. Recent work (Rimmele et al., 2018b) proposes two different mechanisms to underlie the auditory tracking of the speech envelope: one derived from the intrinsic oscillatory properties of auditory regions; the other induced by top-down signals coming from other non-auditory regions of the brain. We propose that under non-speech listening conditions, the intrinsic auditory mechanism dominates and thus, in line with AST, entrainment is rightward lateralized, as is widely observed. However, (i) depending on individual brain structural/functional differences, and/or (ii) in the context of specific speech listening conditions, the relative weight of the top-down mechanism can increase. In this scenario, the typically observed auditory sampling asymmetry (and its rightward dominance) diminishes or vanishes.

Plasticity in auditory categorization is supported by differential engagement of the auditory-linguistic network

To construct our perceptual world, the brain categorizes variable sensory cues into behaviorally-relevant groupings. Categorical representations are apparent within a distributed fronto-temporo-parietal brain network but how this neural circuitry is shaped by experience remains undefined. Here, we asked whether speech and music categories might be formed within different auditory-linguistic brain regions depending on listeners' auditory expertise. We recorded EEG in highly skilled (musicians) vs. less experienced (nonmusicians) perceivers as they rapidly categorized speech and musical sounds. Musicians showed perceptual enhancements across domains, yet source EEG data revealed a double dissociation in the neurobiological mechanisms supporting categorization between groups. Whereas musicians coded categories in primary auditory cortex (PAC), nonmusicians recruited non-auditory regions (e.g., inferior frontal gyrus, IFG) to generate category-level information. Functional connectivity confirmed nonmusicians' increased left IFG involvement reflects stronger routing of signal from PAC directed to IFG, presumably because sensory coding is insufficient to construct categories in less experienced listeners. Our findings establish auditory experience modulates specific engagement and inter-regional communication in the auditory-linguistic network supporting categorical perception. Whereas early canonical PAC representations are sufficient to generate categories in highly trained ears, less experienced perceivers broadcast information downstream to higher-order linguistic brain areas (IFG) to construct abstract sound labels.

Psychobiological Responses Reveal Audiovisual Noise Differentially Challenges Speech Recognition

OBJECTIVES

In noisy environments, listeners benefit from both hearing and seeing a talker, demonstrating audiovisual (AV) cues enhance speech-in-noise (SIN) recognition. Here, we examined the relative contribution of auditory and visual cues to SIN perception and the strategies used by listeners to decipher speech in noise interference(s).

DESIGN

Normal-hearing listeners (n = 22) performed an open-set speech recognition task while viewing audiovisual TIMIT sentences presented under different combinations of signal degradation including visual (AVn), audio (AnV), or multimodal (AnVn) noise. Acoustic and visual noises were matched in physical signal-to-noise ratio. Eyetracking monitored participants' gaze to different parts of a talker's face during SIN perception.

RESULTS

As expected, behavioral performance for clean sentence recognition was better for A-only and AV compared to V-only speech. Similarly, with noise in the auditory channel (AnV and AnVn speech), performance was aided by the addition of visual cues of the talker regardless of whether the visual channel contained noise, confirming a multimodal benefit to SIN recognition. The addition of visual noise (AVn) obscuring the talker's face had little effect on speech recognition by itself. Listeners' eye gaze fixations were biased toward the eyes (decreased at the mouth) whenever the auditory channel was compromised. Fixating on the eyes was negatively associated with SIN recognition performance. Eye gazes on the mouth versus eyes of the face also depended on the gender of the talker.

CONCLUSIONS

Collectively, results suggest listeners (1) depend heavily on the auditory over visual channel when seeing and hearing speech and (2) alter their visual strategy from viewing the mouth to viewing the eyes of a talker with signal degradations, which negatively affects speech perception.

Acoustic noise and vision differentially warp the auditory categorization of speech

Speech perception requires grouping acoustic information into meaningful linguistic-phonetic units via categorical perception (CP). Beyond shrinking observers' perceptual space, CP might aid degraded speech perception if categories are more resistant to noise than surface acoustic features. Combining audiovisual (AV) cues also enhances speech recognition, particularly in noisy environments. This study investigated the degree to which visual cues from a talker (i.e., mouth movements) aid speech categorization amidst noise interference by measuring participants' identification of clear and noisy speech (0 dB signal-to-noise ratio) presented in auditory-only or combined AV modalities (i.e., A, A+noise, AV, AV+noise conditions). Auditory noise expectedly weakened (i.e., shallower identification slopes) and slowed speech categorization. Interestingly, additional viseme cues largely counteracted noise-related decrements in performance and stabilized classification speeds in both clear and noise conditions suggesting more precise acoustic-phonetic representations with multisensory information. Results are parsimoniously described under a signal detection theory framework and by a reduction (visual cues) and increase (noise) in the precision of perceptual object representation, which were not due to lapses of attention or guessing. Collectively, findings show that (i) mapping sounds to categories aids speech perception in "cocktail party" environments; (ii) visual cues help lattice formation of auditory-phonetic categories to enhance and refine speech identification.

Intracortical Myelination of Heschl's Gyrus and the Planum Temporale Varies With Heschl's Duplication Pattern and Rhyming Performance: An Investigation of 440 Healthy Volunteers

We investigated, in 445 healthy adults whose Heschl's gyrus (HG) gyrification patterns had been previously identified, how an in vivo MRI marker of intracortical myelination of HG and the planum temporale (PT) varied as a function of HG gyrification pattern and, in cases of duplication, of anatomical characteristics of the second HG (H2). By measuring the MRI T1/T2 ratio in regions of interest covering the first HG (H1), H2 in cases of common stem (H2CSD), or complete posterior duplication (H2CPD) and the PT, we showed that H1 had the highest T1/T2 values, while the PT had the lowest. The major impact of duplication was a decrease in both H1 and PT T1/T2 values in cases of left CPD. Concerning H2, the right and left T1/T2 values of right H2CSD were closer to those of H1, and those of left H2CPD were closer to those of PT. After adjusting for verbal skills, rhyming performance was not associated with T1/T2 values in left regions, but it decreased with increasing right PT T1/T2 values. These results reveal the existence of hemispheric differences in H2 myelination and underline the importance of neuroimaging markers of intracortical myelination for investigating brain structure-function relationships.

EEG rhythms lateralization patterns in children with unilateral hearing loss are different from the patterns of normal hearing controls during speech-in-noise listening

Unilateral hearing loss constitutes a field of growing interest in the scientific community. In fact, this kind of patients represent a unique and physiological way to investigate how neuroplasticity overcame unilateral deafferentation by implementing particular strategies that produce apparently next- to- normal hearing behavioural performances. This explains why such patients have been underinvestigated for a long time. Thanks to the availability of techniques able to study the cerebral activity underlying the mentioned behavioural outcomes, the aim of the present research was to elucidate whether different electroencephalographic (EEG) patterns occurred in unilateral hearing loss (UHL) children in comparison to normal hearing (NH) controls during speech-in-noise listening. Given the intrinsic lateralized nature of such patients, due to the unilateral side of hearing impairment, the experimental question was to assess whether this would reflect a different EEG pattern while performing a word in noise recognition task varying the direction of the noise source. Results showed a correlation between the period of deafness and the cortical activity asymmetry toward the hearing ear side in the frontal, parietal and occipital areas in all the experimental conditions. Concerning alpha and beta activity in the frontal and central areas highlighted that in the NH group, the lateralization was always left-sided during the Quiet condition, while it was right-sided in noise conditions; this evidence was not, however, detected also in the UHL group. In addition, focusing on the theta and alpha activity in the frontal areas (Broca area) during noise conditions, while the activity was always left-lateralized in the NH group, it was ipsilateral to the direction of the background noise in the UHL group, and of a weaker extent than in NH controls. Furthermore, in noise conditions, only the UHL group showed a higher theta activity in the temporal areas ipsilateral to the side where the background noise was directed to. Finally, in the case of bilateral noise (background noise and word signal both coming from the same two sources), the theta and alpha activity in the frontal areas (Broca area) was left-lateralized in the case of the NH group and lateralized towards the side of the better hearing ear in the case of the UHL group. Taken together, this evidence supports the establishment of a particular EEG pattern occurrence in UHL children taking place in the frontal (Broca area), temporal and parietal lobes, probably physiologically established in order to deal with different sound and noise source directions.