Robust cortical entrainment to the speech envelope relies on the spectro-temporal fine structure

Impaired Cortical Tracking of Speech in Children with Developmental Language Disorder

In developmental language disorder (DLD), learning to comprehend and express oneself with spoken language is impaired, but the reason for this remains unknown. Using millisecond-scale magnetoencephalography recordings combined with machine learning models, we investigated whether the possible neural basis of this disruption lies in poor cortical tracking of speech. The stimuli were common spoken Finnish words (e.g., dog, car, hammer) and sounds with corresponding meanings (e.g., dog bark, car engine, hammering). In both children with DLD (10 boys and 7 girls) and typically developing (TD) control children (14 boys and 3 girls), aged 10-15 years, the cortical activation to spoken words was best modeled as time-locked to the unfolding speech input at ∼100 ms latency between sound and cortical activation. Amplitude envelope (amplitude changes) and spectrogram (detailed time-varying spectral content) of the spoken words, but not other sounds, were very successfully decoded based on time-locked brain responses in bilateral temporal areas; based on the cortical responses, the models could tell at ∼75-85% accuracy which of the two sounds had been presented to the participant. However, the cortical representation of the amplitude envelope information was poorer in children with DLD compared with TD children at longer latencies (at ∼200-300 ms lag). We interpret this effect as reflecting poorer retention of acoustic-phonetic information in short-term memory. This impaired tracking could potentially affect the processing and learning of words as well as continuous speech. The present results offer an explanation for the problems in language comprehension and acquisition in DLD.

Attention to audiovisual speech shapes neural processing through feedback-feedforward loops between different nodes of the speech network

Selective attention-related top-down modulation plays a significant role in separating relevant speech from irrelevant background speech when vocal attributes separating concurrent speakers are small and continuously evolving. Electrophysiological studies have shown that such top-down modulation enhances neural tracking of attended speech. Yet, the specific cortical regions involved remain unclear due to the limited spatial resolution of most electrophysiological techniques. To overcome such limitations, we collected both electroencephalography (EEG) (high temporal resolution) and functional magnetic resonance imaging (fMRI) (high spatial resolution), while human participants selectively attended to speakers in audiovisual scenes containing overlapping cocktail party speech. To utilise the advantages of the respective techniques, we analysed neural tracking of speech using the EEG data and performed representational dissimilarity-based EEG-fMRI fusion. We observed that attention enhanced neural tracking and modulated EEG correlates throughout the latencies studied. Further, attention-related enhancement of neural tracking fluctuated in predictable temporal profiles. We discuss how such temporal dynamics could arise from a combination of interactions between attention and prediction as well as plastic properties of the auditory cortex. EEG-fMRI fusion revealed attention-related iterative feedforward-feedback loops between hierarchically organised nodes of the ventral auditory object related processing stream. Our findings support models where attention facilitates dynamic neural changes in the auditory cortex, ultimately aiding discrimination of relevant sounds from irrelevant ones while conserving neural resources.

Contributions of listening effort and intelligibility to cortical tracking of speech in adverse listening conditions

Cortical tracking of speech is vital for speech segmentation and is linked to speech intelligibility. However, there is no clear consensus as to whether reduced intelligibility leads to a decrease or an increase in cortical speech tracking, warranting further investigation of the factors influencing this relationship. One such factor is listening effort, defined as the cognitive resources necessary for speech comprehension, and reported to have a strong negative correlation with speech intelligibility. Yet, no studies have examined the relationship between speech intelligibility, listening effort, and cortical tracking of speech. The aim of the present study was thus to examine these factors in quiet and distinct adverse listening conditions. Forty-nine normal hearing adults listened to sentences produced casually, presented in quiet and two adverse listening conditions: cafeteria noise and reverberant speech. Electrophysiological responses were registered with electroencephalogram, and listening effort was estimated subjectively using self-reported scores and objectively using pupillometry. Results indicated varying impacts of adverse conditions on intelligibility, listening effort, and cortical tracking of speech, depending on the preservation of the speech temporal envelope. The more distorted envelope in the reverberant condition led to higher listening effort, as reflected in higher subjective scores, increased pupil diameter, and stronger cortical tracking of speech in the delta band. These findings suggest that using measures of listening effort in addition to those of intelligibility is useful for interpreting cortical tracking of speech results. Moreover, reading and phonological skills of participants were positively correlated with listening effort in the cafeteria condition, suggesting a special role of expert language skills in processing speech in this noisy condition. Implications for future research and theories linking atypical cortical tracking of speech and reading disorders are further discussed.

Reliability and generalizability of neural speech tracking in younger and older adults

Neural tracking of spoken speech is considered a potential clinical biomarker for speech-processing difficulties, but the reliability of neural speech tracking is unclear. Here, younger and older adults listened to stories in two sessions while electroencephalography was recorded to investigate the reliability and generalizability of neural speech tracking. Speech tracking amplitude was larger for older than younger adults, consistent with an age-related loss of inhibition. The reliability of neural speech tracking was moderate (ICC ∼0.5-0.75) and tended to be higher for older adults. However, reliability was lower for speech tracking than for neural responses to noise bursts (ICC >0.8), which we used as a benchmark for maximum reliability. Neural speech tracking generalized moderately across different stories (ICC ∼0.5-0.6), which appeared greatest for audiobook-like stories spoken by the same person. Hence, a variety of stories could possibly be used for clinical assessments. Overall, the current data are important for developing a biomarker of speech processing but suggest that further work is needed to increase the reliability to meet clinical standards.

Original speech and its echo are segregated and separately processed in the human brain

Speech recognition crucially relies on slow temporal modulations (<16 Hz) in speech. Recent studies, however, have demonstrated that the long-delay echoes, which are common during online conferencing, can eliminate crucial temporal modulations in speech but do not affect speech intelligibility. Here, we investigated the underlying neural mechanisms. MEG experiments demonstrated that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be fully explained by basic neural adaptation mechanisms. Furthermore, cortical responses to echoic speech can be better explained by a model that segregates speech from its echo than by a model that encodes echoic speech as a whole. The speech segregation effect was observed even when attention was diverted but would disappear when segregation cues, i.e., speech fine structure, were removed. These results strongly suggested that, through mechanisms such as stream segregation, the auditory system can build an echo-insensitive representation of speech envelope, which can support reliable speech recognition.

Subcortical responses to music and speech are alike while cortical responses diverge

Music and speech are encountered daily and are unique to human beings. Both are transformed by the auditory pathway from an initial acoustical encoding to higher level cognition. Studies of cortex have revealed distinct brain responses to music and speech, but differences may emerge in the cortex or may be inherited from different subcortical encoding. In the first part of this study, we derived the human auditory brainstem response (ABR), a measure of subcortical encoding, to recorded music and speech using two analysis methods. The first method, described previously and acoustically based, yielded very different ABRs between the two sound classes. The second method, however, developed here and based on a physiological model of the auditory periphery, gave highly correlated responses to music and speech. We determined the superiority of the second method through several metrics, suggesting there is no appreciable impact of stimulus class (i.e., music vs speech) on the way stimulus acoustics are encoded subcortically. In this study's second part, we considered the cortex. Our new analysis method resulted in cortical music and speech responses becoming more similar but with remaining differences. The subcortical and cortical results taken together suggest that there is evidence for stimulus-class dependent processing of music and speech at the cortical but not subcortical level.

Neural tracking measures of speech intelligibility: Manipulating intelligibility while keeping acoustics unchanged

Neural speech tracking has advanced our understanding of how our brains rapidly map an acoustic speech signal onto linguistic representations and ultimately meaning. It remains unclear, however, how speech intelligibility is related to the corresponding neural responses. Many studies addressing this question vary the level of intelligibility by manipulating the acoustic waveform, but this makes it difficult to cleanly disentangle the effects of intelligibility from underlying acoustical confounds. Here, using magnetoencephalography recordings, we study neural measures of speech intelligibility by manipulating intelligibility while keeping the acoustics strictly unchanged. Acoustically identical degraded speech stimuli (three-band noise-vocoded, ~20 s duration) are presented twice, but the second presentation is preceded by the original (nondegraded) version of the speech. This intermediate priming, which generates a "pop-out" percept, substantially improves the intelligibility of the second degraded speech passage. We investigate how intelligibility and acoustical structure affect acoustic and linguistic neural representations using multivariate temporal response functions (mTRFs). As expected, behavioral results confirm that perceived speech clarity is improved by priming. mTRFs analysis reveals that auditory (speech envelope and envelope onset) neural representations are not affected by priming but only by the acoustics of the stimuli (bottom-up driven). Critically, our findings suggest that segmentation of sounds into words emerges with better speech intelligibility, and most strongly at the later (~400 ms latency) word processing stage, in prefrontal cortex, in line with engagement of top-down mechanisms associated with priming. Taken together, our results show that word representations may provide some objective measures of speech comprehension.

Emergence of the cortical encoding of phonetic features in the first year of life

Even prior to producing their first words, infants are developing a sophisticated speech processing system, with robust word recognition present by 4-6 months of age. These emergent linguistic skills, observed with behavioural investigations, are likely to rely on increasingly sophisticated neural underpinnings. The infant brain is known to robustly track the speech envelope, however previous cortical tracking studies were unable to demonstrate the presence of phonetic feature encoding. Here we utilise temporal response functions computed from electrophysiological responses to nursery rhymes to investigate the cortical encoding of phonetic features in a longitudinal cohort of infants when aged 4, 7 and 11 months, as well as adults. The analyses reveal an increasingly detailed and acoustically invariant phonetic encoding emerging over the first year of life, providing neurophysiological evidence that the pre-verbal human cortex learns phonetic categories. By contrast, we found no credible evidence for age-related increases in cortical tracking of the acoustic spectrogram.

Distinct roles of delta- and theta-band neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing

The brain tracks and encodes multi-level speech features during spoken language processing. It is evident that this speech tracking is dominant at low frequencies (<8 Hz) including delta and theta bands. Recent research has demonstrated distinctions between delta- and theta-band tracking but has not elucidated how they differentially encode speech across linguistic levels. Here, we hypothesised that delta-band tracking encodes prediction errors (enhanced processing of unexpected features) while theta-band tracking encodes neural sharpening (enhanced processing of expected features) when people perceive speech with different linguistic contents. EEG responses were recorded when normal-hearing participants attended to continuous auditory stimuli that contained different phonological/morphological and semantic contents: (1) real-words, (2) pseudo-words and (3) time-reversed speech. We employed multivariate temporal response functions to measure EEG reconstruction accuracies in response to acoustic (spectrogram), phonetic and phonemic features with the partialling procedure that singles out unique contributions of individual features. We found higher delta-band accuracies for pseudo-words than real-words and time-reversed speech, especially during encoding of phonetic features. Notably, individual time-lag analyses showed that significantly higher accuracies for pseudo-words than real-words started at early processing stages for phonetic encoding (<100 ms post-feature) and later stages for acoustic and phonemic encoding (>200 and 400 ms post-feature, respectively). Theta-band accuracies, on the other hand, were higher when stimuli had richer linguistic content (real-words > pseudo-words > time-reversed speech). Such effects also started at early stages (<100 ms post-feature) during encoding of all individual features or when all features were combined. We argue these results indicate that delta-band tracking may play a role in predictive coding leading to greater tracking of pseudo-words due to the presence of unexpected/unpredicted semantic information, while theta-band tracking encodes sharpened signals caused by more expected phonological/morphological and semantic contents. Early presence of these effects reflects rapid computations of sharpening and prediction errors. Moreover, by measuring changes in EEG alpha power, we did not find evidence that the observed effects can be solitarily explained by attentional demands or listening efforts. Finally, we used directed information analyses to illustrate feedforward and feedback information transfers between prediction errors and sharpening across linguistic levels, showcasing how our results fit with the hierarchical Predictive Coding framework. Together, we suggest the distinct roles of delta and theta neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

Eelbrain, a Python toolkit for time-continuous analysis with temporal response functions

Even though human experience unfolds continuously in time, it is not strictly linear; instead, it entails cascading processes building hierarchical cognitive structures. For instance, during speech perception, humans transform a continuously varying acoustic signal into phonemes, words, and meaning, and these levels all have distinct but interdependent temporal structures. Time-lagged regression using temporal response functions (TRFs) has recently emerged as a promising tool for disentangling electrophysiological brain responses related to such complex models of perception. Here, we introduce the Eelbrain Python toolkit, which makes this kind of analysis easy and accessible. We demonstrate its use, using continuous speech as a sample paradigm, with a freely available EEG dataset of audiobook listening. A companion GitHub repository provides the complete source code for the analysis, from raw data to group-level statistics. More generally, we advocate a hypothesis-driven approach in which the experimenter specifies a hierarchy of time-continuous representations that are hypothesized to have contributed to brain responses, and uses those as predictor variables for the electrophysiological signal. This is analogous to a multiple regression problem, but with the addition of a time dimension. TRF analysis decomposes the brain signal into distinct responses associated with the different predictor variables by estimating a multivariate TRF (mTRF), quantifying the influence of each predictor on brain responses as a function of time(-lags). This allows asking two questions about the predictor variables: (1) Is there a significant neural representation corresponding to this predictor variable? And if so, (2) what are the temporal characteristics of the neural response associated with it? Thus, different predictor variables can be systematically combined and evaluated to jointly model neural processing at multiple hierarchical levels. We discuss applications of this approach, including the potential for linking algorithmic/representational theories at different cognitive levels to brain responses through computational models with appropriate linking hypotheses.

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.

EEG-based speaker-listener neural coupling reflects speech-selective attentional mechanisms beyond the speech stimulus

When we pay attention to someone, do we focus only on the sound they make, the word they use, or do we form a mental space shared with the speaker we want to pay attention to? Some would argue that the human language is no other than a simple signal, but others claim that human beings understand each other because they form a shared mental ground between the speaker and the listener. Our study aimed to explore the neural mechanisms of speech-selective attention by investigating the electroencephalogram-based neural coupling between the speaker and the listener in a cocktail party paradigm. The temporal response function method was employed to reveal how the listener was coupled to the speaker at the neural level. The results showed that the neural coupling between the listener and the attended speaker peaked 5 s before speech onset at the delta band over the left frontal region, and was correlated with speech comprehension performance. In contrast, the attentional processing of speech acoustics and semantics occurred primarily at a later stage after speech onset and was not significantly correlated with comprehension performance. These findings suggest a predictive mechanism to achieve speaker-listener neural coupling for successful speech comprehension.

Neural speech tracking shifts from the syllabic to the modulation rate of speech as intelligibility decreases

The most prominent acoustic features in speech are intensity modulations, represented by the amplitude envelope of speech. Synchronization of neural activity with these modulations supports speech comprehension. As the acoustic modulation of speech is related to the production of syllables, investigations of neural speech tracking commonly do not distinguish between lower-level acoustic (envelope modulation) and higher-level linguistic (syllable rate) information. Here we manipulated speech intelligibility using noise-vocoded speech and investigated the spectral dynamics of neural speech processing, across two studies at cortical and subcortical levels of the auditory hierarchy, using magnetoencephalography. Overall, cortical regions mostly track the syllable rate, whereas subcortical regions track the acoustic envelope. Furthermore, with less intelligible speech, tracking of the modulation rate becomes more dominant. Our study highlights the importance of distinguishing between envelope modulation and syllable rate and provides novel possibilities to better understand differences between auditory processing and speech/language processing disorders.

Neural envelope tracking predicts speech intelligibility and hearing aid benefit in children with hearing loss

Early assessment of hearing aid benefit is crucial, as the extent to which hearing aids provide audible speech information predicts speech and language outcomes. A growing body of research has proposed neural envelope tracking as an objective measure of speech intelligibility, particularly for individuals unable to provide reliable behavioral feedback. However, its potential for evaluating speech intelligibility and hearing aid benefit in children with hearing loss remains unexplored. In this study, we investigated neural envelope tracking in children with permanent hearing loss through two separate experiments. EEG data were recorded while children listened to age-appropriate stories (Experiment 1) or an animated movie (Experiment 2) under aided and unaided conditions (using personal hearing aids) at multiple stimulus intensities. Neural envelope tracking was evaluated using a linear decoder reconstructing the speech envelope from the EEG in the delta band (0.5-4 Hz). Additionally, we calculated temporal response functions (TRFs) to investigate the spatio-temporal dynamics of the response. In both experiments, neural tracking increased with increasing stimulus intensity, but only in the unaided condition. In the aided condition, neural tracking remained stable across a wide range of intensities, as long as speech intelligibility was maintained. Similarly, TRF amplitudes increased with increasing stimulus intensity in the unaided condition, while in the aided condition significant differences were found in TRF latency rather than TRF amplitude. This suggests that decreasing stimulus intensity does not necessarily impact neural tracking. Furthermore, the use of personal hearing aids significantly enhanced neural envelope tracking, particularly in challenging speech conditions that would be inaudible when unaided. Finally, we found a strong correlation between neural envelope tracking and behaviorally measured speech intelligibility for both narrated stories (Experiment 1) and movie stimuli (Experiment 2). Altogether, these findings indicate that neural envelope tracking could be a valuable tool for predicting speech intelligibility benefits derived from personal hearing aids in hearing-impaired children. Incorporating narrated stories or engaging movies expands the accessibility of these methods even in clinical settings, offering new avenues for using objective speech measures to guide pediatric audiology decision-making.

Neural Tracking Measures of Speech Intelligibility: Manipulating Intelligibility while Keeping Acoustics Unchanged

Neural speech tracking has advanced our understanding of how our brains rapidly map an acoustic speech signal onto linguistic representations and ultimately meaning. It remains unclear, however, how speech intelligibility is related to the corresponding neural responses. Many studies addressing this question vary the level of intelligibility by manipulating the acoustic waveform, but this makes it difficult to cleanly disentangle effects of intelligibility from underlying acoustical confounds. Here, using magnetoencephalography (MEG) recordings, we study neural measures of speech intelligibility by manipulating intelligibility while keeping the acoustics strictly unchanged. Acoustically identical degraded speech stimuli (three-band noise vocoded, ~20 s duration) are presented twice, but the second presentation is preceded by the original (non-degraded) version of the speech. This intermediate priming, which generates a 'pop-out' percept, substantially improves the intelligibility of the second degraded speech passage. We investigate how intelligibility and acoustical structure affects acoustic and linguistic neural representations using multivariate Temporal Response Functions (mTRFs). As expected, behavioral results confirm that perceived speech clarity is improved by priming. TRF analysis reveals that auditory (speech envelope and envelope onset) neural representations are not affected by priming, but only by the acoustics of the stimuli (bottom-up driven). Critically, our findings suggest that segmentation of sounds into words emerges with better speech intelligibility, and most strongly at the later (~400 ms latency) word processing stage, in prefrontal cortex (PFC), in line with engagement of top-down mechanisms associated with priming. Taken together, our results show that word representations may provide some objective measures of speech comprehension.

Speech Reception in Young Children with Autism Is Selectively Indexed by a Neural Oscillation Coupling Anomaly

Communication difficulties are one of the core criteria in diagnosing autism spectrum disorder (ASD), and are often characterized by speech reception difficulties, whose biological underpinnings are not yet identified. This deficit could denote atypical neuronal ensemble activity, as reflected by neural oscillations. Atypical cross-frequency oscillation coupling, in particular, could disrupt the joint tracking and prediction of dynamic acoustic stimuli, a dual process that is essential for speech comprehension. Whether such oscillatory anomalies already exist in very young children with ASD, and with what specificity they relate to individual language reception capacity is unknown. We collected neural activity data using electroencephalography (EEG) in 64 very young children with and without ASD (mean age 3; 17 females, 47 males) while they were exposed to naturalistic-continuous speech. EEG power of frequency bands typically associated with phrase-level chunking (δ, 1-3 Hz), phonemic encoding (low-γ, 25-35 Hz), and top-down control (β, 12-20 Hz) were markedly reduced in ASD relative to typically developing (TD) children. Speech neural tracking by δ and θ (4-8 Hz) oscillations was also weaker in ASD compared with TD children. After controlling gaze-pattern differences, we found that the classical θ/γ coupling was replaced by an atypical β/γ coupling in children with ASD. This anomaly was the single most specific predictor of individual speech reception difficulties in ASD children. These findings suggest that early interventions (e.g., neurostimulation) targeting the disruption of β/γ coupling and the upregulation of θ/γ coupling could improve speech processing coordination in young children with ASD and help them engage in oral interactions.SIGNIFICANCE STATEMENT Very young children already present marked alterations of neural oscillatory activity in response to natural speech at the time of autism spectrum disorder (ASD) diagnosis. Hierarchical processing of phonemic-range and syllabic-range information (θ/γ coupling) is disrupted in ASD children. Abnormal bottom-up (low-γ) and top-down (low-β) coordination specifically predicts speech reception deficits in very young ASD children, and no other cognitive deficit.

A review of auditory processing and cognitive change during normal ageing, and the implications for setting hearing aids for older adults

Throughout our adult lives there is a decline in peripheral hearing, auditory processing and elements of cognition that support listening ability. Audiometry provides no information about the status of auditory processing and cognition, and older adults often struggle with complex listening situations, such as speech in noise perception, even if their peripheral hearing appears normal. Hearing aids can address some aspects of peripheral hearing impairment and improve signal-to-noise ratios. However, they cannot directly enhance central processes and may introduce distortion to sound that might act to undermine listening ability. This review paper highlights the need to consider the distortion introduced by hearing aids, specifically when considering normally-ageing older adults. We focus on patients with age-related hearing loss because they represent the vast majority of the population attending audiology clinics. We believe that it is important to recognize that the combination of peripheral and central, auditory and cognitive decline make older adults some of the most complex patients seen in audiology services, so they should not be treated as "standard" despite the high prevalence of age-related hearing loss. We argue that a primary concern should be to avoid hearing aid settings that introduce distortion to speech envelope cues, which is not a new concept. The primary cause of distortion is the speed and range of change to hearing aid amplification (i.e., compression). We argue that slow-acting compression should be considered as a default for some users and that other advanced features should be reconsidered as they may also introduce distortion that some users may not be able to tolerate. We discuss how this can be incorporated into a pragmatic approach to hearing aid fitting that does not require increased loading on audiology services.

Effects of aging on cortical representations of continuous speech

Understanding speech in a noisy environment is crucial in day-to-day interactions and yet becomes more challenging with age, even for healthy aging. Age-related changes in the neural mechanisms that enable speech-in-noise listening have been investigated previously; however, the extent to which age affects the timing and fidelity of encoding of target and interfering speech streams is not well understood. Using magnetoencephalography (MEG), we investigated how continuous speech is represented in auditory cortex in the presence of interfering speech in younger and older adults. Cortical representations were obtained from neural responses that time-locked to the speech envelopes with speech envelope reconstruction and temporal response functions (TRFs). TRFs showed three prominent peaks corresponding to auditory cortical processing stages: early (∼50 ms), middle (∼100 ms), and late (∼200 ms). Older adults showed exaggerated speech envelope representations compared with younger adults. Temporal analysis revealed both that the age-related exaggeration starts as early as ∼50 ms and that older adults needed a substantially longer integration time window to achieve their better reconstruction of the speech envelope. As expected, with increased speech masking envelope reconstruction for the attended talker decreased and all three TRF peaks were delayed, with aging contributing additionally to the reduction. Interestingly, for older adults the late peak was delayed, suggesting that this late peak may receive contributions from multiple sources. Together these results suggest that there are several mechanisms at play compensating for age-related temporal processing deficits at several stages but which are not able to fully reestablish unimpaired speech perception.NEW & NOTEWORTHY We observed age-related changes in cortical temporal processing of continuous speech that may be related to older adults' difficulty in understanding speech in noise. These changes occur in both timing and strength of the speech representations at different cortical processing stages and depend on both noise condition and selective attention. Critically, their dependence on noise condition changes dramatically among the early, middle, and late cortical processing stages, underscoring how aging differentially affects these stages.

Delta-band neural envelope tracking predicts speech intelligibility in noise in preschoolers

Behavioral tests are currently the gold standard in measuring speech intelligibility. However, these tests can be difficult to administer in young children due to factors such as motivation, linguistic knowledge and cognitive skills. It has been shown that measures of neural envelope tracking can be used to predict speech intelligibility and overcome these issues. However, its potential as an objective measure for speech intelligibility in noise remains to be investigated in preschool children. Here, we evaluated neural envelope tracking as a function of signal-to-noise ratio (SNR) in 14 5-year-old children. We examined EEG responses to natural, continuous speech presented at different SNRs ranging from -8 (very difficult) to 8 dB SNR (very easy). As expected delta band (0.5-4 Hz) tracking increased with increasing stimulus SNR. However, this increase was not strictly monotonic as neural tracking reached a plateau between 0 and 4 dB SNR, similarly to the behavioral speech intelligibility outcomes. These findings indicate that neural tracking in the delta band remains stable, as long as the acoustical degradation of the speech signal does not reflect significant changes in speech intelligibility. Theta band tracking (4-8 Hz), on the other hand, was found to be drastically reduced and more easily affected by noise in children, making it less reliable as a measure of speech intelligibility. By contrast, neural envelope tracking in the delta band was directly associated with behavioral measures of speech intelligibility. This suggests that neural envelope tracking in the delta band is a valuable tool for evaluating speech-in-noise intelligibility in preschoolers, highlighting its potential as an objective measure of speech in difficult-to-test populations.

Speech intelligibility changes the temporal evolution of neural speech tracking

Listening to speech with poor signal quality is challenging. Neural speech tracking of degraded speech has been used to advance the understanding of how brain processes and speech intelligibility are interrelated. However, the temporal dynamics of neural speech tracking and their relation to speech intelligibility are not clear. In the present MEG study, we exploited temporal response functions (TRFs), which has been used to describe the time course of speech tracking on a gradient from intelligible to unintelligible degraded speech. In addition, we used inter-related facets of neural speech tracking (e.g., speech envelope reconstruction, speech-brain coherence, and components of broadband coherence spectra) to endorse our findings in TRFs. Our TRF analysis yielded marked temporally differential effects of vocoding: ∼50-110 ms (M50TRF), ∼175-230 ms (M200TRF), and ∼315-380 ms (M350TRF). Reduction of intelligibility went along with large increases of early peak responses M50TRF, but strongly reduced responses in M200TRF. In the late responses M350TRF, the maximum response occurred for degraded speech that was still comprehensible then declined with reduced intelligibility. Furthermore, we related the TRF components to our other neural "tracking" measures and found that M50TRF and M200TRF play a differential role in the shifting center frequency of the broadband coherence spectra. Overall, our study highlights the importance of time-resolved computation of neural speech tracking and decomposition of coherence spectra and provides a better understanding of degraded speech processing.

Two stages of speech envelope tracking in human auditory cortex modulated by speech intelligibility

The envelope is essential for speech perception. Recent studies have shown that cortical activity can track the acoustic envelope. However, whether the tracking strength reflects the extent of speech intelligibility processing remains controversial. Here, using stereo-electroencephalogram technology, we directly recorded the activity in human auditory cortex while subjects listened to either natural or noise-vocoded speech. These 2 stimuli have approximately identical envelopes, but the noise-vocoded speech does not have speech intelligibility. According to the tracking lags, we revealed 2 stages of envelope tracking: an early high-γ (60-140 Hz) power stage that preferred the noise-vocoded speech and a late θ (4-8 Hz) phase stage that preferred the natural speech. Furthermore, the decoding performance of high-γ power was better in primary auditory cortex than in nonprimary auditory cortex, consistent with its short tracking delay, while θ phase showed better decoding performance in right auditory cortex. In addition, high-γ responses with sustained temporal profiles in nonprimary auditory cortex were dominant in both envelope tracking and decoding. In sum, we suggested a functional dissociation between high-γ power and θ phase: the former reflects fast and automatic processing of brief acoustic features, while the latter correlates to slow build-up processing facilitated by speech intelligibility.

Reduction in sound discrimination in noise is related to envelope similarity and not to a decrease in envelope tracking abilities

Humans and animals constantly face challenging acoustic environments, such as various background noises, that impair the detection, discrimination and identification of behaviourally relevant sounds. Here, we disentangled the role of temporal envelope tracking in the reduction in neuronal and behavioural discrimination between communication sounds in situations of acoustic degradations. By collecting neuronal activity from six different levels of the auditory system, from the auditory nerve up to the secondary auditory cortex, in anaesthetized guinea-pigs, we found that tracking of slow changes of the temporal envelope is a general functional property of auditory neurons for encoding communication sounds in quiet conditions and in adverse, challenging conditions. Results from a go/no-go sound discrimination task in mice support the idea that the loss of distinct slow envelope cues in noisy conditions impacted the discrimination performance. Together, these results suggest that envelope tracking is potentially a universal mechanism operating in the central auditory system, which allows the detection of any between-stimulus difference in the slow envelope and thus copes with degraded conditions. KEY POINTS: In quiet conditions, envelope tracking in the low amplitude modulation range (<20 Hz) is correlated with the neuronal discrimination between communication sounds as quantified by mutual information from the cochlear nucleus up to the auditory cortex. At each level of the auditory system, auditory neurons retain their abilities to track the communication sound envelopes in situations of acoustic degradation, such as vocoding and the addition of masking noises up to a signal-to-noise ratio of -10 dB. In noisy conditions, the increase in between-stimulus envelope similarity explains the reduction in both behavioural and neuronal discrimination in the auditory system. Envelope tracking can be viewed as a universal mechanism that allows neural and behavioural discrimination as long as the temporal envelope of communication sounds displays some differences.

Cortical tracking of lexical speech units in a multi-talker background is immature in school-aged children

Children have more difficulty perceiving speech in noise than adults. Whether this difficulty relates to an immature processing of prosodic or linguistic elements of the attended speech is still unclear. To address the impact of noise on linguistic processing per se, we assessed how babble noise impacts the cortical tracking of intelligible speech devoid of prosody in school-aged children and adults. Twenty adults and twenty children (7-9 years) listened to synthesized French monosyllabic words presented at 2.5 Hz, either randomly or in 4-word hierarchical structures wherein 2 words formed a phrase at 1.25 Hz, and 2 phrases formed a sentence at 0.625 Hz, with or without babble noise. Neuromagnetic responses to words, phrases and sentences were identified and source-localized. Children and adults displayed significant cortical tracking of words in all conditions, and of phrases and sentences only when words formed meaningful sentences. In children compared with adults, the cortical tracking was lower for all linguistic units in conditions without noise. In the presence of noise, the cortical tracking was similarly reduced for sentence units in both groups, but remained stable for phrase units. Critically, when there was noise, adults increased the cortical tracking of monosyllabic words in the inferior frontal gyri and supratemporal auditory cortices but children did not. This study demonstrates that the difficulties of school-aged children in understanding speech in a multi-talker background might be partly due to an immature tracking of lexical but not supra-lexical linguistic units.

Compromised word-level neural tracking in the high-gamma band for children with attention deficit hyperactivity disorder

Children with attention deficit hyperactivity disorder (ADHD) exhibit pervasive difficulties in speech perception. Given that speech processing involves both acoustic and linguistic stages, it remains unclear which stage of speech processing is impaired in children with ADHD. To investigate this issue, we measured neural tracking of speech at syllable and word levels using electroencephalography (EEG), and evaluated the relationship between neural responses and ADHD symptoms in 6-8 years old children. Twenty-three children participated in the current study, and their ADHD symptoms were assessed with SNAP-IV questionnaires. In the experiment, the children listened to hierarchical speech sequences in which syllables and words were, respectively, repeated at 2.5 and 1.25 Hz. Using frequency domain analyses, reliable neural tracking of syllables and words was observed in both the low-frequency band (<4 Hz) and the high-gamma band (70-160 Hz). However, the neural tracking of words in the high-gamma band showed an anti-correlation with the ADHD symptom scores of the children. These results indicate that ADHD prominently impairs cortical encoding of linguistic information (e.g., words) in speech perception.

Working memory asymmetrically modulates auditory and linguistic processing of speech

Working memory load can modulate speech perception. However, since speech perception and working memory are both complex functions, it remains elusive how each component of the working memory system interacts with each speech processing stage. To investigate this issue, we concurrently measure how the working memory load modulates neural activity tracking three levels of linguistic units, i.e., syllables, phrases, and sentences, using a multiscale frequency-tagging approach. Participants engage in a sentence comprehension task and the working memory load is manipulated by asking them to memorize either auditory verbal sequences or visual patterns. It is found that verbal and visual working memory load modulate speech processing in similar manners: Higher working memory load attenuates neural activity tracking of phrases and sentences but enhances neural activity tracking of syllables. Since verbal and visual WM load similarly influence the neural responses to speech, such influences may derive from the domain-general component of WM system. More importantly, working memory load asymmetrically modulates lower-level auditory encoding and higher-level linguistic processing of speech, possibly reflecting reallocation of attention induced by mnemonic load.

More than words: Neurophysiological correlates of semantic dissimilarity depend on comprehension of the speech narrative

Speech comprehension relies on the ability to understand words within a coherent context. Recent studies have attempted to obtain electrophysiological indices of this process by modelling how brain activity is affected by a word's semantic dissimilarity to preceding words. Although the resulting indices appear robust and are strongly modulated by attention, it remains possible that, rather than capturing the contextual understanding of words, they may actually reflect word-to-word changes in semantic content without the need for a narrative-level understanding on the part of the listener. To test this, we recorded electroencephalography from subjects who listened to speech presented in either its original, narrative form, or after scrambling the word order by varying amounts. This manipulation affected the ability of subjects to comprehend the speech narrative but not the ability to recognise individual words. Neural indices of semantic understanding and low-level acoustic processing were derived for each scrambling condition using the temporal response function. Signatures of semantic processing were observed when speech was unscrambled or minimally scrambled and subjects understood the speech. The same markers were absent for higher scrambling levels as speech comprehension dropped. In contrast, word recognition remained high and neural measures related to envelope tracking did not vary significantly across scrambling conditions. This supports the previous claim that electrophysiological indices based on the semantic dissimilarity of words to their context reflect a listener's understanding of those words relative to that context. It also highlights the relative insensitivity of neural measures of low-level speech processing to speech comprehension.

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.

Neural tracking as a diagnostic tool to assess the auditory pathway

When a person listens to sound, the brain time-locks to specific aspects of the sound. This is called neural tracking and it can be investigated by analysing neural responses (e.g., measured by electroencephalography) to continuous natural speech. Measures of neural tracking allow for an objective investigation of a range of auditory and linguistic processes in the brain during natural speech perception. This approach is more ecologically valid than traditional auditory evoked responses and has great potential for research and clinical applications. This article reviews the neural tracking framework and highlights three prominent examples of neural tracking analyses: neural tracking of the fundamental frequency of the voice (f0), the speech envelope and linguistic features. Each of these analyses provides a unique point of view into the human brain's hierarchical stages of speech processing. F0-tracking assesses the encoding of fine temporal information in the early stages of the auditory pathway, i.e., from the auditory periphery up to early processing in the primary auditory cortex. Envelope tracking reflects bottom-up and top-down speech-related processes in the auditory cortex and is likely necessary but not sufficient for speech intelligibility. Linguistic feature tracking (e.g. word or phoneme surprisal) relates to neural processes more directly related to speech intelligibility. Together these analyses form a multi-faceted objective assessment of an individual's auditory and linguistic processing.

Timing of brain entrainment to the speech envelope during speaking, listening and self-listening

⁠This study investigates the dynamics of speech envelope tracking during speech production, listening and self-listening. We use a paradigm in which participants listen to natural speech (Listening), produce natural speech (Speech Production), and listen to the playback of their own speech (Self-Listening), all while their neural activity is recorded with EEG. After time-locking EEG data collection and auditory recording and playback, we used a Gaussian copula mutual information measure to estimate the relationship between information content in the EEG and auditory signals. In the 2-10 Hz frequency range, we identified different latencies for maximal speech envelope tracking during speech production and speech perception. Maximal speech tracking takes place approximately 110 ms after auditory presentation during perception and 25 ms before vocalisation during speech production. These results describe a specific timeline for speech tracking in speakers and listeners in line with the idea of a speech chain and hence, delays in communication.

Modelling neural entrainment and its persistence: influence of frequency of stimulation and phase at the stimulus offset

Neural entrainment, the synchronization of brain oscillations to the frequency of an external stimuli, is a key mechanism that shapes perceptual and cognitive processes.Objective.Using simulations, we investigated the dynamics of neural entrainment, particularly the period following the end of the stimulation, since the persistence (reverberation) of neural entrainment may condition future sensory representations based on predictions about stimulus rhythmicity.Methods.Neural entrainment was assessed using a modified Jansen-Rit neural mass model (NMM) of coupled cortical columns, in which the spectral features of the output resembled that of the electroencephalogram (EEG). We evaluated spectro-temporal features of entrainment as a function of the stimulation frequency, the resonant frequency of the neural populations comprising the NMM, and the coupling strength between cortical columns. Furthermore, we tested if the entrainment persistence depended on the phase of the EEG-like oscillation at the time the stimulus ended.Main Results.The entrainment of the column that received the stimulation was maximum when the frequency of the entrainer was within a narrow range around the resonant frequency of the column. When this occurred, entrainment persisted for several cycles after the stimulus terminated, and the propagation of the entrainment to other columns was facilitated. Propagation also depended on the resonant frequency of the second column, and the coupling strength between columns. The duration of the persistence of the entrainment depended on the phase of the neural oscillation at the time the entrainer terminated, such that falling phases (fromπ/2 to 3π/2 in a sine function) led to longer persistence than rising phases (from 0 toπ/2 and 3π/2 to 2π).Significance.The study bridges between models of neural oscillations and empirical electrophysiology, providing insights to the mechanisms underlying neural entrainment and the use of rhythmic sensory stimulation for neuroenhancement.

Auditory timing-tuned neural responses in the human auditory cortices

Perception of sub-second auditory event timing supports multisensory integration, and speech and music perception and production. Neural populations tuned for the timing (duration and rate) of visual events were recently described in several human extrastriate visual areas. Here we ask whether the brain also contains neural populations tuned for auditory event timing, and whether these are shared with visual timing. Using 7T fMRI, we measured responses to white noise bursts of changing duration and rate. We analyzed these responses using neural response models describing different parametric relationships between event timing and neural response amplitude. This revealed auditory timing-tuned responses in the primary auditory cortex, and auditory association areas of the belt, parabelt and premotor cortex. While these areas also showed tonotopic tuning for auditory pitch, pitch and timing preferences were not consistently correlated. Auditory timing-tuned response functions differed between these areas, though without clear hierarchical integration of responses. The similarity of auditory and visual timing tuned responses, together with the lack of overlap between the areas showing these responses for each modality, suggests modality-specific responses to event timing are computed similarly but from different sensory inputs, and then transformed differently to suit the needs of each modality.

Degradation levels of continuous speech affect neural speech tracking and alpha power differently

Making sense of a poor auditory signal can pose a challenge. Previous attempts to quantify speech intelligibility in neural terms have usually focused on one of two measures, namely low-frequency speech-brain synchronization or alpha power modulations. However, reports have been mixed concerning the modulation of these measures, an issue aggravated by the fact that they have normally been studied separately. We present two MEG studies analyzing both measures. In study 1, participants listened to unimodal auditory speech with three different levels of degradation (original, 7-channel and 3-channel vocoding). Intelligibility declined with declining clarity, but speech was still intelligible to some extent even for the lowest clarity level (3-channel vocoding). Low-frequency (1-7 Hz) speech tracking suggested a U-shaped relationship with strongest effects for the medium-degraded speech (7-channel) in bilateral auditory and left frontal regions. To follow up on this finding, we implemented three additional vocoding levels (5-channel, 2-channel and 1-channel) in a second MEG study. Using this wider range of degradation, the speech-brain synchronization showed a similar pattern as in study 1, but further showed that when speech becomes unintelligible, synchronization declines again. The relationship differed for alpha power, which continued to decrease across vocoding levels reaching a floor effect for 5-channel vocoding. Predicting subjective intelligibility based on models either combining both measures or each measure alone showed superiority of the combined model. Our findings underline that speech tracking and alpha power are modified differently by the degree of degradation of continuous speech but together contribute to the subjective speech understanding.

Predicting speech intelligibility from a selective attention decoding paradigm in cochlear implant users

OBJECTIVES

Electroencephalography (EEG) can be used to decode selective attention in cochlear implant (CI) users. This work investigates if selective attention to an attended speech source in the presence of a concurrent speech source can predict speech understanding in CI users.

APPROACH

CI users were instructed to attend to one out of two speech streams while EEG was recorded. Both speech streams were presented to the same ear and at different signal to interference ratios (SIRs). Speech envelope reconstruction of the to-be-attended speech from EEG was obtained by training decoders using regularized least squares. The correlation coefficient between the reconstructed and the attended (ρ_(A_SIR )) or the unattended (ρ_(U_SIR )) speech stream at each SIR was computed. Additionally, we computed the difference correlation coefficient at the same 〖(ρ〗_Diff= ρ_(A_SIR )-ρ_(U_SIR )) and opposite SIR (ρ_DiffOpp= ρ_(A_SIR )-ρ_(U_(-SIR) )). ρ_Diff compares the attended and unattended correlation coefficient to speech sources presented at different presentation levels depending on SIR. In contrast, ρ_DiffOpp compares the attended and unattended correlation coefficients to speech sources presented at the same presentation level irrespective of SIR.

MAIN RESULTS

Selective attention decoding in CI users is possible even if both speech streams are presented monaurally. A significant effect of SIR on ρ_(A_SIR ), ρ_Diff and ρ_DiffOpp, but not on ρ_(U_SIR ), was observed. Finally, the results show a significant correlation between speech understanding performance and ρ_(A_SIR ) as well as with ρ_(U_SIR ) across subjects. Moreover, ρ_DiffOpp which is less affected by the CI artifact, also demonstrated a significant correlation with speech understanding.

SIGNIFICANCE

Selective attention decoding in CI users is possible, however care needs to be taken with the CI artifact and the speech material used to train the decoders. These results are important for future development of objective speech understanding measures for CI users.

Neural oscillations track natural but not artificial fast speech: Novel insights from speech-brain coupling using MEG

Neural oscillations contribute to speech parsing via cortical tracking of hierarchical linguistic structures, including syllable rate. While the properties of neural entrainment have been largely probed with speech stimuli at either normal or artificially accelerated rates, the important case of natural fast speech has been largely overlooked. Using magnetoencephalography, we found that listening to naturally-produced speech was associated with cortico-acoustic coupling, both at normal (∼6 syllables/s) and fast (∼9 syllables/s) rates, with a corresponding shift in peak entrainment frequency. Interestingly, time-compressed sentences did not yield such coupling, despite being generated at the same rate as the natural fast sentences. Additionally, neural activity in right motor cortex exhibited stronger tuning to natural fast rather than to artificially accelerated speech, and showed evidence for stronger phase-coupling with left temporo-parietal and motor areas. These findings are highly relevant for our understanding of the role played by auditory and motor cortex oscillations in the perception of naturally produced speech.

Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research

Cognitive neuroscience, in particular research on speech and language, has seen an increase in the use of linear modeling techniques for studying the processing of natural, environmental stimuli. The availability of such computational tools has prompted similar investigations in many clinical domains, facilitating the study of cognitive and sensory deficits under more naturalistic conditions. However, studying clinical (and often highly heterogeneous) cohorts introduces an added layer of complexity to such modeling procedures, potentially leading to instability of such techniques and, as a result, inconsistent findings. Here, we outline some key methodological considerations for applied research, referring to a hypothetical clinical experiment involving speech processing and worked examples of simulated electrophysiological (EEG) data. In particular, we focus on experimental design, data preprocessing, stimulus feature extraction, model design, model training and evaluation, and interpretation of model weights. Throughout the paper, we demonstrate the implementation of each step in MATLAB using the mTRF-Toolbox and discuss how to address issues that could arise in applied research. In doing so, we hope to provide better intuition on these more technical points and provide a resource for applied and clinical researchers investigating sensory and cognitive processing using ecologically rich stimuli.

Temporal fine structure influences voicing confusions for consonant identification in multi-talker babble

To understand the mechanisms of speech perception in everyday listening environments, it is important to elucidate the relative contributions of different acoustic cues in transmitting phonetic content. Previous studies suggest that the envelope of speech in different frequency bands conveys most speech content, while the temporal fine structure (TFS) can aid in segregating target speech from background noise. However, the role of TFS in conveying phonetic content beyond what envelopes convey for intact speech in complex acoustic scenes is poorly understood. The present study addressed this question using online psychophysical experiments to measure the identification of consonants in multi-talker babble for intelligibility-matched intact and 64-channel envelope-vocoded stimuli. Consonant confusion patterns revealed that listeners had a greater tendency in the vocoded (versus intact) condition to be biased toward reporting that they heard an unvoiced consonant, despite envelope and place cues being largely preserved. This result was replicated when babble instances were varied across independent experiments, suggesting that TFS conveys voicing information beyond what is conveyed by envelopes for intact speech in babble. Given that multi-talker babble is a masker that is ubiquitous in everyday environments, this finding has implications for the design of assistive listening devices such as cochlear implants.

Effects of Task Demands on Neural Correlates of Acoustic and Semantic Processing in Challenging Listening Conditions

Purpose Listeners shift their listening strategies between lower level acoustic information and higher level semantic information to prioritize maximum speech intelligibility in challenging listening conditions. Although increasing task demands via acoustic degradation modulates lexical-semantic processing, the neural mechanisms underlying different listening strategies are unclear. The current study examined the extent to which encoding of lower level acoustic cues is modulated by task demand and associations with lexical-semantic processes. Method Electroencephalography was acquired while participants listened to sentences in the presence of four-talker babble that contained either higher or lower probability final words. Task difficulty was modulated by time available to process responses. Cortical tracking of speech-neural correlates of acoustic temporal envelope processing-were estimated using temporal response functions. Results Task difficulty did not affect cortical tracking of temporal envelope of speech under challenging listening conditions. Neural indices of lexical-semantic processing (N400 amplitudes) were larger with increased task difficulty. No correlations were observed between the cortical tracking of temporal envelope of speech and lexical-semantic processes, even after controlling for the effect of individualized signal-to-noise ratios. Conclusions Cortical tracking of the temporal envelope of speech and semantic processing are differentially influenced by task difficulty. While increased task demands modulated higher level semantic processing, cortical tracking of the temporal envelope of speech may be influenced by task difficulty primarily when the demand is manipulated in terms of acoustic properties of the stimulus, consistent with an emerging perspective in speech perception.

Impaired interaural correlation processing in people with schizophrenia

Detection of transient changes in interaural correlation is based on the temporal precision of the central representations of acoustic signals. Whether schizophrenia impairs the temporal precision in the interaural correlation process is not clear. In both participants with schizophrenia and matched healthy-control participants, this study examined the detection of a break in interaural correlation (BIC, a change in interaural correlation from 1 to 0 and back to 1), including the longest interaural delay at which a BIC was just audible, representing the temporal extent of the primitive auditory memory (PAM). Moreover, BIC-induced electroencephalograms (EEGs) and the relationships between the early binaural psychoacoustic processing and higher cognitive functions, which were assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), were examined. The results showed that compared to healthy controls, participants with schizophrenia exhibited poorer BIC detection, PAM and RBANS score. Both the BIC-detection accuracy and the PAM extent were correlated with the RBANS score. Moreover, participants with schizophrenia showed weaker BIC-induced N1-P2 amplitude which was correlated with both theta-band power and inter-trial phase coherence. These results suggested that schizophrenia impairs the temporal precision of the central representations of acoustic signals, affecting both interaural correlation processing and higher-order cognitions.

Temporal Alterations to Central Auditory Processing without Synaptopathy after Lifetime Exposure to Environmental Noise

People are increasingly exposed to environmental noise through the cumulation of occupational and recreational activities, which is considered harmless to the auditory system, if the sound intensity remains <80 dB. However, recent evidence of noise-induced peripheral synaptic damage and central reorganizations in the auditory cortex, despite normal audiometry results, has cast doubt on the innocuousness of lifetime exposure to environmental noise. We addressed this issue by exposing adult rats to realistic and nontraumatic environmental noise, within the daily permissible noise exposure limit for humans (80 dB sound pressure level, 8 h/day) for between 3 and 18 months. We found that temporary hearing loss could be detected after 6 months of daily exposure, without leading to permanent hearing loss or to missing synaptic ribbons in cochlear hair cells. The degraded temporal representation of sounds in the auditory cortex after 18 months of exposure was very different from the effects observed after only 3 months of exposure, suggesting that modifications to the neural code continue throughout a lifetime of exposure to noise.

Modulation masking and fine structure shape neural envelope coding to predict speech intelligibility across diverse listening conditions

A fundamental question in the neuroscience of everyday communication is how scene acoustics shape the neural processing of attended speech sounds and in turn impact speech intelligibility. While it is well known that the temporal envelopes in target speech are important for intelligibility, how the neural encoding of target-speech envelopes is influenced by background sounds or other acoustic features of the scene is unknown. Here, we combine human electroencephalography with simultaneous intelligibility measurements to address this key gap. We find that the neural envelope-domain signal-to-noise ratio in target-speech encoding, which is shaped by masker modulations, predicts intelligibility over a range of strategically chosen realistic listening conditions unseen by the predictive model. This provides neurophysiological evidence for modulation masking. Moreover, using high-resolution vocoding to carefully control peripheral envelopes, we show that target-envelope coding fidelity in the brain depends not only on envelopes conveyed by the cochlea, but also on the temporal fine structure (TFS), which supports scene segregation. Our results are consistent with the notion that temporal coherence of sound elements across envelopes and/or TFS influences scene analysis and attentive selection of a target sound. Our findings also inform speech-intelligibility models and technologies attempting to improve real-world speech communication.

Accurate Decoding of Imagined and Heard Melodies

Music perception requires the human brain to process a variety of acoustic and music-related properties. Recent research used encoding models to tease apart and study the various cortical contributors to music perception. To do so, such approaches study temporal response functions that summarise the neural activity over several minutes of data. Here we tested the possibility of assessing the neural processing of individual musical units (bars) with electroencephalography (EEG). We devised a decoding methodology based on a maximum correlation metric across EEG segments (maxCorr) and used it to decode melodies from EEG based on an experiment where professional musicians listened and imagined four Bach melodies multiple times. We demonstrate here that accurate decoding of melodies in single-subjects and at the level of individual musical units is possible, both from EEG signals recorded during listening and imagination. Furthermore, we find that greater decoding accuracies are measured for the maxCorr method than for an envelope reconstruction approach based on backward temporal response functions (bTRF_env). These results indicate that low-frequency neural signals encode information beyond note timing, especially with respect to low-frequency cortical signals below 1 Hz, which are shown to encode pitch-related information. Along with the theoretical implications of these results, we discuss the potential applications of this decoding methodology in the context of novel brain-computer interface solutions.

The Music of Silence: Part II: Music Listening Induces Imagery Responses

During music listening, humans routinely acquire the regularities of the acoustic sequences and use them to anticipate and interpret the ongoing melody. Specifically, in line with this predictive framework, it is thought that brain responses during such listening reflect a comparison between the bottom-up sensory responses and top-down prediction signals generated by an internal model that embodies the music exposure and expectations of the listener. To attain a clear view of these predictive responses, previous work has eliminated the sensory inputs by inserting artificial silences (or sound omissions) that leave behind only the corresponding predictions of the thwarted expectations. Here, we demonstrate a new alternate approach in which we decode the predictive electroencephalography (EEG) responses to the silent intervals that are naturally interspersed within the music. We did this as participants (experiment 1, 20 participants, 10 female; experiment 2, 21 participants, 6 female) listened or imagined Bach piano melodies. Prediction signals were quantified and assessed via a computational model of the melodic structure of the music and were shown to exhibit the same response characteristics when measured during listening or imagining. These include an inverted polarity for both silence and imagined responses relative to listening, as well as response magnitude modulations that precisely reflect the expectations of notes and silences in both listening and imagery conditions. These findings therefore provide a unifying view that links results from many previous paradigms, including omission reactions and the expectation modulation of sensory responses, all in the context of naturalistic music listening.SIGNIFICANCE STATEMENT Music perception depends on our ability to learn and detect melodic structures. It has been suggested that our brain does so by actively predicting upcoming music notes, a process inducing instantaneous neural responses as the music confronts these expectations. Here, we studied this prediction process using EEGs recorded while participants listen to and imagine Bach melodies. Specifically, we examined neural signals during the ubiquitous musical pauses (or silent intervals) in a music stream and analyzed them in contrast to the imagery responses. We find that imagined predictive responses are routinely co-opted during ongoing music listening. These conclusions are revealed by a new paradigm using listening and imagery of naturalistic melodies.

Brain electrical dynamics in speech segmentation depends upon prior experience with the language

It remains unclear whether the process of speech tracking, which facilitates speech segmentation, reflects top-down mechanisms related to prior linguistic models or stimulus-driven mechanisms, or possibly both. To address this, we recorded electroencephalography (EEG) responses from native and non-native speakers of English that had different prior experience with the English language but heard acoustically identical stimuli. Despite a significant difference in the ability to segment and perceive speech, our EEG results showed that theta-band tracking of the speech envelope did not depend significantly on prior experience with language. However, tracking in the theta-band did show changes across repetitions of the same sentence, suggesting a priming effect. Furthermore, native and non-native speakers showed different phase dynamics at word boundaries, suggesting differences in segmentation mechanisms. Finally, we found that the correlation between higher frequency dynamics reflecting phoneme-level processing and perceptual segmentation of words might depend on prior experience with the spoken language.

The Effect of Stimulus Choice on an EEG-Based Objective Measure of Speech Intelligibility

OBJECTIVES

Recently, an objective measure of speech intelligibility (SI), based on brain responses derived from the electroencephalogram (EEG), has been developed using isolated Matrix sentences as a stimulus. We investigated whether this objective measure of SI can also be used with natural speech as a stimulus, as this would be beneficial for clinical applications.

DESIGN

We recorded the EEG in 19 normal-hearing participants while they listened to two types of stimuli: Matrix sentences and a natural story. Each stimulus was presented at different levels of SI by adding speech weighted noise. SI was assessed in two ways for both stimuli: (1) behaviorally and (2) objectively by reconstructing the speech envelope from the EEG using a linear decoder and correlating it with the acoustic envelope. We also calculated temporal response functions (TRFs) to investigate the temporal characteristics of the brain responses in the EEG channels covering different brain areas.

RESULTS

For both stimulus types, the correlation between the speech envelope and the reconstructed envelope increased with increasing SI. In addition, correlations were higher for the natural story than for the Matrix sentences. Similar to the linear decoder analysis, TRF amplitudes increased with increasing SI for both stimuli. Remarkable is that although SI remained unchanged under the no-noise and +2.5 dB SNR conditions, neural speech processing was affected by the addition of this small amount of noise: TRF amplitudes across the entire scalp decreased between 0 and 150 ms, while amplitudes between 150 and 200 ms increased in the presence of noise. TRF latency changes in function of SI appeared to be stimulus specific: the latency of the prominent negative peak in the early responses (50 to 300 ms) increased with increasing SI for the Matrix sentences, but remained unchanged for the natural story.

CONCLUSIONS

These results show (1) the feasibility of natural speech as a stimulus for the objective measure of SI; (2) that neural tracking of speech is enhanced using a natural story compared to Matrix sentences; and (3) that noise and the stimulus type can change the temporal characteristics of the brain responses. These results might reflect the integration of incoming acoustic features and top-down information, suggesting that the choice of the stimulus has to be considered based on the intended purpose of the measurement.

Human EEG and Recurrent Neural Networks Exhibit Common Temporal Dynamics During Speech Recognition

Recent deep-learning artificial neural networks have shown remarkable success in recognizing natural human speech, however the reasons for their success are not entirely understood. Success of these methods might be because state-of-the-art networks use recurrent layers or dilated convolutional layers that enable the network to use a time-dependent feature space. The importance of time-dependent features in human cortical mechanisms of speech perception, measured by electroencephalography (EEG) and magnetoencephalography (MEG), have also been of particular recent interest. It is possible that recurrent neural networks (RNNs) achieve their success by emulating aspects of cortical dynamics, albeit through very different computational mechanisms. In that case, we should observe commonalities in the temporal dynamics of deep-learning models, particularly in recurrent layers, and brain electrical activity (EEG) during speech perception. We explored this prediction by presenting the same sentences to both human listeners and the Deep Speech RNN and considered the temporal dynamics of the EEG and RNN units for identical sentences. We tested whether the recently discovered phenomenon of envelope phase tracking in the human EEG is also evident in RNN hidden layers. We furthermore predicted that the clustering of dissimilarity between model representations of pairs of stimuli would be similar in both RNN and EEG dynamics. We found that the dynamics of both the recurrent layer of the network and human EEG signals exhibit envelope phase tracking with similar time lags. We also computed the representational distance matrices (RDMs) of brain and network responses to speech stimuli. The model RDMs became more similar to the brain RDM when going from early network layers to later ones, and eventually peaked at the recurrent layer. These results suggest that the Deep Speech RNN captures a representation of temporal features of speech in a manner similar to human brain.

Unilateral Acoustic Degradation Delays Attentional Separation of Competing Speech

Hearing loss is often asymmetric such that hearing thresholds differ substantially between the two ears. The extreme case of such asymmetric hearing is single-sided deafness. A unilateral cochlear implant (CI) on the more severely impaired ear is an effective treatment to restore hearing. The interactive effects of unilateral acoustic degradation and spatial attention to one sound source in multitalker situations are at present unclear. Here, we simulated some features of listening with a unilateral CI in young, normal-hearing listeners (N = 22) who were presented with 8-band noise-vocoded speech to one ear and intact speech to the other ear. Neural responses were recorded in the electroencephalogram to obtain the spectrotemporal response function to speech. Listeners made more mistakes when answering questions about vocoded (vs. intact) attended speech. At the neural level, we asked how unilateral acoustic degradation would impact the attention-induced amplification of tracking target versus distracting speech. Interestingly, unilateral degradation did not per se reduce the attention-induced amplification but instead delayed it in time: Speech encoding accuracy, modelled on the basis of the spectrotemporal response function, was significantly enhanced for attended versus ignored intact speech at earlier neural response latencies (<∼250 ms). This attentional enhancement was not absent but delayed for vocoded speech. These findings suggest that attentional selection of unilateral, degraded speech is feasible but induces delayed neural separation of competing speech, which might explain listening challenges experienced by unilateral CI users.