The relationship between sentence intelligibility, band importance, and signal covariance.

The present study investigates the relationship between sentence intelligibility, band importance, and patterns of spectro-temporal covariation between frequency bands. Sixteen listeners transcribed sentences acoustically degraded to 5, 8, or 15 frequency bands. Half of the sentences retained the frequency bands that captured more signal covariance. The other half retained the bands accounting for less signal covariance. Sentence intelligibility was significantly higher in the high-covariance condition. Critically, this finding was predicted by differences in band importance across reconstructed sentences. These findings provide a mechanistic relationship between the contributions of signal covariance and band importance to sentence intelligibility.

Low detection rate of RT-PCR-confirmed COVID-19 using IgM/IgG rapid antibody tests in a large community sample in Lima, Peru.

BACKGROUND: Rapid IgM/IgG antibody tests were largely used in lieu of RT-PCR tests as part of COVID-19 public health response activities in Lima, Peru. To assess their utility, we explored the relationship between the time since onset of several COVID-19-related symptoms and the sensitivity of a rapid combined IgM/IgG antibody test. METHODS: We collected data from a community sample of individuals (n = 492) who received concurrent RT-PCR and rapid IgM/IgG antibody testing between May 2020 and March 2021. We estimated the sensitivity of the antibody test, against the RT-PCR test, by weeks since symptom onset via segmented regression analysis. RESULTS: The overall sensitivity of the rapid IgM/IgG antibody test was 46.7% (95% CI, 42.4-51.2%). Among 372 (75.6%) participants who reported COVID-19-related symptoms, sensitivity increased from 30.4% (95% CI, 24.7-36.6%) in week 1 after symptom onset to 83.3% (95% CI, 41.6-98.4%) in week 4. The test sensitivity increased by 31.9% (95% CI, 24.8-39.0%) per week until week 2 to 3, then decreased by - 6.0% (95% CI, - 25.7-13.7%) per week thereafter. CONCLUSION: Rapid antibody tests are a poor substitute for RT-PCR testing, regardless of presenting symptoms. This highlights the need for future pandemic planning to include timely and equitable access to gold-standard diagnostics, treatment, and vaccination.

Language experience during the sensitive period narrows infants' sensory encoding of lexical tones-Music intervention reverses it.

The sensitive period for phonetic learning (6∼12 months), evidenced by improved native speech processing and declined non-native speech processing, represents an early milestone in language acquisition. We examined the extent that sensory encoding of speech is altered by experience during this period by testing two hypotheses: (1) early sensory encoding of non-native speech declines as infants gain native-language experience, and (2) music intervention reverses this decline. We longitudinally measured the frequency-following response (FFR), a robust indicator of early sensory encoding along the auditory pathway, to a Mandarin lexical tone in 7- and 11-months-old monolingual English-learning infants. Infants received either no intervention (language-experience group) or music intervention (music-intervention group) randomly between FFR recordings. The language-experience group exhibited the expected decline in FFR pitch-tracking accuracy to the Mandarin tone, while the music-intervention group did not. Our results support both hypotheses and demonstrate that both language and music experiences alter infants' speech encoding.

The emergence of idiosyncratic patterns in the frequency-following response during the first year of life.

The frequency-following response (FFR) is a scalp-recorded signal that reflects phase-locked activity from neurons across the auditory system. In addition to capturing information about sounds, the FFR conveys biometric information, reflecting individual differences in auditory processing. To investigate the development of FFR biometric patterns, we trained a pattern recognition model to recognize infants (N = 16) from FFRs collected at 7 and 11 months. Model recognition scores were used to index the robustness of FFR biometric patterns at each time. Results showed better recognition scores at 11 months, demonstrating the emergence of robust FFR idiosyncratic patterns during this first year of life.

Principal component decomposition of acoustic and neural representations of time-varying pitch reveals adaptive efficient coding of speech covariation patterns.

Understanding the effects of statistical regularities on speech processing is a central issue in auditory neuroscience. To investigate the effects of distributional covariance on the neural processing of speech features, we introduce and validate a novel approach: decomposition of time-varying signals into patterns of covariation extracted with Principal Component Analysis. We used this decomposition to assay the sensory representation of pitch covariation patterns in native Chinese listeners and non-native learners of Mandarin Chinese tones. Sensory representations were examined using the frequency-following response, a far-field potential that reflects phase-locked activity from neural ensembles along the auditory pathway. We found a more efficient representation of the covariation patterns that accounted for more redundancy in the form of distributional covariance. Notably, long-term language and short-term training experiences enhanced the sensory representation of these covariation patterns.

Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Antibodies Among Market and City Bus Depot Workers in Lima, Peru.

We report severe acute respiratory syndrome coronavirus 2 antibody positivity among market and city bus depot workers in Lima, Peru. Among 1285 vendors from 8 markets, prevalence ranged from 27% to 73%. Among 488 workers from 3 city bus depots, prevalence ranged from 11% to 47%. Self-reported symptoms were infrequent.

Frequency-Following Responses to Speech Sounds Are Highly Conserved across Species and Contain Cortical Contributions.

Time-varying pitch is a vital cue for human speech perception. Neural processing of time-varying pitch has been extensively assayed using scalp-recorded frequency-following responses (FFRs), an electrophysiological signal thought to reflect integrated phase-locked neural ensemble activity from subcortical auditory areas. Emerging evidence increasingly points to a putative contribution of auditory cortical ensembles to the scalp-recorded FFRs. However, the properties of cortical FFRs and precise characterization of laminar sources are still unclear. Here we used direct human intracortical recordings as well as extracranial and intracranial recordings from macaques and guinea pigs to characterize the properties of cortical sources of FFRs to time-varying pitch patterns. We found robust FFRs in the auditory cortex across all species. We leveraged representational similarity analysis as a translational bridge to characterize similarities between the human and animal models. Laminar recordings in animal models showed FFRs emerging primarily from the thalamorecipient layers of the auditory cortex. FFRs arising from these cortical sources significantly contributed to the scalp-recorded FFRs via volume conduction. Our research paves the way for a wide array of studies to investigate the role of cortical FFRs in auditory perception and plasticity.

Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults.

Understanding how adult humans learn nonnative speech categories such as tone information has shed novel insights into the mechanisms underlying experience-dependent brain plasticity. Scientists have traditionally examined these questions using longitudinal learning experiments under a multi-category decision making paradigm. Drift-diffusion processes are popular in such contexts for their ability to mimic underlying neural mechanisms. Motivated by these problems, we develop a novel Bayesian semiparametric inverse Gaussian drift-diffusion mixed model for multi-alternative decision making in longitudinal settings. We design a Markov chain Monte Carlo algorithm for posterior computation. We evaluate the method's empirical performances through synthetic experiments. Applied to our motivating longitudinal tone learning study, the method provides novel insights into how the biologically interpretable model parameters evolve with learning, differ between input-response tone combinations, and differ between well and poorly performing adults. supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

The neural processing of pitch accents in continuous speech.

Pitch accents are local pitch patterns that convey differences in word prominence and modulate the information structure of the discourse. Despite the importance to discourse in languages like English, neural processing of pitch accents remains understudied. The current study investigates the neural processing of pitch accents by native and non-native English speakers while they are listening to or ignoring 45 min of continuous, natural speech. Leveraging an approach used to study phonemes in natural speech, we analyzed thousands of electroencephalography (EEG) segments time-locked to pitch accents in a prosodic transcription. The optimal neural discrimination between pitch accent categories emerged at latencies between 100 and 200 ms. During these latencies, we found a strong structural alignment between neural and phonetic representations of pitch accent categories. In the same latencies, native listeners exhibited more robust processing of pitch accent contrasts than non-native listeners. However, these group differences attenuated when the speech signal was ignored. We can reliably capture the neural processing of discrete and contrastive pitch accent categories in continuous speech. Our analytic approach also captures how language-specific knowledge and selective attention influences the neural processing of pitch accent categories.

A distributed dynamic brain network mediates linguistic tone representation and categorization.

Successful categorization requires listeners to represent the incoming sensory information, resolve the "blooming, buzzing confusion" inherent to noisy sensory signals, and leverage the accumulated evidence towards making a decision. Despite decades of intense debate, the neural systems underlying speech categorization remain unresolved. Here we assessed the neural representation and categorization of lexical tones by native Mandarin speakers (N = 31) across a range of acoustic and contextual variabilities (talkers, perceptual saliences, and stimulus-contexts) using functional magnetic imaging (fMRI) and an evidence accumulation model of decision-making. Univariate activation and multivariate pattern analyses reveal that the acoustic-variability-tolerant representations of tone category are observed within the middle portion of the left superior temporal gyrus (STG). Activation patterns in the frontal and parietal regions also contained category-relevant information that was differentially sensitive to various forms of variability. The robustness of neural representations of tone category in a distributed fronto-temporoparietal network is associated with trial-by-trial decision-making parameters. These findings support a hybrid model involving a representational core within the STG that operates dynamically within an extensive frontoparietal network to support the representation and categorization of linguistic pitch patterns.

Non-invasive peripheral nerve stimulation selectively enhances speech category learning in adults.

Adults struggle to learn non-native speech contrasts even after years of exposure. While laboratory-based training approaches yield learning, the optimal training conditions for maximizing speech learning in adulthood are currently unknown. Vagus nerve stimulation has been shown to prime adult sensory-perceptual systems towards plasticity in animal models. Precise temporal pairing with auditory stimuli can enhance auditory cortical representations with a high degree of specificity. Here, we examined whether sub-perceptual threshold transcutaneous vagus nerve stimulation (tVNS), paired with non-native speech sounds, enhances speech category learning in adults. Twenty-four native English-speakers were trained to identify non-native Mandarin tone categories. Across two groups, tVNS was paired with the tone categories that were easier- or harder-to-learn. A control group received no stimulation but followed an identical thresholding procedure as the intervention groups. We found that tVNS robustly enhanced speech category learning and retention of correct stimulus-response associations, but only when stimulation was paired with the easier-to-learn categories. This effect emerged rapidly, generalized to new exemplars, and was qualitatively different from the normal individual variability observed in hundreds of learners who have performed in the same task without stimulation. Electroencephalography recorded before and after training indicated no evidence of tVNS-induced changes in the sensory representation of auditory stimuli. These results suggest that paired-tVNS induces a temporally precise neuromodulatory signal that selectively enhances the perception and memory consolidation of perceptually salient categories.

Biometric identification of listener identity from frequency following responses to speech.

OBJECTIVE: We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran and Kraus 2010, Bidelman, 2015a, 2018, Coffey et al 2017b). Our objective is two-fold: demonstrate that the FFR contains information beyond stimulus properties and broad group-level markers, and to assess the practical viability of the FFR as a biometric across different sounds, auditory experiences, and recording days. APPROACH: We trained the hidden Markov model (HMM) to decode listener identity from FFR spectro-temporal patterns across multiple frequency bands. Our dataset included FFRs from twenty native speakers of English or Mandarin Chinese (10 per group) listening to Mandarin Chinese tones across three EEG sessions separated by days. We decoded subject identity within the same auditory context (same tone and session) and across different stimuli and recording sessions. MAIN RESULTS: The HMM decoded listeners for averaging sizes as small as one single FFR. However, model performance improved for larger averaging sizes (e.g. 25 FFRs), similarity in auditory context (same tone and day), and lack of familiarity with the sounds (i.e. native English relative to native Chinese listeners). Our results also revealed important biometric contributions from frequency bands in the cortical and subcortical EEG. SIGNIFICANCE: Our study provides the first deep and systematic biometric characterization of the FFR and provides the basis for biometric identification systems incorporating this neural signal.

Tracing the Trajectory of Sensory Plasticity across Different Stages of Speech Learning in Adulthood.

Although challenging, adults can learn non-native phonetic contrasts with extensive training [1, 2], indicative of perceptual learning beyond an early sensitivity period [3, 4]. Training can alter low-level sensory encoding of newly acquired speech sound patterns [5]; however, the time-course, behavioral relevance, and long-term retention of such sensory plasticity is unclear. Some theories argue that sensory plasticity underlying signal enhancement is immediate and critical to perceptual learning [6, 7]. Others, like the reverse hierarchy theory (RHT), posit a slower time-course for sensory plasticity [8]. RHT proposes that higher-level categorical representations guide immediate, novice learning, while lower-level sensory changes do not emerge until expert stages of learning [9]. We trained 20 English-speaking adults to categorize a non-native phonetic contrast (Mandarin lexical tones) using a criterion-dependent sound-to-category training paradigm. Sensory and perceptual indices were assayed across operationally defined learning phases (novice, experienced, over-trained, and 8-week retention) by measuring the frequency-following response, a neurophonic potential that reflects fidelity of sensory encoding, and the perceptual identification of a tone continuum. Our results demonstrate that while robust changes in sensory encoding and perceptual identification of Mandarin tones emerged with training and were retained, such changes followed different timescales. Sensory changes were evidenced and related to behavioral performance only when participants were over-trained. In contrast, changes in perceptual identification reflecting improvement in categorical percept emerged relatively earlier. Individual differences in perceptual identification, and not sensory encoding, related to faster learning. Our findings support the RHT-sensory plasticity accompanies, rather than drives, expert levels of non-native speech learning.

Hidden Markov modeling of frequency-following responses to Mandarin lexical tones.

BACKGROUND: The frequency-following response (FFR) is a scalp-recorded electrophysiological potential reflecting phase-locked activity from neural ensembles in the auditory system. The FFR is often used to assess the robustness of subcortical pitch processing. Due to low signal-to-noise ratio at the single-trial level, FFRs are typically averaged across thousands of stimulus repetitions. Prior work using this approach has shown that subcortical encoding of linguistically-relevant pitch patterns is modulated by long-term language experience. NEW METHOD: We examine the extent to which a machine learning approach using hidden Markov modeling (HMM) can be utilized to decode Mandarin tone-categories from scalp-record electrophysiolgical activity. We then assess the extent to which the HMM can capture biologically-relevant effects (language experience-driven plasticity). To this end, we recorded FFRs to four Mandarin tones from 14 adult native speakers of Chinese and 14 of native English. We trained a HMM to decode tone categories from the FFRs with varying size of averages. RESULTS AND COMPARISONS WITH EXISTING METHODS: Tone categories were decoded with above-chance accuracies using HMM. The HMM derived metric (decoding accuracy) revealed a robust effect of language experience, such that FFRs from native Chinese speakers yielded greater accuracies than native English speakers. Critically, the language experience-driven plasticity was captured with average sizes significantly smaller than those used in the extant literature. CONCLUSIONS: Our results demonstrate the feasibility of HMM in assessing the robustness of neural pitch. Machine-learning approaches can complement extant analytical methods that capture auditory function and could reduce the number of trials needed to capture biological phenomena.

Infants adapt to speaking rate differences in word segmentation.

Throughout their development, infants are exposed to varying speaking rates. Thus, it is important to determine whether they are able to adapt to speech at varying rates and recognize target words from continuous speech despite speaking rate differences. To address this question, a series of four experiments were conducted to test whether infants can recognize words in continuous speech when rate is variable. In addition, the underlying mechanisms that infants may use to cope with variations induced by different speaking rates were also examined. Specifically, using the Headturn Preference procedure [Jusczyk and Aslin (1995). Cognitive Psychol. 29, 1-23], infants were familiarized with normal-rate passages containing two trisyllabic target words (e.g., elephants and dinosaurs), and tested with familiar (elephants and dinosaurs) and unfamiliar (crocodiles and platypus) words embedded in normal-rate (experiment 1), fast-rate (experiments 2 and 3), or slow-rate passages (experiment 4). The results indicate that 14-month-olds, but not 11-month-olds, recognized target words in passages with a fast speaking rate. In addition, findings suggest that infants used context to normalize speech across different speaking rates.

Power spectral entropy as an information-theoretic correlate of manner of articulation in American English.

While all languages differentiate speech sounds by manner of articulation, none of the acoustic correlates proposed to date seem to account for how these contrasts are encoded in the speech signal. The present study describes power spectral entropy (PSE), which quantifies the amount of potential information conveyed in the power spectrum of a given sound. Results of acoustic analyses of speech samples extracted from the Texas Instruments-Massachusetts Institute of Technology database reveal a statistically significant correspondence between PSE and American English major classes of manner of articulation. Thus, PSE accurately captures an acoustic correlate of manner of articulation in American English.

The Effects of Language Experience and Speech Context on the Phonetic Accommodation of English-accented Spanish Voicing.

Native speakers of Spanish with different amounts of experience with English classified stop-consonant voicing (/b/ versus /p/) across different speech accents: English-accented Spanish, native Spanish, and native English. While listeners with little experience with English classified target voicing with an English- or Spanish-like voice onset time (VOT) boundary, predicted by contextual VOT, listeners familiar with English relied on an English-like VOT boundary in an English-accented Spanish context even in the absence of clear contextual cues to English VOT. This indicates that Spanish listeners accommodated English-accented Spanish voicing differently depending on their degree of familiarization with the English norm.

Neurocysticercosis as a cause of epilepsy and seizures in two community-based studies in a cysticercosis-endemic region in Peru.

BACKGROUND: The prevalence of epilepsy added to inadequate treatment results in chronic morbidity and considerable mortality in poor populations. Neurocysticercosis (NCC), a helminthic disease of the central nervous system, is a leading cause of seizures and epilepsy in most of the world. METHODS: Taking advantage of a cysticercosis elimination program, we performed two community-based cross-sectional studies between 2006 and 2007 in 58 rural communities (population 20,610) to assess the prevalence and characteristics of epilepsy and epileptic seizures in this endemic region. Serological and computed tomography (CT) data in individuals with epilepsy were compared to previous surveys in general population from the same region. PRINCIPAL FINDINGS: In two surveys, 17,450 individuals were evaluated. Lifetime prevalence of epilepsy was 17.25/1000, and prevalence of active epilepsy was 10.8/1000 inhabitants. The prevalence of epilepsy increased after age 25 years and dropped after age 45. Only 24% (45/188) of patients with active epilepsy were taking antiepileptic drugs, all at sub-therapeutic doses. Antibodies to cysticercosis were found in approximately 40% of individuals with epilepsy in both studies. In one survey only individuals presenting strong antibody reactions were significantly associated with having epilepsy (OR 5.74; p<0.001). In the second, the seroprevalence as well as the proportion presenting strong antibody reactions were both significantly higher in individuals with epilepsy (OR 2.2 and 4.33, respectively). Brain CT showed NCC-compatible images in 109/282 individuals with epilepsy (39%). All individuals with viable parasites on CT were seropositive. CONCLUSION: The prevalence of epilepsy in this cysticercosis endemic region is high and NCC is an important contributor to it.

Auditory enhancement and second language experience in Spanish and English weighting of secondary voicing cues.

The role of secondary cues in voicing categorization was investigated in three listener groups: Monolingual English (n = 20) and Spanish speakers (n = 20), and Spanish speakers with significant English experience (n = 16). Results showed that, in all three groups, participants used onset f0 in making voicing decisions only in the positive voice onset time (VOT) range (short lag and long lag tokens), while there was no effect of onset f0 on voicing categorization within the negative VOT range (voicing lead tokens) for any of the participant groups. These results support an auditory enhancement view of perceptual cue weighting: Onset f0 serves as a secondary cue to voicing only in the positive VOT range where it is not overshadowed by the presence of pre-voicing. Moreover, results showed that Spanish learners of English gave a significantly greater weight to onset f0 in their voicing decisions than did listeners in either of the other two groups. This result supports the view that learners may overweight secondary cues to distinguish between non-native categories that are assimilated to the same native category on the basis of a primary cue.

Differential cue weighting in perception and production of consonant voicing.

This study examines English speakers' relative weighting of two voicing cues in production and perception. Participants repeated words differing in initial consonant voicing ([b] or [p]) and labeled synthesized tokens ranging between [ba] and [pa] orthogonally according to voice onset time (VOT) and onset f0. Discriminant function analysis and logistic regression were used to calculate individuals' relative weighting of each cue. Production results showed a significant negative correlation of VOT and onset f0, while perception results showed a trend toward a positive correlation. No significant correlations were found across perception and production, suggesting a complex relationship between the two domains.