Bharath Chandrasekaran

When we produce sounds ourselves, the brain modulates the auditory neural response through an efference copy mechanism, allowing us to distinguish between self-initiated and externally generated auditory inputs. However, the precise level of the auditory pathway at which this attenuation occurs remains unclear. While evidence from animal models suggests that early auditory processing of self-generated sounds may be modulated by corticofugal signaling, localized cortical modulation would preserve the high-fidelity subcortical sound encoding while allowing flexible, context-dependent processing at higher levels. To probe potential motor influences in the early auditory system, we collected scalp-recorded frequency following responses (FFRs) from 33 normal-hearing adults during active (self-initiated) and passive (externally presented) listening conditions using a 170 ms speech stimulus. Data were collected with a vertical montage that emphasizes subcortical generators of the FFR. We observed no significant differences in the FFR between active and passive conditions in spectral power, response amplitude, pitch tracking, onset latency, or phase consistency. In contrast, cortical event-related potentials showed motor-induced suppression (MIS): reduced early peak amplitudes in the active condition after correcting for motor signals, increased phase consistency prior to auditory feedback, and more precise phase consistency at sound offset. In addition to indicating FFRs can be collected during a wider range of behavioral tasks without substantial motor contamination, our observation of the canonical MIS in cortical signals but not in FFRs suggests that MIS of self-initiated sounds primarily affects later stages of auditory processing rather than the early encoding reflected in the FFR.

Objectives: Objective and ecologically valid measures of speech processing can complement conventional audiologic assessments. Phoneme-related potentials (PRPs), derived by averaging listeners' electroencephalography (EEG) responses time-locked to phonemes in continuous speech, have emerged as a promising approach for capturing cortical processing of speech in naturalistic listening conditions. Importantly, PRPs reveal speech perception challenges even when conventional audiograms are clinically normal, positioning them as a promising neural marker for suprathreshold listening difficulties that standard audiometry often misses. As a critical step toward clinical translation, this study examined the extent to which PRP-derived measures remain stable across real-world contexts relevant to clinical implementation, including monaural versus binaural presentation, stimulus intensity level, and repeated testing sessions. The study also assessed cortical tracking of lower-level speech acoustics to determine whether the PRP findings could be attributed to acoustic processing. Design: EEG was recorded from 18 young adults with normal hearing as they listened to audiobook speech presented monaurally or binaurally at 60 or 75 dB across two sessions separated by approximately one week. Neural differentiation of phoneme manner-of-articulation classes (vowels, nasals/approximants, fricatives, and stops) in PRPs was quantified using two measures: an F-statistic reflecting between-manner relative to within-manner variability, and classification accuracy from a machine-learning model trained to predict manner class from PRPs. Temporal response function modeling assessed neural tracking of continuous acoustic envelope and onset features of the audiobook speech. Results: Neither PRP-derived measure of manner differentiation showed significant effects of session, presentation modality, intensity level, or their interactions. Intraclass correlation analyses further indicated moderate-to-good reliability across all three factors. In contrast, neural tracking of the acoustic envelope and acoustic onsets was stronger under binaural than monaural presentation, with binaural presentation eliciting more pronounced cortical responses to the envelope. Conclusions: PRP-derived measures remained relatively stable across modest procedural variations that are common in clinical testing contexts, positioning PRPs as a potent objective index of naturalistic speech processing. This stability may reflect cortical processing of abstract, linguistically relevant speech categories and suggest that PRPs provide complementary information beyond audiologic assessments of peripheral auditory functions and EEG measures that primarily capture lower-level acoustic processing.

Spoken language contains critical information related to “what” is being said as well as “who” is talking. Listeners use various cues from speech to identify talkers. Talkers can be identified primarily based on acoustic cues, but access to higher‐level cues depends on the extent of language familiarity. Do listeners have greater processing costs when there is a greater number of cues available? Or do listeners leverage cues in a reverse hierarchical manner, using higher‐level cues more strategically to reduce processing costs? Here, we leveraged multiple methodological approaches, including pupillometry, analysis of the behavioral error pattern, and drift diffusion models (DDMs), to examine the dynamics of how learners identify novel talkers and accrue sensory evidence, balance cue usage, and manage processing costs during talker identity learning. Native English‐speaking adults learned to identify talkers in English and Mandarin, then were tested on recognizing them speaking new sentences, all while their pupillary responses, a proxy for processing cost, were recorded. Talker identification was more accurate and induced less pupil dilation in English relative to Mandarin. Analysis of error patterns showed that listeners relied more heavily on low‐level acoustic features in Mandarin than English, and DDMs revealed that higher evidence accumulation rates were associated with smaller pupil dilation. These findings suggest that, whenever available, listeners primarily use higher‐level abstract representations to identify talkers from the beginning of the learning process while relying on less efficient, lower‐level features of speech sounds in unfamiliar languages, consistent with the predictions of the reverse hierarchical framework.

Talker identification categorizes variable speech signals into stable talker representations, a process facilitated by language and accent familiarity. The dual learning systems (DLS) model posits that speech category learning involves a “reflective” system based on explicit rules and a “reflexive” system based on stimulus-reward associations, with reflexive learning dominating in later stages. In this study, we leverage the DLS framework to investigate talker learning by training Mandarin-speaking listeners to identify talkers in native (Mandarin) and nonnative languages with native (English) or nonnative, but familiar accents (Mandarin-accented English) contexts. Listeners received either using full (e.g., Incorrect. It’s Talker 1 ) or minimally informative (e.g., Incorrect ) feedback, encouraging reflective or reflexive learning, respectively. We assessed identification performance through accuracy and response times and analyzed the underlying decision processes using drift diffusion models. Results showed that language and accent familiarity improved accuracy and response times. At later training stages, minimal feedback, which promotes reflexive learning according to the DLS model, facilitated faster identification and more efficient decision-making, particularly in the nonnative language context (English). The findings highlight the benefit of reflexive learning in talker identification through improved response efficiency and the need to consider decision dynamics in this process. The data, materials, and analysis code are available online ( https://osf.io/g7r9q/ ).

Middle age represents a critical window for early detection of neurophysiological decline. Hearing loss is increasingly recognized as both an early marker of neural degeneration and a modifiable risk factor for dementia. Yet many adults report difficulty understanding speech in noise despite normal audiograms, highlighting the limitations of current clinical tests that fail to capture the underlying physiology or effort required for real-world listening. Beyond hearing thresholds, speech comprehension in complex environments depends on precise neural encoding of temporal fine structure (TFS) cues that convey pitch and spatial information. Here, we use a noninvasive EEG-based measure of neural phase-locking (frequency modulation following responses or FMFRs) to quantify TFS encoding in young and middle-aged adults with normal hearing thresholds. Middle-aged listeners exhibited reduced FMFR amplitudes and shallower discriminability slopes, reflecting diminished neural synchrony despite preserved hearing thresholds. Using a multi-talker speech task we further found that pupil-indexed listening effort was significantly greater in middle-aged adults despite matched accuracy across groups. Further, increases in listening effort were predicted by decreases in TFS encoding. Together, these results reveal that degraded neural encoding of TFS underlies subclinical listening difficulties and increased cognitive load, establishing the FMFR as a sensitive biomarker of hidden auditory neural decline. Significance: Understanding speech in noisy environments depends on precise neural encoding of temporal fine structure (TFS) cues. Using a noninvasive EEG metric, the FMFR, we show that neural TFS coding in the peripheral auditory system declines markedly by midlife, even when hearing thresholds and speech performance are normal. These neural deficits predict elevated pupil-indexed listening effort during multi-talker speech perception, revealing that subclinical degradation of temporal coding increases cognitive load in everyday listening. The FMFR thus provides a promising biomarker for early auditory neural decline and its downstream cognitive consequences.

Pitch is a prosodic element of speech that speakers dynamically manipulate to convey intention and meaning, making it a powerful cue for spoken language. Neural encoding of fundamental frequency, the primary acoustic cue for pitch, has been shown to deteriorate with age and can occur as early as midlife without overt hearing loss. Here, we systematically examined neural coding of fundamental frequency in middle‐aged and young adult listeners using syllabic and naturalistic speech stimuli. We then examined the extent to which neural processing of pitch accents, phonological units of prosody that convey differences in word prominence in naturalistic speech, differed based on age group. Our findings revealed that middle‐aged adults exhibited reduced neural coding of fundamental frequency to syllabic and naturalistic stimuli compared with younger adults. Middle‐aged adults also demonstrated less distinct neural processing of pitch accents in naturalistic speech, as reflected by greater classification uncertainty in a neural network model classifying pitch accent categories. This finding suggests less specialized cortical processing of suprasegmental prosodic features in the auditory cortex in middle age. Reduced neural coding of fundamental frequency was associated with greater classification uncertainty for pitch accents, linking early auditory deficits to higher order prosodic processing challenges.

Extended high frequencies (EHFs; above 8 kHz) improve speech perception in noise, but the underlying mechanisms remain unclear. Debate continues over whether the benefit arises from EHFs providing direct cues to phonemes or more indirectly reflects the listener's cochlear health. To examine whether and how EHFs contribute to phoneme recognition—which is difficult to test in humans given the wide variability in EHF thresholds—this study leveraged an acoustic automatic speech recognition (ASR) model. English speech from the VCTK corpus was resynthesized to create spatial audio where target speech was masked by an interfering talker separated by 20°, 45°, 80°, or 120° azimuth at target-to-masker ratios (TMRs) from +3 to −12 dB. A convolutional neural network bi-directional long short-term memory model was trained to decode target phonemes from cochleagrams of broadband or low-pass filtered (e.g., 8 kHz cutoff) speech. In masked conditions, EHFs improved phoneme recognition across all spatial separations, particularly at TMRs ≤ −9 dB. The improvement was not found in quiet. Removing EHFs disproportionately increased phoneme error rates for consonants, consistent with consonants' spectral concentration at higher frequencies. These findings indicate that EHFs contribute directly to phoneme recognition in adverse conditions, supporting their inclusion in clinical audiometry and ASR system development.

This study examines the extent to which Mandarin-speaking listeners rely on low-level acoustic information when identifying new talkers speaking Mandarin-accented English (MAE), native Mandarin (NM), and native English (NE). Identification accuracy was highest for NM, intermediate for MAE, and lowest for NE, replicating language/accent familiarity effects. Representational similarity analysis comparing listeners' behavioral responses with talkers' low-level acoustic features (e.g., F0, jitter) revealed less reliance on these acoustic cues in more familiar contexts (e.g., NM vs NE). In MAE context, acoustic reliance decreased with training despite improved accuracy, suggesting a shift away from talker identification strategies based on low-level acoustic processing.

Speech perception can decline in middle age even when hearing thresholds remain normal, and the underlying neurobiological mechanisms are not well understood. In line with the age-related neural dedifferentiation hypothesis, we predicted that middle-aged adults show less distinct cortical representations of phonemes and acoustic-phonetic features relative to younger adults. In addition to an extensive audiological, auditory electrophysiological, and speech perceptual test battery, we measured electroencephalographic responses time-locked to phoneme instances (phoneme-related potential) in naturalistic, continuous speech and trained neural network classifiers to predict phonemes from these responses. Consistent with age-related neural dedifferentiation, phoneme predictions were less accurate, more uncertain, and involved a broader network for middle-aged adults compared with younger adults. Representational similarity analysis revealed that the featural relationship between phonemes was less robust in middle age. Electrophysiological and behavioral measures revealed signatures of putative cochlear neural degeneration (CND) and speech perceptual deficits in middle-aged adults relative to younger adults. In line with prior work in animal models, proxies of CND were associated with greater cortical dedifferentiation, explaining nearly a third of the variance in PRP prediction accuracy together with measures of acoustic neural processing. Notably, even after controlling for CND proxies and acoustic processing abilities, age-group differences in cortical PRP prediction accuracy remained. Overall, the results reveal “fuzzier” cortical phonemic representations in middle age, suggesting that age-related neural dedifferentiation may underlie speech perceptual challenges despite a normal audiogram.

Prosody has a vital function in speech, structuring a speaker’s intended message for the listener. The superior temporal gyrus (STG) is considered a critical hub for prosody, but the role of earlier auditory regions like Heschl’s gyrus (HG), associated with pitch processing, remains unclear. Using intracerebral recordings in humans and non-human primate models, we investigated prosody processing in narrative speech, focusing on pitch accents—abstract phonological units that signal word prominence and communicative intent. In humans, HG encoded pitch accents as abstract representations beyond spectrotemporal features, distinct from segmental speech processing, and outperforms STG in disambiguating pitch accents. Multivariate models confirm HG’s unique representation of pitch accent categories. In the non-human primate, pitch accents were not abstractly encoded, despite robust spectrotemporal processing, highlighting the role of experience in shaping abstract representations. These findings emphasize a key role for the HG in early prosodic abstraction and advance our understanding of human speech processing.