Exploring neural tracking of acoustic and linguistic speech representations in individuals with post‐stroke aphasia

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(8)

Published: May 26, 2024

Abstract Aphasia is a communication disorder that affects processing of language at different levels (e.g., acoustic, phonological, semantic). Recording brain activity via Electroencephalography while people listen to continuous story allows analyze responses acoustic and linguistic properties speech. When the neural aligns with these speech properties, it referred as tracking. Even though measuring tracking may present an interesting approach studying aphasia in ecologically valid way, has not yet been investigated individuals stroke‐induced aphasia. Here, we explored representations chronic phase after stroke age‐matched healthy controls. We found decreased (envelope envelope onsets) In addition, word surprisal displayed amplitudes around 195 ms over frontal electrodes, although this effect was corrected for multiple comparisons. These results show there potential capture impairments by However, more research needed validate results. Nonetheless, exploratory study shows naturalistic, presents powerful

Language: Английский

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

Hearing Research, Journal Year: 2023, Volume and Issue: 439, P. 108893 - 108893

Published: Oct. 4, 2023

Language: Английский

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Beyond linear neural envelope tracking: a mutual information approach

Journal of Neural Engineering, Journal Year: 2023, Volume and Issue: 20(2), P. 026007 - 026007

Published: Feb. 22, 2023

Objective.The human brain tracks the temporal envelope of speech, which contains essential cues for speech understanding. Linear models are most common tool to study neural tracking. However, information on how is processed can be lost since nonlinear relations precluded. Analysis based mutual (MI), other hand, detect both linear and gradually becoming more popular in field Yet, several different approaches calculating MI applied with no consensus approach use. Furthermore, added value techniques remains a subject debate field. The present paper aims resolve these open questions.Approach.We analyzed electroencephalography (EEG) data participants listening continuous analyses models.Main results.Comparing approaches, we conclude that results reliable robust using Gaussian copula approach, first transforms standard Gaussians. With this analysis valid technique studying Like models, it allows spatial interpretations processing, peak latency analyses, applications multiple EEG channels combined. In final analysis, tested whether components were response by removing all data. We robustly detected single-subject level analysis.Significance.We demonstrate processes way. Unlike detects such relations, proving its addition, retains characteristics an advantage when complex (nonlinear) deep networks.

Language: Английский

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Detecting post-stroke aphasia using EEG-based neural envelope tracking of natural speech

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: March 17, 2023

Abstract After a stroke, approximately one-third of patients suffer from aphasia, language disorder that impairs communication ability. The standard behavioral tests used to diagnose aphasia are time-consuming, require subjective interpretation, and have low ecological validity. As consequence, comorbid cognitive problems present in individuals with (IWA) can bias test results, generating discrepancy between outcomes everyday-life abilities. Neural tracking the speech envelope is promising tool for investigating brain responses natural speech. crucial understanding, encompassing cues detecting segmenting linguistic units, e.g., phrases, words phonemes. In this study, we aimed potential neural technique impairments IWA. We recorded EEG 27 IWA chronic phase after stroke 22 healthy controls while they listened 25-minute story. quantified broadband frequency range as well delta, theta, alpha, beta, gamma bands using mutual information analysis. Besides group differences measures, also tested its suitability at individual level Support Vector Machine (SVM) classifier. further investigated required recording length SVM detect obtain reliable outcomes. displayed decreased compared broad, band, which line assumed role these auditory pro-cessing effectively captured level, an accuracy 84% area under curve 88%. Moreover, demonstrated high-accuracy detection be achieved time-efficient (5 minutes) highly manner (split-half reliability correlations R=0.62 R=0.96 across bands). Our study shows effective biomarker post-stroke aphasia. diagnostic high reliability, individual-level assessment. This work represents significant step towards more automatic, objective, ecologically valid assessments

Language: Английский

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Neural speech tracking contribution of lip movements predicts behavioral deterioration when the speaker's mouth is occluded

eNeuro, Journal Year: 2025, Volume and Issue: unknown, P. ENEURO.0368 - 24.2024

Published: Jan. 16, 2025

Observing lip movements of a speaker facilitates speech understanding, especially in challenging listening situations. Converging evidence from neuroscientific studies shows stronger neural responses to audiovisual stimuli compared audio-only stimuli. However, the interindividual variability this contribution movement information and its consequences on behavior are unknown. We analyzed source-localized magnetoencephalographic (MEG) 29 normal-hearing participants (12 female) speech, both with without wearing surgical face mask, presence or absence distractor speaker. Using temporal response functions (TRFs) quantify tracking, we show that are, general, enhanced when is challenging. After controlling for acoustics, contribute particularly present. extent visual tracking varied greatly among participants. Probing behavioral relevance, demonstrate individuals who higher terms drop comprehension an increase perceived difficulty mouth occluded by mask. By contrast, no effect was found not occluded. provide novel insights how varies revealing negative absent. Our results also offer potential implications objective assessments perception. Significance Statement In complex auditory environments, simultaneous conversations pose challenge comprehension. investigated level, aid such situations what observing enhances rely more deterioration wears Remarkably, case mask worn findings reveal differences applications

Language: Английский

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Neural tracking of natural speech: an effective marker for post-stroke aphasia

Brain Communications, Journal Year: 2025, Volume and Issue: 7(2)

Published: Jan. 1, 2025

Abstract After a stroke, approximately one-third of patients suffer from aphasia, language disorder that impairs communication ability. Behavioural tests are the current standard to detect but they time-consuming, have limited ecological validity and require active patient cooperation. To address these limitations, we tested potential EEG-based neural envelope tracking natural speech. The technique investigates response temporal speech, which is critical for speech understanding by encompassing cues detecting segmenting linguistic units (e.g. phrases, words phonemes). We recorded EEG 26 individuals with aphasia in chronic phase after stroke (>6 months post-stroke) 22 healthy controls while listened 25-min story. quantified broadband frequency range as well delta, theta, alpha, beta gamma bands using mutual information analyses. Besides group differences measures, also its suitability at individual level support vector machine classifier. further investigated reliability required recording length accurate detection. Our results showed had decreased encoding compared broad, theta bands, aligns assumed role auditory processing Neural effectively captured level, classification accuracy 83.33% an area under curve 89.16%. Moreover, demonstrated high-accuracy detection can be achieved time-efficient (5–7 min) highly reliable manner (split-half correlations between R = 0.61 0.96 across bands). In this study, identified specific characteristics impaired holding promise biomarker condition. Furthermore, demonstrate discriminate high accuracy, manner. findings represent significant advance towards more automated, objective ecologically valid assessments impairments aphasia.

Language: Английский

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Minimal background noise enhances neural speech tracking: Evidence of stochastic resonance

Published: March 10, 2025

Neural activity in auditory cortex tracks the amplitude-onset envelope of continuous speech, but recent work counter-intuitively suggests that neural tracking increases when speech is masked by background noise, despite reduced intelligibility. Noise-related amplification could indicate stochastic resonance – response facilitation through noise supports tracking, a comprehensive account lacking. In five human electroencephalography (EEG) experiments, current study demonstrates generalized enhancement due to minimal noise. Results show a) enhanced for at very high SNRs (∼30 dB SNR) where highly intelligible; b) this independent attention; c) it generalizes across different stationary maskers, strongest 12-talker babble; and d) present headphone free-field listening, suggesting neural-tracking real-life listening. The paints clear picture enhances representation onset-envelope, contributes tracking. further highlights non-linearities induced make its use as biological marker processing challenging.

Language: Английский

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CORGEE: Real-Time Hearing Diagnostics Based on EEG Responses to Natural Speech

Springer briefs in electrical and computer engineering, Journal Year: 2025, Volume and Issue: unknown, P. 39 - 52

Published: Jan. 1, 2025

Language: Английский

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A Brain-Computer Interface for Improving Auditory Attention in Multi-Talker Environments

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 13, 2025

There is significant research in accurately determining the focus of a listener's attention multi-talker environment using auditory decoding (AAD) algorithms. These algorithms rely on neural signals to identify intended speaker, assuming that these consistently reflect focus. However, some listeners struggle with this competing talkers task, leading suboptimal tracking desired speaker due potential interference from distractors. The goal study was enhance target real time and investigate underlying bases improvement. This paper describes closed-loop neurofeedback system decodes listener time, utilizing data non-invasive, wet electroencephalography (EEG) brain-computer interface (BCI). Fluctuations real-time accuracy used provide acoustic feedback. As improved, ignored talker two-talker listening scenario attenuated; making easier attend improved attended signal-to-noise ratio (SNR). A one-hour session divided into 10-minute decoder training phase, rest allocated observing changes decoding. In study, we found evidence suppression (i.e., reduction in) unattended when comparing first second half ( p = 0.012). We did not find statistically increase talker. results establish single performance benchmark for time-invariant, non-adaptive linear utilized extract integrated within system. lays engineering scientific foundation prospective multi-session clinical trials an paradigm.

Language: Английский

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Speech Reception Threshold Estimation via EEG‐Based Continuous Speech Envelope Reconstruction

European Journal of Neuroscience, Journal Year: 2025, Volume and Issue: 61(6)

Published: March 1, 2025

ABSTRACT This study investigates the potential of speech reception threshold (SRT) estimation through electroencephalography (EEG) based envelope reconstruction techniques with continuous speech. Additionally, we investigate influence stimuli's signal‐to‐noise ratio (SNR) on temporal response function (TRF). Twenty young normal‐hearing participants listened to audiobook excerpts varying background noise levels while EEG was recorded. A linear decoder trained reconstruct from data. The accuracy calculated as Pearson's correlation between reconstructed and actual envelopes. An SRT estimate (SRT neuro ) obtained midpoint a sigmoid fitted versus SNR data points. TRF estimated at each level, followed by statistical analysis reveal significant effects latencies amplitudes most prominent components. within 3 dB behavioral for all participants. showed latency decrease N1 P2 amplitude magnitude increase increasing SNR. results suggest that both components are influenced changes in SNR, indicating they may be linked same underlying neural process.

Language: Английский

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