Biology subjects

Vanthornhout, J.

Publications and source records attributed to Vanthornhout, J..

29 records · Page 2Linked to original sources

bioRxiv2021

Hearing loss is associated with delayed neural responses to continuous speech

We investigated the impact of hearing loss on the neural processing of speech. Using a forward modeling approach, we compared the neural responses to continuous speech of 14 adults with sensorineural hearing loss with those of age-matched normal-hearing peers. Compared to their normal-hearing peers, hearing-impaired listeners had increased neural tracking and delayed neural responses to continuous speech in quiet. The latency also increased with the degree of hearing loss. As speech understanding decreased, neural tracking decreased in both populations; however, a significantly different trend was observed for the latency of the neural responses. For normal-hearing listeners, the latency increased with increasing background noise level. However, for hearing-impaired listeners, this increase was not observed. Our results support the idea that the neural response latency indicates the efficiency of neural speech processing. Hearing-impaired listeners process speech in silence less efficiently than normal-hearing listeners. Our results suggest that this reduction in neural speech processing efficiency is a gradual effect which occurs as hearing deteriorates. Moreover, the efficiency of neural speech processing in hearing-impaired listeners is already at its lowest level when listening to speech in quiet, while normal-hearing listeners show a further decrease in efficiency when the noise level increases. From our results, it is apparent that sound amplification does not solve hearing loss. Even when listing to speech in silence at a comfortable loudness, hearing-impaired listeners process speech less efficiently.

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bioRxiv2020

The effect of stimulus intensity on neural envelope tracking

ObjectivesThe last years there has been significant interest in attempting to recover the temporal envelope of a speech signal from the neural response to investigate neural speech processing. The research focus is now broadening from neural speech processing in normal-hearing listeners towards hearing-impaired listeners. When testing hearing-impaired listeners speech has to be amplified to resemble the effect of a hearing aid and compensate peripheral hearing loss. Until today, it is not known with certainty how or if neural speech tracking is influenced by sound amplification. As these higher intensities could influence the outcome, we investigated the influence of stimulus intensity on neural speech tracking. DesignWe recorded the electroencephalogram (EEG) of 20 normal-hearing participants while they listened to a narrated story. The story was presented at intensities from 10 to 80 dB A. To investigate the brain responses, we analyzed neural tracking of the speech envelope by reconstructing the envelope from EEG using a linear decoder and by correlating the reconstructed with the actual envelope. We investigated the delta (0.5-4 Hz) and the theta (4-8 Hz) band for each intensity. We also investigated the latencies and amplitudes of the responses in more detail using temporal response functions which are the estimated linear response functions between the stimulus envelope and the EEG. ResultsNeural envelope tracking is dependent on stimulus intensity in both the TRF and envelope reconstruction analysis. However, provided that the decoder is applied on data of the same stimulus intensity as it was trained on, envelope reconstruction is robust to stimulus intensity. In addition, neural envelope tracking in the delta (but not theta) band seems to relate to speech intelligibility. Similar to the linear decoder analysis, TRF amplitudes and latencies are dependent on stimulus intensity: The amplitude of peak 1 (30-50 ms) increases and the latency of peak 2 (140-160 ms) decreases with increasing stimulus intensity. ConclusionAlthough brain responses are influenced by stimulus intensity, neural envelope tracking is robust to stimulus intensity when using the same intensity to test and train the decoder. Therefore we can assume that intensity is not a confound when testing hearing-impaired participants with amplified speech using the linear decoder approach. In addition, neural envelope tracking in the delta band appears to be correlated with speech intelligibility, showing the potential of neural envelope tracking as an objective measure of speech intelligibility.

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bioRxiv2019

Top-down modulation of neural envelope tracking: the interplay with behavioral, self-reported and neural measures of listening effort

When listening to natural speech, our neural activity tracks the speech envelope. Moreover, recent research has demonstrated that this neural envelope tracking can be affected by top-down processes. The present study was designed to examine if neural envelope tracking is modulated by the effort that a person expends during listening. Five measures were included to quantify listening effort: two behavioral measures based on a novel dual-task paradigm, a self-report effort measure and two neural measures related to neural phase synchronization and alpha power. Electroencephalography responses to sentences, presented at a wide range of subject-specific signal-to-noise ratios, were recorded in thirteen young, normal-hearing adults. A comparison of the five measures revealed different effects of listening effort as a function of speech understanding. Reaction times on the primary task and self-reported effort decreased with increasing speech understanding. In contrast, reaction times on the secondary task and alpha power showed a peak-shaped behavior with highest effort at intermediate speech understanding levels. We found a positive association between envelope tracking and speech understanding. While a significant effect of listening effort was found on theta-band envelope tracking, the effect size was negligible. Therefore, our results suggest that listening effort is not a confound when using envelope tracking to objectively measure speech understanding in young, normal-hearing adults.

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bioRxiv2019

Hearing impairment is associated with enhanced neural tracking of the speech envelope

Elevated hearing thresholds in hearing impaired adults are usually compensated by providing amplification through a hearing aid. In spite of restoring hearing sensitivity, difficulties with understanding speech in noisy environments often remain. One main reason is that sensorineural hearing loss not only causes loss of audibility but also other deficits, including peripheral distortion but also central temporal processing deficits. To investigate the neural consequences of hearing impairment in the brain underlying speech-in-noise difficulties, we compared EEG responses to natural speech of 14 hearing impaired adults with those of 14 age-matched normal-hearing adults. We measured neural envelope tracking to sentences and a story masked by different levels of a stationary noise or competing talker. Despite their sensorineural hearing loss, hearing impaired adults showed higher neural envelope tracking of the target than the competing talker, similar to their normal-hearing peers. Furthermore, hearing impairment was related to an additional increase in neural envelope tracking of the target talker, suggesting that hearing impaired adults may have an enhanced sensitivity to envelope modulations or require a larger differential tracking of target versus competing talker to neurally segregate speech from noise. Lastly, both normal-hearing and hearing impaired participants showed an increase in neural envelope tracking with increasing speech understanding. Hence, our results open avenues towards new clinical applications, such as neuro-steered prostheses as well as objective and automatic measurements of speech understanding performance. HighlightsO_LIAdults with hearing impairment can neurally segregate speech from background noise C_LIO_LIHearing loss is related to enhanced neural envelope tracking of the target talker C_LIO_LINeural envelope tracking has potential to objectively measure speech understanding C_LI

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bioRxiv2019

Effect of task and attention on neural tracking of speech

EEG-based measures of neural tracking of natural running speech are becoming increasingly popular to investigate neural processing of speech and have applications in audiology. When the stimulus is a single speaker, it is usually assumed that the listener actively attends to and understands the stimulus. However, as the level of attention of the listener is inherently variable, we investigated how it affected neural envelope tracking. Using a movie as a distractor, we varied the level of attention while we estimated neural envelope tracking. We varied the intelligibility level by adding stationary noise. We found a significant difference in neural envelope tracking between the condition with maximal attention and the movie condition. This difference was most pronounced in the right-frontal region of the brain. The degree of neural envelope tracking was highly correlated with the stimulus signal-to-noise ratio, even in the movie condition. This could be due to residual neural resources to passively attend to the stimulus. When envelope tracking is used to objectively measure speech understanding this means that the procedure can be made more enjoyable and feasible by letting participants watch a movie during stimulus presentation.

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bioRxiv2019

Data-driven spatial filtering for improved measurement of cortical tracking of multiple representations of speech

ObjectiveMeasurement of the cortical tracking of continuous natural speech from electroencephalography (EEG) recordings using a forward model is becoming an important tool in auditory neuroscience. However, it requires a manual channel selection based on visual inspection or prior knowledge to obtain a summary measure of cortical tracking. In this study, we present a method to on the one hand remove non-stimulus-related activity from the EEG signals to be predicted, and on the other hand automatically select the channels of interest. We also aim to show that the EEG prediction from phonology-related speech features is possible in Dutch. ApproachEighteen participants listened to a Flemish story, while their EEG was recorded. Subject-specific and grand-average temporal responses functions were determined between the EEG activity in different frequency bands and several stimulus features: the envelope, spectrogram, phonemes, phonetic features or a combination. The temporal response functions were then used to predict EEG from the stimulus, and the predicted was compared with the recorded EEG, yielding a measure of cortical tracking of stimulus features. A spatial filter was calculated based on the generalized eigenvalue decomposition (GEVD), and the effect on EEG prediction accuracy was determined. Main resultsA model including both low- and high-level speech representations was able to better predict the brain responses to the speech than a model only including low-level features. The inclusion of a GEVD-based spatial filter in the model increased the prediction accuracy of cortical responses to each speech feature at both single-subject (270% improvement) and group-level (310 %). SignificanceWe showed that the inclusion of acoustical and phonetic speech information and the addition of a data-driven spatial filter allow improved modelling of the relationship between the speech and its brain response and offer an automatic channel selection. HighlightsO_LIAutomatic channel selection for evaluating the cortical tracking of continuous natural speech C_LIO_LIData-driven spatial filtering for removing non-stimulus-related activity from the EEG signals C_LIO_LIImproved prediction of brain responses to speech by combining acoustical and phonetic speech information in Dutch C_LI DisclosureThe authors report no disclosures relevant to the manuscript.

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bioRxiv2019

Stimulus-aware spatial filtering for single-trial neural response and temporal response function estimation in high-density EEG with applications in auditory research

Objective. Neural responses recorded using electroencephalography (EEG) and magnetoencephalography (MEG) can be used to study how our brain functions, as well as for various promising brain computer interface (BCI) applications. However, a common problem is the low signal to noise ratio (SNR) which makes it challenging to estimate task-related neural responses or the temporal response function (TRF) describing the linear relationship between the stimulus and the neural response, particularly over short data windows. To address these, we present an algorithm that takes advantage of the multi-channel nature of the recordings, and knowledge of the presented stimulus, to achieve a joint noise reduction and dimensionality reduction using spatial filtering. Methods. Forward modeling is used to project the stimulus onto the electrode space. The second-order statistics of this estimated desired signal and the raw neural data are used to estimate spatial filters that maximize the SNR of the neural response, based on a generalized eigenvalue decomposition. Main Results. 1. For synthesized EEG data, over a range of SNRs, our filtering resulted in significantly better TRF estimates from 20 s trials, compared to unfiltered EEG data. 2. On a dataset from 28 subjects who listened to a single-talker stimulus, our method resulted in correlations between predicted neural responses and the original EEG data that were significantly higher compared to standard approaches. 3. On a dataset of 16 subjects attending to 1 speaker in a two-speaker scenario, our method resulted in attention decoding accuracies which were higher compared to existing forward modelling methods. Significance. Our algorithm presents a data-driven way to denoise and reduce dimensionality of neural data, thus aiding further analysis, by utilizing the knowledge of the stimulus. The method is computationally efficient, and does not require repeated trials, thereby relieving experiment design from the necessity of presenting repeated stimuli to the subjects.

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bioRxiv2018

Evidence for enhanced neural tracking of the speech envelope underlying age-related speech-in-noise difficulties

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bioRxiv2018

Predicting individual speech intelligibility from the neural tracking of acoustic- and phonetic-level speech representations

ObjectiveTo objectively measure speech intelligibility of individual subjects from the EEG, based on cortical tracking of different representations of speech: low-level acoustical, higher-level discrete, or a combination. To compare each models prediction of the speech reception threshold (SRT) for each individual with the behaviorally measured SRT.\n\nMethodsNineteen participants listened to Flemish Matrix sentences presented at different signal-to-noise ratios (SNRs), corresponding to different levels of speech understanding. For different EEG frequency bands (delta, theta, alpha, beta or low-gamma), a model was built to predict the EEG signal from various speech representations: envelope, spectrogram, phonemes, phonetic features or a combination of phonetic Features and Spectrogram (FS). The same model was used for all subjects. The model predictions were then compared to the actual EEG of each subject for the different SNRs, and the prediction accuracy in function of SNR was used to predict the SRT.\n\nResultsThe model based on the FS speech representation and the theta EEG band yielded the best SRT predictions, with a difference between the behavioral and objective SRT below 1 decibel for 53% and below 2 decibels for 89% of the subjects.\n\nConclusionA model including low- and higher-level speech features allows to predict the speech reception threshold from the EEG of people listening to natural speech. It has potential applications in diagnostics of the auditory system.\n\nSearch Termscortical speech tracking, objective measure, speech intelligibility, auditory processing, speech representations.\n\nHighlightsO_LIObjective EEG-based measure of speech intelligibility\nC_LIO_LIImproved prediction of speech intelligibility by combining speech representations\nC_LIO_LICortical tracking of speech in the delta EEG band monotonically increased with SNRs\nC_LIO_LICortical responses in the theta EEG band best predicted the speech reception threshold\nC_LI\n\nDisclosureThe authors report no disclosures relevant to the manuscript.

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bioRxiv2018

Semantic context enhances neural envelope tracking

ObjectivesRecently an objective measure of speech intelligibility, 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 speech intelligibility can also be used with natural speech as a stimulus, as this would be beneficial for clinical applications. DesignWe 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 speech intelligibility by adding speech weighted noise. Speech intelligibility 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. ResultsFor both stimulus types the correlation between the speech envelope and the reconstructed envelope increased with increasing speech intelligibility. 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 speech intelligibility for both stimuli. Remarkable is that although speech intelligibility remained unchanged in the no noise and +2.5 dB SNR condition, neural speech processing was affected by the addition of this small amount of noise: TRF amplitudes across the entire scalp decreased between 0 to 150 ms, while amplitudes between 150 to 200 ms increased in the presence of noise. TRF latency changes in function of speech intelligibility appeared to be stimulus specific: The latency of the prominent negative peak in the early responses (50-300 ms) increased with increasing speech intelligibility for the Matrix sentences, but remained unchanged for the natural story. ConclusionsThese results show (1) the feasibility of natural speech as a stimulus for the objective measure of speech intelligibility, (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.

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bioRxiv2018

Speech intelligibility predicted from neural entrainment of the speech envelope

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation and memory. Very often electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.

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