Biology subjects

Gillis, M.

Publications and source records attributed to Gillis, M..

9 recordsLinked to original sources

bioRxiv2023

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

Observing lip movements of a speaker is known to facilitate speech understanding, especially in challenging listening situations. Converging evidence from neuroscientific studies shows enhanced processing of audiovisual stimuli. However, the interindividual variability of this visual benefit and its consequences on behavior are unknown. Here, we analyzed source-localized magnetoencephalographic (MEG) responses from normal-hearing participants listening to audiovisual speech with or without an additional distractor speaker. Using temporal response functions (TRFs), we show that neural responses to lip movements are, in general, enhanced when speech is challenging. After conducting a crucial control for speech acoustics, we show that lip movements effectively contribute to higher neural speech tracking, particularly when a distractor speaker is present. However, the extent of this visual benefit varied greatly among participants. Probing the behavioral relevance, we show that individuals who benefit more from lip movement information in terms of neural speech tracking, show a stronger drop in performance and an increase in perceived difficulty when the mouth is occluded by a surgical face mask. By contrast, no effect was found when the mouth was not occluded. We provide novel insights on how the benefit of lip movements in terms of neural speech tracking varies among individuals. Furthermore, we reveal its behavioral relevance by demonstrating negative consequences for behavior when visual speech is absent. Our results also offer potential implications for future objective assessments of audiovisual speech perception.

neuroscience↗

bioRxiv2023

Robust neural tracking of linguistic speech representations using a convolutional neural network.

ObjectiveWhen listening to continuous speech, populations of neurons in the brain track different features of the signal. Neural tracking can be measured by relating the electroencephalography (EEG) and the speech signal. Recent studies have shown a significant contribution of linguistic features over acoustic neural tracking using linear models. However, linear models cannot model the nonlinear dynamics of the brain. To overcome this, we use a convolutional neural network (CNN) that relates EEG to linguistic features using phoneme or word onsets as a control and has the capacity to model non-linear relations. ApproachWe integrate phoneme- and word-based linguistic features (phoneme surprisal, cohort entropy, word surprisal and word frequency) in our nonlinear CNN model and investigate if they carry additional information on top of lexical features (phoneme and word onsets). We then compare the performance of our nonlinear CNN with that of a linear encoder and a linearized CNN. Main resultsFor the non-linear CNN, we found a significant contribution of cohort entropy over phoneme onsets and of word surprisal and word frequency over word onsets. Moreover, the non-linear CNN outperformed the linear baselines. SignificanceMeasuring coding of linguistic features in the brain is important for auditory neuroscience research and applications that involve objectively measuring speech understanding. With linear models, this is measurable, but the effects are very small. The proposed non-linear CNN model yields larger differences between linguistic and lexical models and, therefore, could show effects that would otherwise be unmeasurable and may, in the future, lead to improved within-subject measures and shorter recordings. Index TermsEEG decoding, speech processing, CNN, linguistics.

neuroscience↗

bioRxiv2023

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

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

neuroscience↗

bioRxiv2022

Heard or understood? Neural tracking of language features in a comprehensible story, an incomprehensible story and a word list

Speech comprehension is a complex neural process on which relies on activation and integration of multiple brain regions. In the current study, we evaluated whether speech comprehension can be investigated by neural tracking. Neural tracking is the phenomenon in which the brain responses time-lock to the rhythm of specific features in continuous speech. These features can be acoustic, i.e., acoustic tracking, or derived from the content of the speech using language properties, i.e., language tracking. We evaluated whether neural tracking of speech differs between a comprehensible story, an incomprehensible story, and a word list. We evaluated the neural responses to speech of 19 participants (6 men). No significant difference regarding acoustic tracking was found. However, significant language tracking was only found for the comprehensible story. The most prominent effect was visible to word surprisal, a language feature at the word level. The neural response to word surprisal showed a prominent negativity between 300 and 400 ms, similar to the N400 in evoked response paradigms. This N400 was significantly more negative when the story was comprehended, i.e., when words could be integrated in the context of previous words. These results show that language tracking can capture the effect of speech comprehension. Significance statementMost neural tracking studies focus on how the brain tracks acoustic speech features. However, whether acoustic tracking reflects speech comprehension is unclear. Therefore, in the pursuit of finding a neural marker for speech comprehension, language tracking might be a more suitable candidate. The results of this study showed that, indeed, language tracking can capture the effect of speech comprehension. This indicates that language tracking is a potential neural marker of speech comprehension. Such a neural marker would allow testing speech comprehension in populations that are currently difficult to test with behavioral tests, such as young children and persons with cognitive impairment.

neuroscience↗

bioRxiv2022

Linguistic speech processing decreases with advancing age

BackgroundOlder adults process speech differently, but it is not yet clear how aging affects different levels of processing natural, continuous speech, both in terms of bottom-up acoustic analysis and top-down generation of linguistic-based predictions. We studied natural speech processing across the adult lifespan via electroencephalography (EEG) measurements of neural tracking. GoalsOur goals are to analyze the unique contribution of linguistic speech processing across the adult lifespan using natural speech, while controlling for the influence of acoustic processing. In particular, we focus on changes in spatial and temporal activation patterns in response to natural speech across the lifespan. Methods52 normal-hearing adults between 17 and 82 years of age listened to a naturally spoken story while the EEG signal was recorded. We investigated the effect of age on acoustic and linguistic processing of speech. Because age correlated with hearing capacity and measures of cognition, we investigated whether the observed age effect is mediated by these factors. Furthermore, we investigated whether there is an effect of age on hemisphere lateralization and on spatiotemporal patterns of the neural responses. ResultsOur EEG results showed that linguistic speech processing declines with advancing age. More-over, as age increased, the neural response latency to certain aspects of linguistic speech processing increased. Also acoustic neural tracking (NT) decreased with increasing age but in contrast to linguistic processing, older subjects showed shorter latencies for early acoustic responses to speech. No evidence was found for hemispheric lateralization in neither younger nor older adults during linguistic speech processing. Most of the observed aging effects on acoustic and linguistic processing were not explained by age-related decline in hearing capacity or cognition. However, our results suggest that the effect of decreasing linguistic neural tracking with advancing age at word-level is likely more due to an age-related decline in cognition than a robust effect of age. ConclusionSpatial and temporal characteristics of the neural responses to continuous speech change across the adult lifespan for both acoustic and linguistic speech processing. These changes may be traces of structural and/or functional change that occurs with advancing age. HighlightsO_LIWith increasing age, linguistic neural tracking of continuous speech decreases. C_LIO_LIWith increasing age, the processing speed of linguistic aspects of speech slows down. C_LIO_LIAging-related changes in word-level linguistic processing are affected by cognition. C_LIO_LIWith advancing age, tracking of speech acoustics decreases in the right hemisphere. C_LIO_LIOlder adults displayed earlier neural responses to speech acoustics. C_LI

neuroscience↗

bioRxiv2022

Speech understanding oppositely affectsacoustic and linguistic neural tracking in aspeech rate manipulation paradigm.

When listening to continuous speech, the human brain can track features of the presented speech signal. It has been shown that neural tracking of acoustic features is a prerequisite for speech understanding and can predict speech understanding in controlled circumstances. However, the brain also tracks linguistic features of speech, which may be more directly related to speech understanding. We investigated acoustic and linguistic speech processing as a function of varying speech understanding by manipulating the speech rate. In this paradigm, acoustic and linguistic speech processing are affected simultaneously but in opposite directions: When the speech rate increases, more acoustic information per second is present. In contrast, the tracking of linguistic information becomes more challenging when speech is less intelligible at higher speech rates. We measured the EEG of 18 participants (4 male) who listened to speech at various speech rates. As expected and confirmed by the behavioral results, speech understanding decreased with increasing speech rate. Accordingly, linguistic neural tracking decreased with increasing speech rate, but acoustic neural tracking increased. This indicates that neural tracking of linguistic representations can capture the gradual effect of decreasing speech understanding. In addition, increased acoustic neural tracking does not necessarily imply better speech understanding. This suggests that, although more challenging to measure due to the low signal-to-noise ratio, linguistic neural tracking may be a more direct predictor of speech understanding. Significance statementAn increasingly popular method to investigate neural speech processing is to measure neural tracking. Although much research has been done on how the brain tracks acoustic speech features, linguistic speech features have received less attention. In this study, we disentangled acoustic and linguistic characteristics of neural speech tracking via manipulating the speech rate. A proper way of objectively measuring auditory and language processing paves the way towards clinical applications: An objective measure of speech understanding would allow for behavioral-free evaluation of speech understanding, which allows to evaluate hearing loss and adjust hearing aids based on brain responses. This objective measure would benefit populations from whom obtaining behavioral measures may be complex, such as young children or people with cognitive impairments.

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bioRxiv2021

Neural tracking as an objective measure of auditory perception and speech intelligibility

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 brains 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 speechrelated 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 individuals auditory and linguistic processing.

neuroscience↗

bioRxiv2021

Neural markers of speech comprehension: measuring EEG tracking of linguistic speech representations, controlling the speech acoustics

When listening to speech, our brain responses time-lock to acoustic events in the stimulus. Recent studies have also reported that cortical responses track linguistic representations of speech. However, tracking of these representations is often described without controlling for acoustic properties. Therefore, the response to these linguistic representations might reflect unaccounted acoustic processing rather than language processing. Here, we evaluated the potential of several recently proposed linguistic representations as neural markers of speech comprehension. To do so, we investigated EEG responses to audiobook speech of 29 participants (22 [female]). We examined whether these representations contribute unique information over and beyond acoustic neural tracking and each other. Indeed, not all of these linguistic representations were significantly tracked after controlling for acoustic properties. However, phoneme surprisal, cohort entropy, word surprisal, and word frequency were all significantly tracked over and beyond acoustic properties. We also tested the generality of the associated responses by training on one story and testing on another. In general, the linguistic representations are tracked similarly across different stories spoken by different readers. These results suggests that these representations characterize processing of the linguistic content of speech. Significance StatementFor clinical applications it would be desirable to develop a neural marker of speech comprehension derived from neural responses to continuous speech. Such a measure would allow for behaviour-free evaluation of speech understanding; this would open doors towards better quantification of speech understanding in populations from whom obtaining behavioral measures may be difficult, such as young children or people with cognitive impairments, to allow better targeted interventions and better fitting of hearing devices.

neuroscience↗

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.

neuroscience↗