Biology subjects

Weissbart, H.

Publications and source records attributed to Weissbart, H..

4 recordsLinked to original sources

bioRxiv2023

The Structure and Statistics of Language jointly shape Cross-frequency Dynamics during Spoken Language Comprehension

Humans excel at extracting structurally-determined meaning from speech despite inherent physical variability. This study explores the brains ability to predict and understand spoken language robustly. It investigates the relationship between structural and statistical language knowledge in brain dynamics, focusing on phase and amplitude modulation. Using syntactic features from constituent hierarchies and surface statistics from a transformer model as predictors of forward encoding models, we reconstructed cross-frequency neural dynamics from MEG data during audiobook listening. Our findings challenge a strict separation of linguistic structure and statistics in the brain, with both aiding neural signal reconstruction. Syntactic features had a more temporally spread impact, and both word entropy and the number of closing syntactic constituents were linked to the phase-amplitude coupling of neural dynamics, implying a role in temporal prediction and cortical oscillation alignment during speech processing. Our results indicate that structured and statistical information jointly shape neural dynamics during spoken language comprehension and suggest an integration process via a cross-frequency coupling mechanism.

neuroscience↗

bioRxiv2022

A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension

When we comprehend language from speech, the phase of the neural response aligns with particular features of the speech input, resulting in a phenomenon referred to as neural tracking. In recent years, a large body of work has demonstrated the tracking of the acoustic envelope and abstract linguistic units at the phoneme and word levels, and beyond. However, the degree to which speech tracking is driven by acoustic edges of the signal, or by internally-generated linguistic units, or by the interplay of both, remains contentious. In this study, we used naturalistic story-listening to investigate (1) whether phoneme-level features are tracked over and above acoustic edges, (2) whether word entropy, which can reflect sentence- and discourse-level constraints, impacted the encoding of acoustic and phoneme-level features, and (3) whether the tracking of acoustic edges was enhanced or suppressed during comprehension of a first language (Dutch) compared to a statistically-familiar but uncomprehended language (French). We first show that encoding models with phoneme-level linguistic features, in addition to acoustic features, uncovered an increased neural tracking response; this signal was further amplified in a comprehended language, putatively reflecting the transformation of acoustic features into internally-generated phoneme-level representations. Phonemes were tracked more strongly in a comprehended language, suggesting that language comprehension functions as a neural filter over acoustic edges of the speech signal as it transforms sensory signals into abstract linguistic units. We then show that word entropy enhances neural tracking of both acoustic and phonemic features when sentence- and discourse-context are less constraining. When language was not comprehended, acoustic features, but not phonemic ones, were more strongly modulated, but in contrast, when a first language is comprehended, phoneme features are more strongly modulated. Taken together, our findings highlight the flexible modulation of acoustic, and phonemic features by sentence and discourse-level constraint in language comprehension, and document the neural transformation from speech perception to language comprehension, consistent with an account of language processing as a neural filter from sensory to abstract representations.

neuroscience↗

bioRxiv2022

Naturalistic language comprehension is supported by alpha and beta oscillations linked to domain-general inhibition and reactivation

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. Alpha oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while beta oscillations are linked to the reactivation of content representations. Can the proposed functional role of alpha and beta oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language processing. Twenty-two (18 female) Dutch native speakers listened to stories in spoken Dutch and French while magnetoencephalography (MEG) was recorded. We used dependency parsing to identify three dependency states at each word, as the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed linear forward models to predict alpha and beta power from the dependency features. Results showed that dependency features predict alpha and beta power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in the alpha band, while frontal and parietal, higher-order language regions, and motor regions are mostly involved in the beta band. Critically, alpha and beta band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Overall, this study sheds light on the role of alpha and beta oscillations during naturalistic language processing, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes. Significance StatementPrior research identified the functional role of alpha and beta oscillations in basic perceptual and motor functions. However, it remains unclear whether their proposed role can be generalized to higher-level processes during language comprehension. Here, we found that high-level syntactic features predict alpha and beta power in language-related regions beyond low-level linguistic features when listening to comprehensible naturalistic speech. Our work contributes to the debate about whether the functional roles of brain oscillations are domain-general or depend on the task at hand. We offer experimental findings that integrate a neuroscientific framework on the role of brain oscillations as "building blocks" with language comprehension as a compositional process, and novel evidence regarding the encoding of higher-level syntactic operations in the brain. This supports the view of a domain-general role of cortical oscillations across the hierarchy of cognitive functions, from low-level sensory operations to complex linguistic processes.

neuroscience↗

bioRxiv2022

The Neural Response at the Fundamental Frequency of Speech is Modulated by Word-level Acoustic and Linguistic Information

Spoken language comprehension requires rapid and continuous integration of information, from lower-level acoustic to higher-level linguistic features. Much of this processing occurs in the cerebral cortex. Its neural activity exhibits, for instance, correlates of predictive processing, emerging at delays of a few hundred milliseconds. However, the auditory pathways are also characterized by extensive feedback loops from higher-level cortical areas to lower-level ones as well as to subcortical structures. Early neural activity can therefore be influenced by higher-level cognitive processes, but it remains unclear whether such feedback contributes to linguistic processing. Here, we investigated early speech-evoked neural activity that emerges at the fundamental frequency. We analyzed EEG recordings obtained when subjects listened to a story read by a single speaker. We identified a response tracking the speakers fundamental frequency that occurred at a delay of 11 ms, while another response elicited by the high-frequency modulation of the envelope of higher harmonics exhibited a larger magnitude and longer latency of about 18 ms. Subsequently, we determined the magnitude of these early neural responses for each individual word in the story. We then quantified the context-independent frequency of each word and used a language model to compute context-dependent word surprisal and precision. The word surprisal represented how predictable a word is, given the previous context, and the word precision reflected the confidence about predicting the next word from the past context. We found that the word-level neural responses at the fundamental frequency were predominantly influenced by the acoustic features: the average fundamental frequency and its variability. Amongst the linguistic features, only context-independent word frequency showed a weak but significant modulation of the neural response to the high-frequency envelope modulation. Our results show that the early neural response at the fundamental frequency is already influenced by acoustic as well as linguistic information, suggesting top-down modulation of this neural response.

neuroscience↗