Delta-band neural activity primarily tracks sentences instead of semantic properties of words

Clinical Diagnostic and Prognostic Value of Residual Language Learning Ability in Patients with Disorders of Consciousness

Recent research suggests that the detection of preserved cognitive function can assist in the diagnosis and prognosis of patients with disorders of consciousness (DoC). This study investigates EEG signals as indicators of neural activity associated with the processing of transitional probabilities during a learning paradigm in patients with DoC. By examining the sensitivity to transitional probabilities across levels of consciousness, we aim to assess the potential value of this indicator in clinical diagnosis and prognosis. We collected EEG recordings from 51 DoC patients (10 female) and 26 healthy controls (9 female). EEG activity was recorded while participants listened to artificial vocabulary speech sequences before and after the learning phase. Intertrial phase coherence (ITPC) was used to examine differences in neural responses in different learning phases. Results showed that minimally conscious patients showed a significant increase in the word-tracking response after the learning phase, similar to healthy controls. Moreover, their learning-mediated word-rate ITPC difference correlated significantly with their Coma Recovery Scale-Revised score and 6 month outcome. However, these correlations were absent in unresponsive wakefulness syndrome patients. Crucially, differences in vocabulary ITPC before and after the learning phase effectively discriminated between healthy controls and patients, as well as between minimally conscious and unresponsive wakefulness syndrome patients. Combining EEG indicators with clinical performance accurately predicted patients' prognosis. In conclusion, the language learning paradigm has the potential to contribute to both diagnosis and prognosis in this challenging population, thereby significantly reducing prognostic uncertainty in medical decision-making and benefiting the rehabilitation of DoC patients.

The Less Meaningful the Understanding, the Faster the Feeling: Speech Comprehension Changes Perceptual Speech Tempo

The perception of speech tempo is influenced by both the acoustic properties of speech and the cognitive state of the listener. However, there is a lack of research on how speech comprehension affects the perception of speech tempo. This study aims to disentangle the impact of speech comprehension on the perception of speech tempo by manipulating linguistic structures and measuring perceptual speech tempo at explicit and implicit levels. Three experiments were conducted to explore these relationships. In Experiment 1, two explicit speech tasks revealed that listeners tend to overestimate the speech tempo of sentences with low comprehensibility, although this effect decreased with repeated exposure to the speech. Experiment 2, utilizing an implicit speech tempo task, replicated the main findings of Experiment 1. Furthermore, the results from the drift-diffusion model eliminated the possibility that participants' responses were based on the type of sentence. In Experiment 3, non-native Chinese speakers with varying levels of language proficiency completed the implicit speech rate task. The results showed that non-native Chinese speakers exhibited distinct behavioral patterns compared to native Chinese speakers, as they did not perceive differences in speech tempo between high and low comprehensibility conditions. These findings highlight the intricate relationship between the perception of speech tempo and the comprehensibility of processed speech.

Low-frequency neural activity tracks syntactic information through semantic mediation

How our brain integrates single words into larger linguistic units is a central focus in neurolinguistic studies. Previous studies mainly explored this topic at the semantic or syntactic level, with few looking at how cortical activities track word sequences with different levels of semantic correlations. In addition, prior research did not tease apart the semantic factors from the syntactic ones in the word sequences. The current study addressed these issues by conducting a speech perception EEG experiment using the frequency-tagging paradigm. Participants (N = 25, Meanage = 23;4, 16 girls) were asked to listen to different types of sequences and their neural activity was recorded by EEG. We also constructed a model simulation based on surprisal values of GPT-2. Both the EEG results and the model prediction show that low-frequency neural activity tracks syntactic information through semantic mediation. Implications of the findings were discussed in relation to the language processing mechanism.

Chunk Duration Limits the Learning of Multiword Chunks: Behavioral and Electroencephalography Evidence from Statistical Learning

Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., low-frequency neural oscillations) may set an upper limit of 2-3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learned chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.

Lexical Surprisal Shapes the Time Course of Syntactic Structure Building

When we understand language, we recognize words and combine them into sentences. In this article, we explore the hypothesis that listeners use probabilistic information about words to build syntactic structure. Recent work has shown that lexical probability and syntactic structure both modulate the delta-band (<4 Hz) neural signal. Here, we investigated whether the neural encoding of syntactic structure changes as a function of the distributional properties of a word. To this end, we analyzed MEG data of 24 native speakers of Dutch who listened to three fairytales with a total duration of 49 min. Using temporal response functions and a cumulative model-comparison approach, we evaluated the contributions of syntactic and distributional features to the variance in the delta-band neural signal. This revealed that lexical surprisal values (a distributional feature), as well as bottom-up node counts (a syntactic feature) positively contributed to the model of the delta-band neural signal. Subsequently, we compared responses to the syntactic feature between words with high- and low-surprisal values. This revealed a delay in the response to the syntactic feature as a consequence of the surprisal value of the word: high-surprisal values were associated with a delayed response to the syntactic feature by 150-190 ms. The delay was not affected by word duration, and did not have a lexical origin. These findings suggest that the brain uses probabilistic information to infer syntactic structure, and highlight an importance for the role of time in this process.

Multiple dimensions of syntactic structure are resolved earliest in posterior temporal cortex

How we combine minimal linguistic units into larger structures remains an unresolved topic in neuroscience. Language processing involves the abstract construction of 'vertical' and 'horizontal' information simultaneously (e.g., phrase structure, morphological agreement), but previous paradigms have been constrained in isolating only one type of composition and have utilized poor spatiotemporal resolution. Using intracranial recordings, we report multiple experiments designed to separate phrase structure from morphosyntactic agreement. Epilepsy patients (n = 10) were presented with auditory two-word phrases grouped into pseudoword-verb ('trab run') and pronoun-verb either with or without Person agreement ('they run' vs. 'they runs'). Phrase composition and Person violations both resulted in significant increases in broadband high gamma activity approximately 300 ms after verb onset in posterior middle temporal gyrus (pMTG) and posterior superior temporal sulcus (pSTS), followed by inferior frontal cortex (IFC) at 500 ms. While sites sensitive to only morphosyntactic violations were distributed, those sensitive to both composition types were generally confined to pSTS/pMTG and IFC. These results indicate that posterior temporal cortex shows the earliest sensitivity for hierarchical linguistic structure across multiple dimensions, providing neural resources for distinct windows of composition. This region is comprised of sparsely interwoven heterogeneous constituents that afford cortical search spaces for dissociable syntactic relations.

Cross-linguistic and acoustic-driven effects on multiscale neural synchrony to stress rhythms

We investigated how neural oscillations code the hierarchical nature of stress rhythms in speech and how stress processing varies with language experience. By measuring phase synchrony of multilevel EEG-acoustic tracking and intra-brain cross-frequency coupling, we show the encoding of stress involves different neural signatures (delta rhythms = stress foot rate; theta rhythms = syllable rate), is stronger for amplitude vs. duration stress cues, and induces nested delta-theta coherence mirroring the stress-syllable hierarchy in speech. Only native English, but not Mandarin, speakers exhibited enhanced neural entrainment at central stress (2 Hz) and syllable (4 Hz) rates intrinsic to natural English. English individuals with superior cortical-stress tracking capabilities also displayed stronger neural hierarchical coherence, highlighting a nuanced interplay between internal nesting of brain rhythms and external entrainment rooted in language-specific speech rhythms. Our cross-language findings reveal brain-speech synchronization is not purely a "bottom-up" but benefits from "top-down" processing from listeners' language-specific experience.

Dissociating prosodic from syntactic delta activity during natural speech comprehension

Decoding human speech requires the brain to segment the incoming acoustic signal into meaningful linguistic units, ranging from syllables and words to phrases. Integrating these linguistic constituents into a coherent percept sets the root of compositional meaning and hence understanding. One important cue for segmentation in natural speech is prosodic cues, such as pauses, but their interplay with higher-level linguistic processing is still unknown. Here, we dissociate the neural tracking of prosodic pauses from the segmentation of multi-word chunks using magnetoencephalography (MEG). We find that manipulating the regularity of pauses disrupts slow speech-brain tracking bilaterally in auditory areas (below 2 Hz) and in turn increases left-lateralized coherence of higher-frequency auditory activity at speech onsets (around 25-45 Hz). Critically, we also find that multi-word chunks-defined as short, coherent bundles of inter-word dependencies-are processed through the rhythmic fluctuations of low-frequency activity (below 2 Hz) bilaterally and independently of prosodic cues. Importantly, low-frequency alignment at chunk onsets increases the accuracy of an encoding model in bilateral auditory and frontal areas while controlling for the effect of acoustics. Our findings provide novel insights into the neural basis of speech perception, demonstrating that both acoustic features (prosodic cues) and abstract linguistic processing at the multi-word timescale are underpinned independently by low-frequency electrophysiological brain activity in the delta frequency range.

Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain

Recent human brain imaging studies have identified widely distributed cortical areas that represent information about the meaning of language. Yet, the dynamic nature of widespread neural activity as a correlate of the semantic information processing remains poorly explored. Our state space analysis of electroencephalograms (EEGs) recorded during semantic match-to-category task show that depending on the semantic category and decision path chosen by participants, whole-brain delta-band dynamics follow distinct trajectories that are correlated with participants' response time on a trial-by-trial basis. Especially, the proximity of the neural trajectory to category decision-specific region in the state space was predictive of participants' decision-making reaction times. We also found that posterolateral regions primarily encoded word categories while postero-central regions encoded category decisions. Our results demonstrate the role of neural dynamics embedded in the evolving multivariate delta-band activity patterns in processing the semantic relatedness of words and the semantic category-based decision-making.

Cross-linguistic and acoustic-driven effects on multiscale neural synchrony to stress rhythms

We investigated how neural oscillations code the hierarchical nature of stress rhythms in speech and how stress processing varies with language experience. By measuring phase synchrony of multilevel EEG-acoustic tracking and intra-brain cross-frequency coupling, we show the encoding of stress involves different neural signatures (delta rhythms = stress foot rate; theta rhythms = syllable rate), is stronger for amplitude vs. duration stress cues, and induces nested delta-theta coherence mirroring the stress-syllable hierarchy in speech. Only native English, but not Mandarin, speakers exhibited enhanced neural entrainment at central stress (2 Hz) and syllable (4 Hz) rates intrinsic to natural English. English individuals with superior cortical-stress tracking capabilities also displayed stronger neural hierarchical coherence, highlighting a nuanced interplay between internal nesting of brain rhythms and external entrainment rooted in language-specific speech rhythms. Our cross-language findings reveal brain-speech synchronization is not purely a "bottom-up" but benefits from "top-down" processing from listeners' language-specific experience.

EEG-based speaker-listener neural coupling reflects speech-selective attentional mechanisms beyond the speech stimulus

When we pay attention to someone, do we focus only on the sound they make, the word they use, or do we form a mental space shared with the speaker we want to pay attention to? Some would argue that the human language is no other than a simple signal, but others claim that human beings understand each other because they form a shared mental ground between the speaker and the listener. Our study aimed to explore the neural mechanisms of speech-selective attention by investigating the electroencephalogram-based neural coupling between the speaker and the listener in a cocktail party paradigm. The temporal response function method was employed to reveal how the listener was coupled to the speaker at the neural level. The results showed that the neural coupling between the listener and the attended speaker peaked 5 s before speech onset at the delta band over the left frontal region, and was correlated with speech comprehension performance. In contrast, the attentional processing of speech acoustics and semantics occurred primarily at a later stage after speech onset and was not significantly correlated with comprehension performance. These findings suggest a predictive mechanism to achieve speaker-listener neural coupling for successful speech comprehension.

Phase-locking of Neural Activity to the Envelope of Speech in the Delta Frequency Band Reflects Differences between Word Lists and Sentences

The envelope of a speech signal is tracked by neural activity in the cerebral cortex. The cortical tracking occurs mainly in two frequency bands, theta (4-8 Hz) and delta (1-4 Hz). Tracking in the faster theta band has been mostly associated with lower-level acoustic processing, such as the parsing of syllables, whereas the slower tracking in the delta band relates to higher-level linguistic information of words and word sequences. However, much regarding the more specific association between cortical tracking and acoustic as well as linguistic processing remains to be uncovered. Here, we recorded EEG responses to both meaningful sentences and random word lists in different levels of signal-to-noise ratios (SNRs) that lead to different levels of speech comprehension as well as listening effort. We then related the neural signals to the acoustic stimuli by computing the phase-locking value (PLV) between the EEG recordings and the speech envelope. We found that the PLV in the delta band increases with increasing SNR for sentences but not for the random word lists, showing that the PLV in this frequency band reflects linguistic information. When attempting to disentangle the effects of SNR, speech comprehension, and listening effort, we observed a trend that the PLV in the delta band might reflect listening effort rather than the other two variables, although the effect was not statistically significant. In summary, our study shows that the PLV in the delta band reflects linguistic information and might be related to listening effort.

Dynamic networks differentiate the language ability of children with cochlear implants

Background

Cochlear implantation (CI) in prelingually deafened children has been shown to be an effective intervention for developing language and reading skill. However, there is a substantial proportion of the children receiving CI who struggle with language and reading. The current study-one of the first to implement electrical source imaging in CI population was designed to identify the neural underpinnings in two groups of CI children with good and poor language and reading skill.

Methods

Data using high density electroencephalography (EEG) under a resting state condition was obtained from 75 children, 50 with CIs having good (HL) or poor language skills (LL) and 25 normal hearing (NH) children. We identified coherent sources using dynamic imaging of coherent sources (DICS) and their effective connectivity computing time-frequency causality estimation based on temporal partial directed coherence (TPDC) in the two CI groups compared to a cohort of age and gender matched NH children.

Findings

Sources with higher coherence amplitude were observed in three frequency bands (alpha, beta and gamma) for the CI groups when compared to normal hearing children. The two groups of CI children with good (HL) and poor (LL) language ability exhibited not only different cortical and subcortical source profiles but also distinct effective connectivity between them. Additionally, a support vector machine (SVM) algorithm using these sources and their connectivity patterns for each CI group across the three frequency bands was able to predict the language and reading scores with high accuracy.

Interpretation

Increased coherence in the CI groups suggest overall that the oscillatory activity in some brain areas become more strongly coupled compared to the NH group. Moreover, the different sources and their connectivity patterns and their association to language and reading skill in both groups, suggest a compensatory adaptation that either facilitated or impeded language and reading development. The neural differences in the two groups of CI children may reflect potential biomarkers for predicting outcome success in CI children.

Spatiotemporally distributed frontotemporal networks for sentence reading

Reading a sentence entails integrating the meanings of individual words to infer more complex, higher-order meaning. This highly rapid and complex human behavior is known to engage the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) in the language-dominant hemisphere, yet whether there are distinct contributions of these regions to sentence reading is still unclear. To probe these neural spatiotemporal dynamics, we used direct intracranial recordings to measure neural activity while reading sentences, meaning-deficient Jabberwocky sentences, and lists of words or pseudowords. We isolated two functionally and spatiotemporally distinct frontotemporal networks, each sensitive to distinct aspects of word and sentence composition. The first distributed network engages the IFG and MTG, with IFG activity preceding MTG. Activity in this network ramps up over the duration of a sentence and is reduced or absent during Jabberwocky and word lists, implying its role in the derivation of sentence-level meaning. The second network engages the superior temporal gyrus and the IFG, with temporal responses leading those in frontal lobe, and shows greater activation for each word in a list than those in sentences, suggesting that sentential context enables greater efficiency in the lexical and/or phonological processing of individual words. These adjacent, yet spatiotemporally dissociable neural mechanisms for word- and sentence-level processes shed light on the richly layered semantic networks that enable us to fluently read. These results imply distributed, dynamic computation across the frontotemporal language network rather than a clear dichotomy between the contributions of frontal and temporal structures.

Delta-band neural tracking primarily reflects rule-based chunking instead of semantic relatedness between words

It is debated whether cortical responses matching the time scales of phrases and sentences mediate the mental construction of the syntactic chunks or are simply caused by the semantic properties of words. Here, we investigate to what extent delta-band neural responses to speech can be explained by semantic relatedness between words. To dissociate the contribution of semantic relatedness from sentential structures, participants listened to sentence sequences and paired-word sequences in which semantically related words repeated at 1 Hz. Semantic relatedness in the 2 types of sequences was quantified using a word2vec model that captured the semantic relation between words without considering sentential structure. The word2vec model predicted comparable 1-Hz responses with paired-word sequences and sentence sequences. However, empirical neural activity, recorded using magnetoencephalography, showed a weaker 1-Hz response to paired-word sequences than sentence sequences in a word-level task that did not require sentential processing. Furthermore, when listeners applied a task-related rule to parse paired-word sequences into multi-word chunks, 1-Hz response was stronger than that in word-level task on the same sequences. Our results suggest that cortical activity tracks multi-word chunks constructed by either syntactic rules or task-related rules, whereas the semantic relatedness between words contributes only in a minor way.

Compromised word-level neural tracking in the high-gamma band for children with attention deficit hyperactivity disorder

Children with attention deficit hyperactivity disorder (ADHD) exhibit pervasive difficulties in speech perception. Given that speech processing involves both acoustic and linguistic stages, it remains unclear which stage of speech processing is impaired in children with ADHD. To investigate this issue, we measured neural tracking of speech at syllable and word levels using electroencephalography (EEG), and evaluated the relationship between neural responses and ADHD symptoms in 6-8 years old children. Twenty-three children participated in the current study, and their ADHD symptoms were assessed with SNAP-IV questionnaires. In the experiment, the children listened to hierarchical speech sequences in which syllables and words were, respectively, repeated at 2.5 and 1.25 Hz. Using frequency domain analyses, reliable neural tracking of syllables and words was observed in both the low-frequency band (<4 Hz) and the high-gamma band (70-160 Hz). However, the neural tracking of words in the high-gamma band showed an anti-correlation with the ADHD symptom scores of the children. These results indicate that ADHD prominently impairs cortical encoding of linguistic information (e.g., words) in speech perception.

Working memory asymmetrically modulates auditory and linguistic processing of speech

Working memory load can modulate speech perception. However, since speech perception and working memory are both complex functions, it remains elusive how each component of the working memory system interacts with each speech processing stage. To investigate this issue, we concurrently measure how the working memory load modulates neural activity tracking three levels of linguistic units, i.e., syllables, phrases, and sentences, using a multiscale frequency-tagging approach. Participants engage in a sentence comprehension task and the working memory load is manipulated by asking them to memorize either auditory verbal sequences or visual patterns. It is found that verbal and visual working memory load modulate speech processing in similar manners: Higher working memory load attenuates neural activity tracking of phrases and sentences but enhances neural activity tracking of syllables. Since verbal and visual WM load similarly influence the neural responses to speech, such influences may derive from the domain-general component of WM system. More importantly, working memory load asymmetrically modulates lower-level auditory encoding and higher-level linguistic processing of speech, possibly reflecting reallocation of attention induced by mnemonic load.

Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension

Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5-3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., "sheep white grass eat" instead of "white sheep eat grass"), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts.

Overt and implicit prosody contribute to neurophysiological responses previously attributed to grammatical processing

Recent neurophysiological research suggests that slow cortical activity tracks hierarchical syntactic structure during online sentence processing. Here we tested an alternative hypothesis: electrophysiological activity peaks at constituent phrase as well as sentence frequencies reflect cortical tracking of overt or covert (implicit) prosodic grouping. Participants listened to series of sentences presented in three conditions while electroencephalography (EEG) was recorded. First, prosodic cues in the sentence materials were neutralized. We found an EEG spectral power peak elicited at a frequency that only 'tagged' covert, implicit prosodic change, but not any major syntactic constituents. In the second condition, participants listened to a series of sentences with overt prosodic grouping cues that either aligned or misaligned with the syntactic phrasing in the sentences (initial overt prosody trials). Following each overt prosody trial, participants were presented with a second series of sentences lacking overt prosodic cues (instructed prosody trial) and were instructed to imagine the prosodic contour present in the previous, overt prosody trial. The EEG responses reflected an interactive relationship between syntactic processing and prosodic tracking at the frequencies of syntactic constituents (sentences and phrases): alignment of syntax and prosody boosted EEG responses, whereas their misalignment had an opposite effect. This was true for both overt and imagined prosody conditions. We conclude that processing of both overt and covert prosody is reflected in the frequency-tagged neural responses at sentence constituent frequencies. These findings need to be incorporated in any account that aims to identify neural markers reflecting syntactic processing.