Publications

Abstract

It has long been recognised that phrases and sentences are organised hierarchically, but many computational models of language treat them as sequences of words without computing constituent structure. Against this background, we conducted two experiments which showed that participants interpret ambiguous noun phrases, such as second blue ball, in terms of their abstract hierarchical structure rather than their linear surface order. When a neural network model was tested on this task, it could simulate such “hierarchical” behaviour. However, when we changed the training data such that they were not entirely unambiguous anymore, the model stopped generalising in a human-like way. It did not systematically generalise to novel items, and when it was trained on ambiguous trials, it strongly favoured the linear interpretation. We argue that these models should be endowed with a bias to make generalisations over hierarchical structure in order to be cognitively adequate models of human language.

Abstract

Recent research has established that cortical activity “tracks” the presentation rate of syntactic phrases in continuous speech, even though phrases are abstract units that do not have direct correlates in the acoustic signal. We investigated whether cortical tracking of phrase structures is modulated by the extent to which these structures compositionally determine meaning. To this end, we recorded electroencephalography (EEG) of 38 native speakers who listened to naturally spoken Dutch stimuli in different conditions, which parametrically modulated the degree to which syntactic structure and lexical semantics determine sentence meaning. Tracking was quantified through mutual information between the EEG data and either the speech envelopes or abstract annotations of syntax, all of which were filtered in the frequency band corresponding to the presentation rate of phrases (1.1–2.1 Hz). Overall, these mutual information analyses showed stronger tracking of phrases in regular sentences than in stimuli whose lexical-syntactic content is reduced, but no consistent differences in tracking between sentences and stimuli that contain a combination of syntactic structure and lexical content. While there were no effects of compositional meaning on the degree of phrase-structure tracking, analyses of event-related potentials elicited by sentence-final words did reveal meaning-induced differences between conditions. Our findings suggest that cortical tracking of structure in sentences indexes the internal generation of this structure, a process that is modulated by the properties of its input, but not by the compositional interpretation of its output.

Abstract

Listening to speech is difficult in noisy environments, and is even harder when the interfering noise consists of intelligible speech as compared to unintelligible sounds. This suggests that the competing linguistic information interferes with the neural processing of target speech. Interference could either arise from a degradation of the neural representation of the target speech, or from increased representation of distracting speech that enters in competition with the target speech. We tested these alternative hypotheses using magnetoencephalography (MEG) while participants listened to a target clear speech in the presence of distracting noise-vocoded speech. Crucially, the distractors were initially unintelligible but became more intelligible after a short training session. Results showed that the comprehension of the target speech was poorer after training than before training. The neural tracking of target speech in the delta range (1–4 Hz) reduced in strength in the presence of a more intelligible distractor. In contrast, the neural tracking of distracting signals was not significantly modulated by intelligibility. These results suggest that the presence of distracting speech signals degrades the linguistic representation of target speech carried by delta oscillations.

Abstract

The neurobiology of sentence production has been largely understudied compared to the neurobiology of sentence comprehension, due to difficulties with experimental control and motion-related artifacts in neuroimaging. We studied the neural response to constituents of increasing size and specifically focused on the similarities and differences in the production and comprehension of the same stimuli. Participants had to either produce or listen to stimuli in a gradient of constituent size based on a visual prompt. Larger constituent sizes engaged the left inferior frontal gyrus (LIFG) and middle temporal gyrus (LMTG) extending to inferior parietal areas in both production and comprehension, confirming that the neural resources for syntactic encoding and decoding are largely overlapping. An ROI analysis in LIFG and LMTG also showed that production elicited larger responses to constituent size than comprehension and that the LMTG was more engaged in comprehension than production, while the LIFG was more engaged in production than comprehension. Finally, increasing constituent size was characterized by later BOLD peaks in comprehension but earlier peaks in production. These results show that syntactic encoding and parsing engage overlapping areas, but there are asymmetries in the engagement of the language network due to the specific requirements of production and comprehension.

Abstract

Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable neural signatures of predictions about syntactic category (parts of speech), phonemes, and semantics. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.

Abstract

Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index*frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150ms) and late stages of word processing, but interact during later stages of word processing (>150-250ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neuro-cognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.

Abstract

Traditional experiments indicate that prediction is important for efficient speech processing. In three virtual reality visual world paradigm experiments, we tested whether such findings hold in naturalistic settings (Experiment 1) and provided novel insights into whether disfluencies in speech (repairs/hesitations) inform one’s predictions in rich environments (Experiments 2–3). Experiment 1 supports that listeners predict upcoming speech in naturalistic environments, with higher proportions of anticipatory target fixations in predictable compared to unpredictable trials. In Experiments 2–3, disfluencies reduced anticipatory fixations towards predicted referents, compared to conjunction (Experiment 2) and fluent (Experiment 3) sentences. Unexpectedly, Experiment 2 provided no evidence that participants made new predictions from a repaired verb. Experiment 3 provided novel findings that fixations towards the speaker increase upon hearing a hesitation, supporting current theories of how hesitations influence sentence processing. Together, these findings unpack listeners’ use of visual (objects/speaker) and auditory (speech/disfluencies) information when predicting upcoming words.

Abstract

Introduction: Mood is a constant in our daily life and can permeate all levels of cognition. We examined whether and how mood influences the processing of discourse content that is relatively neutral and not loaded with emotion. During discourse processing, readers have to constantly strike a balance between what they know in long term memory and what the current discourse is about. Our general hypothesis is that mood states would affect this balance. We hypothesized that readers in a positive mood would rely more on default world knowledge, whereas readers in a negative mood would be more inclined to analyze the details in the current discourse.

Methods: Participants were put in a positive and a negative mood via film clips, one week apart. In each session, after mood manipulation, they were presented with sentences in discourse materials. We created sentences such as “With the lights on you can see...” that end with critical words (CWs) “more” or “less”, where general knowledge supports “more”, not “less”. We then embedded each of these sentences in a wider discourse that does/does not support the CWs (a story about driving in the night vs. stargazing). EEG was recorded throughout.

Results: The results showed that first, mood manipulation was successful in that there was a significant mood difference between sessions. Second, mood did not modulate the N400 effects. Participants in both moods detected outright semantic violations and allowed world knowledge to be overridden by discourse context. Third, mood modulated the LPC (Late Positive Component) effects, distributed in the frontal region. In negative moods, the LPC was sensitive to one-level violation. That is, CWs that were supported by only world knowledge, only discourse, and neither, elicited larger frontal LPCs, in comparison to the condition where CWs were supported by both world knowledge and discourse.

Discussion: These results suggest that mood does not influence all processes involved in discourse processing. Specifically, mood does not influence lexical-semantic retrieval (N400), but it does influence elaborative processes for sensemaking (P600) during discourse processing. These results advance our understanding of the impact and time course of mood on discourse.

Abstract

The ability to comprehend phrases is an essential integrative property of the brain. Here we evaluate the neural processes that enable the transition from single word processing to a minimal compositional scheme. Previous research has reported conflicting timing effects of composition, and disagreement persists with respect to inferior frontal and posterior temporal contributions. To address these issues, 19 patients (10 male, 19 female) implanted with penetrating depth or surface subdural intracranial electrodes heard auditory recordings of adjective-noun, pseudoword-noun and adjective-pseudoword phrases and judged whether the phrase matched a picture. Stimulus-dependent alterations in broadband gamma activity, low frequency power and phase-locking values across the language-dominant left hemisphere were derived. This revealed a mosaic located on the lower bank of the posterior superior temporal sulcus (pSTS), in which closely neighboring cortical sites displayed exclusive sensitivity to either lexicality or phrase structure, but not both. Distinct timings were found for effects of phrase composition (210–300 ms) and pseudoword processing (approximately 300–700 ms), and these were localized to neighboring electrodes in pSTS. The pars triangularis and temporal pole encoded anticipation of composition in broadband low frequencies, and both regions exhibited greater functional connectivity with pSTS during phrase composition. Our results suggest that the pSTS is a highly specialized region comprised of sparsely interwoven heterogeneous constituents that encodes both lower and higher level linguistic features. This hub in pSTS for minimal phrase processing may form the neural basis for the human-specific computational capacity for forming hierarchically organized linguistic structures.

Abstract

This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe (LaTL) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

Abstract

Vocal learning, the ability to produce modified vocalizations via learning from acoustic signals, is a key trait in the evolution of speech. While extensively studied in songbirds, mammalian models for vocal learning are rare. Bats present a promising study system given their gregarious natures, small size, and the ability of some species to be maintained in captive colonies. We utilize the pale spear-nosed bat (Phyllostomus discolor) and report advances in establishing this species as a tractable model for understanding vocal learning. We have taken an interdisciplinary approach, aiming to provide an integrated understanding across genomics (Part I), neurobiology (Part II), and transgenics (Part III). In Part I, we generated new, high-quality genome annotations of coding genes and noncoding microRNAs to facilitate functional and evolutionary studies. In Part II, we traced connections between auditory-related brain regions and reported neuroimaging to explore the structure of the brain and gene expression patterns to highlight brain regions. In Part III, we created the first successful transgenic bats by manipulating the expression of FoxP2, a speech-related gene. These interdisciplinary approaches are facilitating a mechanistic and evolutionary understanding of mammalian vocal learning and can also contribute to other areas of investigation that utilize P. discolor or bats as study species.

Abstract

Predictive language processing is often studied by measuring eye movements as participants look at objects on a computer screen while they listen to spoken sentences. The use of this variant of the visual world paradigm has shown that information encountered by a listener at a spoken verb can give rise to anticipatory eye movements to a target object, which is taken to indicate that people predict upcoming words. The ecological validity of such findings remains questionable, however, because these computer experiments used two-dimensional (2D) stimuli that are mere abstractions of real world objects. Here we present a visual world paradigm study in a three-dimensional (3D) immersive virtual reality environment. Despite significant changes in the stimulus material and the different mode of stimulus presentation, language-mediated anticipatory eye movements were observed. These findings thus indicate prediction of upcoming words in language comprehension in a more naturalistic setting where natural depth cues are preserved. Moreover, the results confirm the feasibility of using eye-tracking in rich and multimodal 3D virtual environments.

Abstract

When talking, speakers continuously monitor and use the auditory feedback of their own voice to control and inform speech production processes. When speakers are provided with auditory feedback that is perturbed in real time, most of them compensate for this by opposing the feedback perturbation. But some speakers follow the perturbation. In the current study, we investigated whether the state of the speech production system at perturbation onset may determine what type of response (opposing or following) is given. The results suggest that whether a perturbation-related response is opposing or following depends on ongoing fluctuations of the production system: It initially responds by doing the opposite of what it was doing. This effect and the non-trivial proportion of following responses suggest that current production models are inadequate: They need to account for why responses to unexpected sensory feedback depend on the production-system’s state at the time of perturbation.

Abstract

Speaking is a complex motor skill which requires near instantaneous integration of sensory and motor-related information. Current theory hypothesizes a complex interplay between motor and auditory processes during speech production, involving the online comparison of the speech output with an internally generated forward model. To examine the neural correlates of this intricate interplay between sensory and motor processes, the current study uses altered auditory feedback (AAF) in combination with magnetoencephalography (MEG). Participants vocalized the vowel/e/and heard auditory feedback that was temporarily pitch-shifted by only 25 cents, while neural activity was recorded with MEG. As a control condition, participants also heard the recordings of the same auditory feedback that they heard in the first half of the experiment, now without vocalizing. The participants were not aware of any perturbation of the auditory feedback. We found auditory cortical areas responded more strongly to the pitch shifts during vocalization. In addition, auditory feedback perturbation resulted in spectral power increases in the θ and lower β bands, predominantly in sensorimotor areas. These results are in line with current models of speech production, suggesting auditory cortical areas are involved in an active comparison between a forward model's prediction and the actual sensory input. Subsequently, these areas interact with motor areas to generate a motor response. Furthermore, the results suggest that θ and β power increases support auditory-motor interaction, motor error detection and/or sensory prediction processing.

Abstract

Participants’ performance differs when conducting a task in the presence of a secondary individual, moreover the opinion the participant has of this individual also plays a role. Using EEG, we investigated how previous interactions with, and evaluations of, an avatar in virtual reality subsequently influenced attentional allocation to the face of that avatar. We focused on changes in the alpha activity as an index of attentional allocation. We found that the onset of an avatar’s face whom the participant had developed a rapport with induced greater alpha suppression. This suggests greater attentional resources are allocated to the interacted-with avatars. The evaluative ratings of the avatar induced a U-shaped change in alpha suppression, such that participants paid most attention when the avatar was rated as average. These results suggest that attentional allocation is an important element of how behaviour is altered in the presence of a secondary individual and is modulated by our opinion of that individual.

Abstract

Low-frequency neural entrainment to rhythmic input
has been hypothesized as a canonical mechanism
that shapes sensory perception in time. Neural
entrainment is deemed particularly relevant for
speech analysis, as it would contribute to the extraction
of discrete linguistic elements from continuous
acoustic signals. However, its causal influence in
speech perception has been difficult to establish.
Here, we provide evidence that oscillations build temporal
predictions about the duration of speech tokens
that affect perception. Using magnetoencephalography
(MEG), we studied neural dynamics during
listening to sentences that changed in speech rate.
Weobserved neural entrainment to preceding speech
rhythms persisting for several cycles after the change
in rate. The sustained entrainment was associated
with changes in the perceived duration of the last
word’s vowel, resulting in the perception of words
with different meanings. These findings support oscillatory
models of speech processing, suggesting that
neural oscillations actively shape speech perception.

Abstract

Neural oscillations may be instrumental for the tracking and segmentation of continuous speech. Earlier work has suggested that delta, theta and gamma oscillations entrain to the speech rhythm. We used magnetoencephalography and a large sample of 102 participants to investigate oscillatory entrainment to speech, and observed robust entrainment of delta and theta activity, and weak group-level gamma entrainment. We show that the peak frequency and the hemispheric lateralisation of the entrainment are subject to considerable individual variability. The first finding may support the involvement of intrinsic oscillations in entrainment, and the second finding suggests that there is no systematic default right-hemispheric bias for processing acoustic signals on a slow time scale. Although low frequency entrainment to speech is a robust phenomenon, the characteristics of entrainment vary across individuals, and this variation is important for understanding the underlying neural mechanisms of entrainment, as well as its functional significance.

Abstract

Syntactic binding refers to combining words into larger structures. Using EEG, we investigated the neural processes involved in syntactic binding. Participants were auditorily presented two-word sentences (i.e. pronoun and pseudoverb such as ‘I grush’, ‘she grushes’, for which syntactic binding can take place) and wordlists (i.e. two pseudoverbs such as ‘pob grush’, ‘pob grushes’, for which no binding occurs). Comparing these two conditions, we targeted syntactic binding while minimizing contributions of semantic binding and of other cognitive processes such as working memory. We found a converging pattern of results using two distinct analysis approaches: one approach using frequency bands as defined in previous literature, and one data-driven approach in which we looked at the entire range of frequencies between 3-30 Hz without the constraints of pre-defined frequency bands. In the syntactic binding (relative to the wordlist) condition, a power increase was observed in the alpha and beta frequency range shortly preceding the presentation of the target word that requires binding, which was maximal over frontal-central electrodes. Our interpretation is that these signatures reflect that language comprehenders expect the need for binding to occur. Following the presentation of the target word in a syntactic binding context (relative to the wordlist condition), an increase in alpha power maximal over a left lateralized cluster of frontal-temporal electrodes was observed. We suggest that this alpha increase relates to syntactic binding taking place. Taken together, our findings suggest that increases in alpha and beta power are reflections of distinct the neural processes underlying syntactic binding.

Abstract

When we comprehend language, we often do this in rich settings in which we can use many cues to understand what someone is saying. However, it has traditionally been difficult to design experiments with rich three-dimensional contexts that resemble our everyday environments, while maintaining control over the linguistic and non-linguistic information that is available. Here we test the validity of combining electroencephalography (EEG) and Virtual Reality (VR) to overcome this problem. We recorded electrophysiological brain activity during language processing in a well-controlled three-dimensional virtual audiovisual environment. Participants were immersed in a virtual restaurant, while wearing EEG equipment. In the restaurant participants encountered virtual restaurant guests. Each guest was seated at a separate table with an object on it (e.g. a plate with salmon). The restaurant guest would then produce a sentence (e.g. “I just ordered this salmon.”). The noun in the spoken sentence could either match (“salmon”) or mismatch (“pasta”) with the object on the table, creating a situation in which the auditory information was either appropriate or inappropriate in the visual context. We observed a reliable N400 effect as a consequence of the mismatch. This finding validates the combined use of VR and EEG as a tool to study the neurophysiological mechanisms of everyday language comprehension in rich, ecologically valid settings.

Abstract

Learning often occurs in communicative and collaborative settings, yet almost all research into the neural basis of memory relies on participants encoding and retrieving information on their own. We investigated whether learning linguistic labels in a collaborative context at least partly relies on cognitively and neurally distinct representations, as compared to learning in an individual context. Healthy human participants learned labels for sets of abstract shapes in three different tasks. They came up with labels with another person in a collaborative communication task (collaborative condition), by themselves (individual condition), or were given pre-determined unrelated labels to learn by themselves (arbitrary condition). Immediately after learning, participants retrieved and produced the labels aloud during a communicative task in the MRI scanner. The fMRI results show that the retrieval of collaboratively generated labels as compared to individually learned labels engages brain regions involved in understanding others (mentalizing or theory of mind) and autobiographical memory, including the medial prefrontal cortex, the right temporoparietal junction and the precuneus. This study is the first to show that collaboration during encoding affects the neural networks involved in retrieval.

Abstract

Readers and listeners actively predict upcoming words during language processing. These predictions might serve to support the unification of incoming words into sentence context and thus rely on interactions between areas in the language network. In the current magnetoencephalography study, participants read sentences that varied in contextual constraints so that the predictability of the sentence-final words was either high or low. Before the sentence-final words, we observed stronger alpha power suppression for the highly compared with low constraining sentences in the left inferior frontal cortex, left posterior temporal region, and visual word form area. Importantly, the temporal and visual word form area alpha power correlated negatively with left frontal gamma power for the highly constraining sentences. We suggest that the correlation between alpha power decrease in temporal language areas and left prefrontal gamma power reflects the initiation of an anticipatory unification process in the language network.

Abstract

Using magnetoencephalography, the current study examined gamma activity associated with language prediction. Participants read high- and low-constraining sentences in which the final word of the sentence was either expected or unexpected. Although no consistent gamma power difference induced by the sentence-final words was found between the expected and unexpected conditions, the correlation of gamma power during the prediction and activation intervals of the sentence-final words was larger when the presented words matched with the prediction compared with when the prediction was violated or when no prediction was available. This suggests that gamma magnitude relates to the match between predicted and perceived words. Moreover, the expected words induced activity with a slower gamma frequency compared with that induced by unexpected words. Overall, the current study establishes that prediction is related to gamma power correlations and a slowing of the gamma frequency.