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

We hypothesized that areas in the temporal lobe that have been implicated in the phonological processing of spoken words would also be activated during the generation and phonological processing of imagined speech. We tested this hypothesis using functional magnetic resonance imaging during a behaviorally controlled task of metrical stress evaluation. Subjects were presented with bisyllabic words and had to determine the alternation of strong and weak syllables. Thus, they were required to discriminate between weak-initial words and strong-initial words. In one condition, the stimuli were presented auditorily to the subjects (by headphones). In the other condition the stimuli were presented visually on a screen and subjects were asked to imagine hearing the word. Results showed activation of the supplementary motor area, inferior frontal gyrus (Broca's area) and insula in both conditions. In the superior temporal gyrus (STG) and in the superior temporal sulcus (STS) strong activation was observed during the auditory (perceptual) condition. However, a region located in the posterior part of the STS/STG also responded during the imagery condition. No activation of this same region of the STS was observed during a control condition which also involved processing of visually presented words, but which required a semantic decision from the subject. We suggest that processing of metrical stress, with or without auditory input, relies in part on cortical interface systems located in the posterior part of STS/STG. These results corroborate behavioral evidence regarding phonological loop involvement in auditory–verbal imagery.

Abstract

Oscillatory neuronal dynamics, observed in the human electroencephalogram (EEG) during language processing, have been related to the dynamic formation of functionally coherent networks that serve the role of integrating the different sources of information needed for understanding the linguistic input. To further explore the functional role of oscillatory synchrony during language processing, we quantified event-related EEG power changes induced by the presentation of open-class (OC) words and closed-class (CC) words in a wide range of frequencies (from 1 to 30 Hz), while subjects read a short story. Word presentation induced three oscillatory components: a theta power increase (4–7 Hz), an alpha power decrease (10–12 Hz), and a beta power decrease (16–21 Hz). Whereas the alpha and beta responses showed mainly quantitative differences between the two word classes, the theta responses showed qualitative differences between OC words and CC words: A theta power increase was found over left temporal areas for OC words, but not for CC words. The left temporal theta increase may index the activation of a network involved in retrieving the lexical–semantic properties of the OC items.

Abstract

In speaking and comprehending language, word information is retrieved from memory and combined into larger units (unification). Unification operations take place in parallel at the semantic, syntactic and phonological levels of processing. This article proposes a new framework that connects psycholinguistic models to a neurobiological account of language. According to this proposal the left inferior frontal gyrus (LIFG) plays an important role in unification. Research in other domains of cognition indicates that left prefrontal cortex has the necessary neurobiological characteristics for its involvement in the unification for language. I offer here a psycholinguistic perspective on the nature of language unification and the role of LIFG.

Abstract

Children begin to talk at about age one. The vocabulary they need to do so must be built on perceptual evidence and, indeed, infants begin to recognize spoken words long before they talk. Most of the utterances infants hear, however, are continuous, without pauses between words, so constructing a vocabulary requires them to decompose continuous speech in order to extract the individual words. Here, we present electrophysiological evidence that 10-month-old infants recognize two-syllable words they have previously heard only in isolation when these words are presented anew in continuous speech. Moreover, they only need roughly the first syllable of the word to begin doing this. Thus, prelinguistic infants command a highly efficient procedure for segmentation and recognition of spoken words in the absence of an existing vocabulary, allowing them to tackle effectively the problem of bootstrapping a lexicon out of the highly variable, continuous speech signals in their environment.

Abstract

The chronic fatigue syndrome (CFS) is a disabling disorder of unknown etiology. The symptomatology of CFS (central fatigue, impaired concentration, attention and memory) suggests that this disorder could be related to alterations at the level of the central nervous system. In this study, we have used an automated and unbiased morphometric technique to test whether CFS patients display structural cerebral abnormalities. We mapped structural cerebral morphology and volume in two cohorts of CFS patients (in total 28 patients) and healthy controls (in total 28 controls) from high-resolution structural magnetic resonance images, using voxel-based morphometry. Additionally, we recorded physical activity levels to explore the relation between severity of CFS symptoms and cerebral abnormalities. We observed significant reductions in global gray matter volume in both cohorts of CFS patients, as compared to matched control participants. Moreover, the decline in gray matter volume was linked to the reduction in physical activity, a core aspect of CFS. These findings suggest that the central nervous system plays a key role in the pathophysiology of CFS and point to a new objective and quantitative tool for clinical diagnosis of this disabling disorder.

Abstract

We have used implicit motor imagery to investigate the neural correlates of motor planning independently from actual movements. Subjects were presented with drawings of left or right hands and asked to judge the hand laterality, regardless of the stimulus rotation from its upright orientation. We paired this task with a visual imagery control task, in which subjects were presented with typographical characters and asked to report whether they saw a canonical letter or its mirror image, regardless of its rotation. We measured neurovascular activity with fast event-related fMRI, distinguishing responses parametrically related to motor imagery from responses evoked by visual imagery and other task-related phenomena. By quantifying behavioral and neurovascular correlates of imagery on a trial-by-trial basis, we could discriminate between stimulusrelated, mental rotation-related, and response-related neural activity. We found that specific portions of the posterior parietal and precentral cortex increased their activity as a function of mental rotation only during the motor imagery task. Within these regions, the parietal cortex was visually responsive, whereas the dorsal precentral cortex was not. Response- but not rotation-related activity was found around the left central sulcus (putative primary motor cortex) during both imagery tasks. Our study provides novel evidence on the topography and content of movement representations in the human brain. During intended action, the posterior parietal cortex combines somatosensory and visuomotor information, whereas the dorsal premotor cortex generates the actual motor plan, and the primary motor cortex deals with movement execution. We discuss the relevance of these results in the context of current models of action planning.

Abstract

The authors examined whether people can use their knowledge of the wider discourse rapidly enough to anticipate specific upcoming words as a sentence is unfolding. In an event-related brain potential (ERP) experiment, subjects heard Dutch stories that supported the prediction of a specific noun. To probe whether this noun was anticipated at a preceding indefinite article, stories were continued with a gender-marked adjective whose suffix mismatched the upcoming noun's syntactic gender. Prediction-inconsistent adjectives elicited a differential ERP effect, which disappeared in a no-discourse control experiment. Furthermore, in self-paced reading, prediction-inconsistent adjectives slowed readers down before the noun. These findings suggest that people can indeed predict upcoming words in fluent discourse and, moreover, that these predicted words can immediately begin to participate in incremental parsing operations.

Abstract

An event-related brain potential experiment was carried out to investigate on-line syntactic processing in patients with Broca’s aphasia. Subjects were visually presented with sentences that were either syntactically correct or contained violations of word-category. Three groups of subjects were tested: Broca patients (N=11), non-aphasic patients with a right hemisphere (RH) lesion (N=9), and healthy aged-matched controls (N=15). Both control groups appeared sensitive to the violations of word-category as shown by clear P600/SPS effects. The Broca patients displayed only a very reduced and delayed P600/SPS effect. The results are discussed in the context of a lexicalist parsing model. It is concluded that Broca patients are hindered to detect on-line violations of word-category, if word class information is incomplete or delayed available.