Publications

Abstract

Recent artificial neural networks that process natural language achieve unprecedented performance in tasks requiring sentence-level understanding. As such, they could be interesting models of the integration of linguistic information in the human brain. We review works that compare these artificial language models with human brain activity and we assess the extent to which this approach has improved our understanding of the neural processes involved in natural language comprehension. Two main results emerge. First, the neural representation of word meaning aligns with the context-dependent, dense word vectors used by the artificial neural networks. Second, the processing hierarchy that emerges within artificial neural networks broadly matches the brain, but is surprisingly inconsistent across studies. We discuss current challenges in establishing artificial neural networks as process models of natural language comprehension. We suggest exploiting the highly structured representational geometry of artificial neural networks when mapping representations to brain data.

Abstract

There is a robust positive relationship between reading skills and the time to name aloud an array of letters, digits, objects, or colors as quickly as possible. A convincing and complete explanation for the direction and locus of this association remains, however, elusive. In this study we investigated rapid automatized naming (RAN) of every-day objects and basic color patches in neurotypical illiterate and literate adults. Literacy acquisition and education enhanced RAN performance for both conceptual categories but this advantage was much larger for (abstract) colors than every-day objects. This result suggests that (i) literacy/education may be causal for serial rapid naming ability of non-alphanumeric items, (ii) differences in the lexical quality of conceptual representations can underlie the reading-related differential RAN performance.

Abstract

Gliomas are brain tumors infiltrating healthy cortical and subcortical areas that may host cognitive functions, such as language. If these areas are damaged during surgery, the patient might develop word retrieval or articulation problems. For this reason, many glioma patients are operated on awake, while their language functions are tested. For this practice, quite simple tests are used, for example, picture naming. This paper describes the process and timeline of picture naming (noun retrieval) and shows the timeline and localization of the distinguished stages. This is relevant information for presurgical language testing with navigated Magnetic Stimulation (nTMS). This novel technique allows us to identify cortical involved in the language production process and, thus, guides the neurosurgeon in how to approach and remove the tumor. We argue that not only nouns, but also verbs should be tested, since sentences are built around verbs, and sentences are what we use in daily life. This approach’s relevance is illustrated by two case studies of glioma patients.

Abstract

While formal variation in Latin’s numerals is generally acknowledged, little is known about (relative) incidence, distribution, context, or linguistic productivity. Addressing this lacuna, this article examines “decads+” in Latin, which convey the numbers between the full decads: the teens (‘eleven’ through ‘nineteen’) as well as the numerals between the higher decads starting at ‘twenty-one’ through ‘ninety-nine’. Latin’s decads+ are compounds and prone to variation. The data, which are drawn from a variety of sources, reveal (a) substantial formal variation in Latin, both internally and typologically; (b) co-existence of several types of formation; (c) productivity of potential borrowings; (d) resilience of early formations; (e) patterns in structure and incidence that anticipate the Romance numerals; and (f) historical trends. From a typological and general linguistic perspective as well, Latin’s decads+ are most relevant because their formal variation involves sequence, connector, and arithmetical operations and because their historical depth shows a gradual shift away from widespread formal variation, eventually resulting in the relatively rigid system found in Romance. Moreover, the combined system attested in decads+ in Latin – based on a combination of inherited, innovative and borrowed patterns and reflecting different stages of development – presents a number of typological inconsistencies that require further assessment

Abstract

In face-to-face communication, humans are faced with multiple layers of discontinuous multimodal signals, such as head, face, hand gestures, speech and non-speech sounds, which need to be interpreted as coherent and unified communicative actions. This implies a fundamental computational challenge: optimally binding only signals belonging to the same communicative action while segregating signals that are not connected by the communicative content. How do we achieve such an extraordinary feat, reliably, and efficiently? To address this question, we need to further move the study of human communication beyond speech-centred perspectives and promote a multimodal approach combined with interdisciplinary cooperation. Accordingly, we seek to reconcile two explanatory frameworks recently proposed in psycholinguistics and sensory neuroscience into a neurocognitive model of multimodal face-to-face communication. First, we introduce a psycholinguistic framework that characterises face-to-face communication at three parallel processing levels: multiplex signals, multimodal gestalts and multilevel predictions. Second, we consider the recent proposal of a lateral neural visual pathway specifically dedicated to the dynamic aspects of social perception and reconceive it from a multimodal perspective (“lateral processing pathway”). Third, we reconcile the two frameworks into a neurocognitive model that proposes how multiplex signals, multimodal gestalts, and multilevel predictions may be implemented along the lateral processing pathway. Finally, we advocate a multimodal and multidisciplinary research approach, combining state-of-the-art imaging techniques, computational modelling and artificial intelligence for future empirical testing of our model.

Abstract

Introduction
Despite abundant research on the role of Broca's area in language processing, there is still no consensus on language specificity of this region and its connectivity network.

Methods
The present study employed the meta-analytic connectivity modeling procedure to identify and compare domain-specific (language-specific) and domain-general (shared between language and other domains) functional connectivity patterns of three subdivisions within the broadly defined Broca's area: pars opercularis (IFGop), pars triangularis (IFGtri), and pars orbitalis (IFGorb) of the left inferior frontal gyrus.

Results
The findings revealed a left-lateralized frontotemporal network for all regions of interest underlying domain-specific linguistic functions. The domain-general network, however, spanned frontoparietal regions that overlap with the multiple-demand network and subcortical regions spanning the thalamus and the basal ganglia.

Conclusions
The findings suggest that language specificity of Broca's area emerges within a left-lateralized frontotemporal network, and that domain-general resources are garnered from frontoparietal and subcortical networks when required by task demands.

Abstract

Speaking requires the temporally coordinated planning of core linguistic information, from conceptual meaning to articulation. Recent neurophysiological results suggested that these operations involve a cascade of neural events with subsequent onset times, whilst competing evidence suggests early parallel neural activation. To test these hypotheses, we examined the sources of neuromagnetic activity recorded from 34 participants overtly naming 134 images from 4 object categories (animals, tools, foods and clothes). Within each category, word length and phonological neighbourhood density were co-varied to target phonological/phonetic processes. Multivariate pattern analyses (MVPA) searchlights in source space decoded object categories in occipitotemporal and middle temporal cortex, and phonological/phonetic variables in left inferior frontal (BA 44) and motor cortex early on. The findings suggest early activation of multiple variables due to intercorrelated properties and interactivity of processing, thus raising important questions about the representational properties of target words during the preparatory time enabling overt speaking.

Abstract

Previous electroencephalography studies have yielded evidence for automatic processing of syntax and lexical stress. However, these studies looked at both effects in isolation, limiting their generalizability to everyday language comprehension. In the current study, we investigated automatic processing of grammatical agreement in the face of variation in lexical stress. Using an oddball paradigm, we measured the Mismatch Negativity (MMN) in Dutch-speaking participants while they listened to Dutch subject–verb sequences (linguistic context) or acoustically similar sequences in which the subject was replaced by filtered noise (nonlinguistic context). The verb forms differed in the inflectional suffix, rendering the subject–verb sequences grammatically correct or incorrect, and leading to a difference in the stress pattern of the verb forms. We found that the MMNs were modulated in both the linguistic and nonlinguistic condition, suggesting that the processing load induced by variation in lexical stress can hinder early automatic processing of grammatical agreement. However, as the morphological differences between the verb forms correlated with differences in number of syllables, an interpretation in terms of the prosodic structure of the sequences cannot be ruled out. Future research is needed to determine which of these factors (i.e., lexical stress, syllabic structure) most strongly modulate early syntactic processing.

Abstract

Since the cognitive revolution, language and action have been compared as cognitive systems, with cross-domain convergent views recently gaining renewed interest in biology, neuroscience, and cognitive science. Language and action are both combinatorial systems whose mode of combination has been argued to be hierarchical, combining elements into constituents of increasingly larger size. This structural similarity has led to the suggestion that they rely on shared cognitive and neural resources. In this article, we compare the conceptual and formal properties of hierarchy in language and action using set theory. We show that the strong compositionality of language requires a particular formalism, a magma, to describe the algebraic structure corresponding to the set of hierarchical structures underlying sentences. When this formalism is applied to actions, it appears to be both too strong and too weak. To overcome these limitations, which are related to the weak compositionality and sequential nature of action structures, we formalize the algebraic structure corresponding to the set of actions as a trace monoid. We aim to capture the different system properties of language and action in terms of the distinction between hierarchical sets and hierarchical sequences and discuss the implications for the way both systems could be represented in the brain.

Abstract

The extent to which languages share properties reflecting the non-linguistic constraints of the speakers who speak them is key to the debate regarding the relationship between language and cognition. A critical case is spatial communication, where it has been argued that semantic universals should exist, if anywhere. Here, using an experimental paradigm able to separate variation within a language from variation between languages, we tested the use of spatial demonstratives—the most fundamental and frequent spatial terms across languages. In n = 874 speakers across 29 languages, we show that speakers of all tested languages use spatial demonstratives as a function of being able to reach or act on an object being referred to. In some languages, the position of the addressee is also relevant in selecting between demonstrative forms. Commonalities and differences across languages in spatial communication can be understood in terms of universal constraints on action shaping spatial language and cognition.

Abstract

This paper investigates the fractional order behavior of ZnO ceramics at different frequencies. ZnO ceramic was prepared by high energy ball milling technique (HEBM) sintered at 1300℃ to study the frequency response properties. The frequency response properties (impedance and phase
angles) were examined by analyzing through impedance analyzer (100 Hz - 1 MHz). Constant phase angles (84°-88°) were obtained at low temperature ranges (25 ℃-125 ℃). The structural and
morphological composition of the ZnO ceramic was investigated using X-ray diffraction techniques and FESEM. Raman spectrum was studied to understand the different modes of ZnO ceramics. Machine learning (polynomial regression) models were trained on a dataset of 1280
experimental values to accurately predict the relationship between frequency and temperature with respect to impedance and phase values of the ZnO ceramic FOC. The predicted impedance values were found to be in good agreement (R2 ~ 0.98, MSE ~ 0.0711) with the experimental results.
Impedance values were also predicted beyond the experimental frequency range (at 50 Hz and 2 MHz) for different temperatures (25℃ - 500℃) and for low temperatures (10°, 15° and 20℃)
within the frequency range (100Hz - 1MHz).

Abstract

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call ‘neuroconnectionism’. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.

Abstract

During face-to-face communication, recipients need to rapidly integrate a plethora of auditory and visual signals. This integration of signals from many different bodily articulators, all offset in time, with the information in the speech stream may either tax the cognitive system, thus slowing down language processing, or may result in multimodal facilitation. Using the classical shadowing paradigm, participants shadowed speech from face-to-face, naturalistic dyadic conversations in an audiovisual context, an audiovisual context without visual speech (e.g., lips), and an audio-only context. Our results provide evidence of a multimodal facilitation effect in human communication: participants were faster in shadowing words when seeing multimodal messages compared with when hearing only audio. Also, the more visual context was present, the fewer shadowing errors were made, and the earlier in time participants shadowed predicted lexical items. We propose that the multimodal facilitation effect may contribute to the ease of fast face-to-face conversational interaction.

Abstract

How do neural oscillations support human audiovisual language and communication? Considering the rhythmic nature of audiovisual language, in which stimuli from different sensory modalities unfold over time, neural oscillations represent an ideal candidate to investigate how audiovisual language is processed in the brain. Modulations of oscillatory phase and power are thought to support audiovisual language and communication in multiple ways. Neural oscillations synchronize by tracking external rhythmic stimuli or by re-setting their phase to presentation of relevant stimuli, resulting in perceptual benefits. In particular, synchronized neural oscillations have been shown to subserve the processing and the integration of auditory speech, visual speech, and hand gestures. Furthermore, synchronized oscillatory modulations have been studied and reported between brains during social interaction, suggesting that their contribution to audiovisual communication goes beyond the processing of single stimuli and applies to natural, face-to-face communication.

There are still some outstanding questions that need to be answered to reach a better understanding of the neural processes supporting audiovisual language and communication. In particular, it is not entirely clear yet how the multitude of signals encountered during audiovisual communication are combined into a coherent percept and how this is affected during real-world dyadic interactions. In order to address these outstanding questions, it is fundamental to consider language as a multimodal phenomenon, involving the processing of multiple stimuli unfolding at different rhythms over time, and to study language in its natural context: social interaction. Other outstanding questions could be addressed by implementing novel techniques (such as rapid invisible frequency tagging, dual-electroencephalography, or multi-brain stimulation) and analysis methods (e.g., using temporal response functions) to better understand the relationship between oscillatory dynamics and efficient audiovisual communication.

Abstract

This article explores the role of text and reader characteristics in character engagement experiences. In an online study, participants completed several self-report and behavioral measures of social-cognitive abilities and read two literary narratives in which the presence of linguistic viewpoint markers was varied using a highly controlled manipulation strategy. Afterward, participants reported on their character engagement experiences. A principal component analysis on participants’ responses revealed the multidimensional nature of character engagement, which included both self- and other-oriented emotional responses (e.g., empathy, personal distress) as well as more cognitive responses (e.g., identification, perspective taking). Furthermore, character engagement was found to rely on a wide range of social-cognitive abilities but not on the presence of viewpoint markers. Finally, and most importantly, we did not find convincing evidence for an interplay between social-cognitive abilities and the presence of viewpoint markers. These findings suggest that readers rely on their social-cognitive abilities to engage with the inner worlds of fictional others, more so than on the lexical cues of those inner worlds provided by the text.

Abstract

Acquiring a second language (L2) requires newly learned information to be integrated with existing knowledge. It has been proposed that several memory systems work together to enable this process of rapidly encoding new information and then slowly incorporating it with existing knowledge, such that it is consolidated and integrated into the language network without catastrophic interference. This chapter focuses on consolidation of L2 vocabulary. First, the complementary learning systems model is outlined, along with the model’s predictions regarding lexical consolidation. Next, word learning studies in first language (L1) that investigate the factors playing a role in consolidation, and the neural mechanisms underlying this, are reviewed. Using the L1 memory consolidation literature as background, the chapter then presents what is currently known about memory consolidation in L2 word learning. Finally, considering what is already known about L1 but not about L2, future research investigating memory consolidation in L2 neurocognition is proposed.

Abstract

According to the language marker hypothesis language has provided homo sapiens with a rich symbolic system that plays a central role in interpreting signals delivered by our sensory apparatus, in shaping action goals, and in creating a powerful tool for reasoning and inferencing. This view provides an important correction on embodied accounts of language that reduce language to action, perception, emotion and mental simulation. The presence of a language system has, however, also important consequences for perception, action, emotion, and memory. Language stamps signals from perception, action, and emotional systems with rich cognitive markers that transform the role of these signals in the overall cognitive architecture of the human mind. This view does not deny that language is implemented by means of universal principles of neural organization. However, language creates the possibility to generate rich internal models of the world that are shaped and made accessible by the characteristics of a language system. This makes us less dependent on direct action-perception couplings and might even sometimes go at the expense of the veridicality of perception. In cognitive (neuro)science the pendulum has swung from language as the key to understand the organization of the human mind to the perspective that it is a byproduct of perception and action. It is time that it partly swings back again.

Abstract

Neural oscillations are thought to support speech and language processing. They may not only inherit acoustic rhythms, but might also impose endogenous rhythms onto processing. In support of this, we here report that human (both male and female) eye movements during naturalistic reading exhibit rhythmic patterns that show frequency-selective coherence with the EEG, in the absence of any stimulation rhythm. Periodicity was observed in two distinct frequency bands: First, word-locked saccades at 4-5 Hz display coherence with whole-head theta-band activity. Second, fixation durations fluctuate rhythmically at ∼1 Hz, in coherence with occipital delta-band activity. This latter effect was additionally phase-locked to sentence endings, suggesting a relationship with the formation of multi-word chunks. Together, eye movements during reading contain rhythmic patterns that occur in synchrony with oscillatory brain activity. This suggests that linguistic processing imposes preferred processing time scales onto reading, largely independent of actual physical rhythms in the stimulus.

Abstract

In an online experiment among native speakers of Dutch we measured addressees' responses to emails written in the informal pronoun T or the formal pronoun V in HR communication. 172 participants (61 male, mean age 37 years) read either the V-versions or the T-versions of two invitation emails and two rejection emails by four different fictitious recruiters. After each email, participants had to score their appreciation of the company and the recruiter on five different scales each, such as The recruiter who wrote this email seems … [scale from friendly to unfriendly]. We hypothesized that (i) the V-pronoun would be more appreciated in letters of rejection, and the T-pronoun in letters of invitation, and (ii) older people would appreciate the V-pronoun more than the T-pronoun, and the other way around for younger people. Although neither of these hypotheses was supported, we did find a small effect of pronoun: Emails written in V were more highly appreciated than emails in T, irrespective of type of email (invitation or rejection), and irrespective of the participant's age, gender, and level of education. At the same time, we observed differences in the strength of this effect across different scales.

Abstract

EEG and eye-tracking provide complementary information when investigating language comprehension. Evidence that speech processing may be facilitated by speech prediction comes from the observation that a listener's eye gaze moves towards a referent before it is mentioned if the remainder of the spoken sentence is predictable. However, changes to the trajectory of anticipatory fixations could result from a change in prediction or an attention shift. Conversely, N400 amplitudes and concurrent spectral power provide information about the ease of word processing the moment the word is perceived. In a proof-of-principle investigation, we combined EEG and eye-tracking to study linguistic prediction in naturalistic, virtual environments. We observed increased processing, reflected in theta band power, either during verb processing - when the verb was predictive of the noun - or during noun processing - when the verb was not predictive of the noun. Alpha power was higher in response to the predictive verb and unpredictable nouns. We replicated typical effects of noun congruence but not predictability on the N400 in response to the noun. Thus, the rich visual context that accompanied speech in virtual reality influenced language processing compared to previous reports, where the visual context may have facilitated processing of unpredictable nouns. Finally, anticipatory fixations were predictive of spectral power during noun processing and the length of time fixating the target could be predicted by spectral power at verb onset, conditional on the object having been fixated. Overall, we show that combining EEG and eye-tracking provides a promising new method to answer novel research questions about the prediction of upcoming linguistic input, for example, regarding the role of extralinguistic cues in prediction during language comprehension.

Abstract

n conversations, interlocutors concurrently perform two related processes: speech comprehension and speech planning. We investigated effects of speech planning on comprehension using EEG. Dutch speakers listened to sentences that ended with expected or unexpected target words. In addition, a picture was presented two seconds after target onset (Experiment 1) or 50 ms before target onset (Experiment 2). Participants’ task was to name the picture or to stay quiet depending on the picture category. In Experiment 1, we found a strong N400 effect in response to unexpected compared to expected target words. Importantly, this N400 effect was reduced in Experiment 2 compared to Experiment 1. Unexpectedly, the N400 effect was not smaller in the naming compared to categorization condition. This indicates that conceptual preparation or the decision whether to speak (taking place in both task conditions of Experiment 2) rather than processes specific to word planning interfere with comprehension.

Abstract

The growing importance of research on bilingualism in psychology and neuroscience motivates the need for a psychometric model that can be used to understand and quantify this phenomenon. This research is the first to meet this need. We reanalyzed two data sets (N = 171 and N = 112) from relatively young adult language-unbalanced bilinguals and asked whether bilingualism is best described by the factor structure or by the network structure. The factor and network models were established on one data set and then validated on the other data set in a fully confirmatory manner. The network model provided the best fit to the data. This implies that bilingualism should be conceptualized as an emergent phenomenon arising from direct and idiosyncratic dependencies among the history of language acquisition, diverse language skills, and language-use practices. These dependencies can be reduced to neither a single universal quotient nor to some more general factors. Additional in-depth network analyses showed that the subjective perception of proficiency along with language entropy and language mixing were the most central indices of bilingualism, thus indicating that these measures can be especially sensitive to variation in the overall bilingual experience. Overall, this work highlights the great potential of psychometric network modeling to gain a more accurate description and understanding of complex (psycho)linguistic and cognitive phenomena.

Abstract

During listening, brain activity tracks the rhythmic structures of speech signals. Here, we directly dissociated the contribution of neural envelope tracking in the processing of speech acoustic cues from that related to linguistic processing. We examined the neural changes associated with the comprehension of Noise-Vocoded (NV) speech using magnetoencephalography (MEG). Participants listened to NV sentences in a 3-phase training paradigm: (1) pre-training, where NV stimuli were barely comprehended, (2) training with exposure of the original clear version of speech stimulus, and (3) post-training, where the same stimuli gained intelligibility from the training phase. Using this paradigm, we tested if the neural responses of a speech signal was modulated by its intelligibility without any change in its acoustic structure. To test the influence of spectral degradation on neural envelope tracking independently of training, participants listened to two types of NV sentences (4-band and 2-band NV speech), but were only trained to understand 4-band NV speech. Significant changes in neural tracking were observed in the delta range in relation to the acoustic degradation of speech. However, we failed to find a direct effect of intelligibility on the neural tracking of speech envelope in both theta and delta ranges, in both auditory regions-of-interest and whole-brain sensor-space analyses. This suggests that acoustics greatly influence the neural tracking response to speech envelope, and that caution needs to be taken when choosing the control signals for speech-brain tracking analyses, considering that a slight change in acoustic parameters can have strong effects on the neural tracking response.

Abstract

Emotional words have consistently been shown to be processed differently than neutral words. However, few studies have examined individual variability in emotion word processing with longer, ecologically valid stimuli (beyond isolated words, sentences, or paragraphs). In the current study, we re-analysed eye-tracking data collected during story reading to reveal how individual differences in need for affect and narrative absorption impact the speed of emotion word reading. Word emotionality was indexed by affective-aesthetic potentials (AAP) calculated by a sentiment analysis tool. We found that individuals with higher levels of need for affect and narrative absorption read positive words more slowly. On the other hand, these individual differences did not influence the reading time of more negative words, suggesting that high need for affect and narrative absorption are characterised by a positivity bias only. In general, unlike most previous studies using more isolated emotion word stimuli, we observed a quadratic (U-shaped) effect of word emotionality on reading speed, such that both positive and negative words were processed more slowly than neutral words. Taken together, this study emphasises the importance of taking into account individual differences and task context when studying emotion word processing.

Abstract

All living beings try to save effort, and humans are no exception. This groundbreaking book shows how we save time and energy during communication by unconsciously making efficient choices in grammar, lexicon and phonology. It presents a new theory of 'communicative efficiency', the idea that language is designed to be as efficient as possible, as a system of communication. The new framework accounts for the diverse manifestations of communicative efficiency across a typologically broad range of languages, using various corpus-based and statistical approaches to explain speakers' bias towards efficiency. The author's unique interdisciplinary expertise allows her to provide rich evidence from a broad range of language sciences. She integrates diverse insights from over a hundred years of research into this comprehensible new theory, which she presents step-by-step in clear and accessible language. It is essential reading for language scientists, cognitive scientists and anyone interested in language use and communication.

Abstract

This article argues for a gradient approach to word order, which treats word order preferences, both within and across languages, as a continuous variable. Word order variability should be regarded as a basic assumption, rather than as something exceptional. Although this approach follows naturally from the emergentist usage-based view of language, we argue that it can be beneficial for all frameworks and linguistic domains, including language acquisition, processing, typology, language contact, language evolution and change, and formal approaches. Gradient approaches have been very fruitful in some domains, such as language processing, but their potential is not fully realized yet. This may be due to practical reasons. We discuss the most pressing methodological challenges in corpus-based and experimental research of word order and propose some practical solutions.

Abstract

There remains some debate about whether beta power effects observed during sentence comprehension reflect ongoing syntactic unification operations (beta-syntax hypothesis), or instead reflect maintenance or updating of the sentence-level representation (beta-maintenance hypothesis). In this study, we used magnetoencephalography to investigate beta power neural dynamics while participants read relative clause sentences that were initially ambiguous between a subject- or an object-relative reading. An additional condition included a grammatical violation at the disambiguation point in the relative clause sentences. The beta-maintenance hypothesis predicts a decrease in beta power at the disambiguation point for unexpected (and less preferred) object-relative clause sentences and grammatical violations, as both signal a need to update the sentence-level representation. While the beta-syntax hypothesis also predicts a beta power decrease for grammatical violations due to a disruption of syntactic unification operations, it instead predicts an increase in beta power for the object-relative clause condition because syntactic unification at the point of disambiguation becomes more demanding. We observed decreased beta power for both the agreement violation and object-relative clause conditions in typical left hemisphere language regions, which provides compelling support for the beta-maintenance hypothesis. Mid-frontal theta power effects were also present for grammatical violations and object-relative clause sentences, suggesting that violations and unexpected sentence interpretations are registered as conflicts by the brain's domain-general error detection system.

Abstract

Mental simulation is an important aspect of narrative reading. In a previous study, we found that gaze durations are differentially impacted by different kinds of mental simulation. Motor simulation, perceptual simulation, and mentalizing as elicited by literary short stories influenced eye movements in distinguishable ways (Mak & Willems, 2019). In the current study, we investigated the existence of a common neural locus for these different kinds of simulation. We additionally investigated whether individual differences during reading, as indexed by the eye movements, are reflected in domain-specific activations in the brain. We found a variety of brain areas activated by simulation-eliciting content, both modality-specific brain areas and a general simulation area. Individual variation in percent signal change in activated areas was related to measures of story appreciation as well as personal characteristics (i.e., transportability, perspective taking). Taken together, these findings suggest that mental simulation is supported by both domain-specific processes grounded in previous experiences, and by the neural mechanisms that underlie higher-order language processing (e.g., situation model building, event indexing, integration).

Abstract

We present a protocol to study naturalistic human communication using dual-EEG and audio-visual recordings. We describe preparatory steps for data collection including setup preparation, experiment design, and piloting. We then describe the data collection process in detail which consists of participant recruitment, experiment room preparation, and data collection. We also outline the kinds of research questions that can be addressed with the current protocol, including several analysis possibilities, from conversational to advanced time-frequency analyses.
For complete details on the use and execution of this protocol, please refer to Drijvers and Holler (2022).

Abstract

Affective behaviors enable social robots to not only establish better connections with humans but also serve as a tool for the robots to express their internal states. It has been well established that emotions are important to signal understanding in Human-Robot Interaction (HRI). This work aims to harness the power of Large Language Models (LLM) and proposes an approach to control the affective behavior of robots. By interpreting emotion appraisal as an Emotion Recognition in Conversation (ERC) tasks, we used GPT-3.5 to predict the emotion of a robot’s turn in real-time, using the dialogue history of the ongoing conversation. The robot signaled the predicted emotion using facial expressions. The model was evaluated in a within-subjects user study (N = 47) where the model-driven emotion generation was compared against conditions where the robot did not display any emotions and where it displayed incongruent emotions. The participants interacted with the robot by playing a card sorting game that was specifically designed to evoke emotions. The results indicated that the emotions were reliably generated by the LLM and the participants were able to perceive the robot’s emotions. It was found that the robot expressing congruent model-driven facial emotion expressions were perceived to be significantly more human-like, emotionally appropriate, and elicit a more positive impression. Participants also scored significantly better in the card sorting game when the robot displayed congruent facial expressions. From a technical perspective, the study shows that LLMs can be used to control the affective behavior of robots reliably in real-time. Additionally, our results could be used in devising novel human-robot interactions, making robots more effective in roles where emotional interaction is important, such as therapy, companionship, or customer service.

Abstract

Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger cortical circuits.

Abstract

Prediction is often regarded as an integral aspect of incremental language comprehension, but little is known about the cognitive architectures and mechanisms that support it. We review studies showing that listeners and readers use all manner of contextual information to generate multifaceted predictions about upcoming input. The nature of these predictions may vary between individuals owing to differences in language experience, among other factors. We then turn to unresolved questions which may guide the search for the underlying mechanisms. (i) Is prediction essential to language processing or an optional strategy? (ii) Are predictions generated from within the language system or by domain-general processes? (iii) What is the relationship between prediction and memory? (iv) Does prediction in comprehension require simulation via the production system? We discuss promising directions for making progress in answering these questions and for developing a mechanistic understanding of prediction in language.

Abstract

Frequency tagging has been successfully used to investigate selective stimulus processing in electroencephalography (EEG) or magnetoencephalography (MEG) studies. Recently, new projectors have been developed that allow for frequency tagging at higher frequencies (>60 Hz). This technique, rapid invisible frequency tagging (RIFT), provides two crucial advantages over low-frequency tagging as (i) it leaves low-frequency oscillations unperturbed, and thus open for investigation, and ii) it can render the tagging invisible, resulting in more naturalistic paradigms and a lack of participant awareness. The development of this technique has far-reaching implications as oscillations involved in cognitive processes can be investigated, and potentially manipulated, in a more naturalistic manner.

Abstract

Frontal lobe organisation displays a functional gradient, with overarching processing goals located in parts anterior to more subordinate goals, processed more posteriorly. Functional specialisation for syntax and phonology within language relevant areas has been supported by meta-analyses and reviews, but never directly tested experimentally. We tested for organised functional specialisation by manipulating syntactic case and phonotactics, creating violations at the end of otherwise matched and predictable sentences. Both violations led to increased activation in expected language regions. We observe the clearest signs of a functional gradient for language processing in the medial frontal cortex, where syntactic violations activated a more anterior portion compared to the phonotactic violations. A large overlap of syntactic and phonotactic processing in the left inferior frontal gyrus (LIFG) supports the view that general structured sequence processes are located in this area. These findings are relevant for understanding how sentence processing is implemented in hierarchically organised processing steps in the frontal lobe.

Abstract

Formal language hierarchy describes levels of increasing syntactic complexity (adjacent dependencies, nonadjacent nested, nonadjacent crossed) of which the transcription into a hierarchy of cognitive complexity remains under debate. The cognitive foundations of formal language hierarchy have been contradicted by two types of evidence: First, adjacent dependencies are not easier to learn compared to nonadjacent; second, crossed nonadjacent dependencies may be easier than nested. However, studies providing these findings may have engaged confounds: Repetition monitoring strategies may have accounted for participants’ high performance in nonadjacent dependencies, and linguistic experience may have accounted for the advantage of crossed dependencies. We conducted two artificial grammar learning experiments where we addressed these confounds by manipulating reliance on repetition monitoring and by testing participants inexperienced with crossed dependencies. Results showed relevant differences in learning adjacent versus nonadjacent dependencies and advantages of nested over crossed, suggesting that formal language hierarchy may indeed translate into a hierarchy of cognitive complexity

Abstract

The current study explored the role of sentential inference in connecting lexical/grammatical knowledge and overall text comprehension in foreign language learning. Using structural equation modeling (SEM), causal relationships were examined between four latent variables: lexical knowledge, grammatical knowledge, sentential inference, and text comprehension. The study analyzed 281 Chinese university students learning Japanese as a second language and compared two causal models: (1) the partially-mediated model, which suggests that lexical knowledge, grammatical knowledge, and sentential inference concurrently influence text comprehension, and (2) the wholly-mediated model, which posits that both lexical and grammatical knowledge impact sentential inference, which then further affects text comprehension. The SEM comparison analysis supported the wholly-mediated model, showing sequential causal relationships from lexical knowledge to sentential inference and then to text comprehension, without significant contribution from grammatical knowledge. The results indicate that sentential inference serves as a crucial bridge between lexical knowledge and text comprehension.

Abstract

This study is the first to report chronometric evidence on Tongan language production. It has been speculated that the mora plays an important role during Tongan phonological encoding. A mora follows the (C)V form, so /a/ and /ka/ (but not /k/) denote a mora in Tongan. Using a picture-word naming paradigm, Tongan native speakers named pictures containing superimposed non-word distractors. This task has been used before in Japanese, Korean, and Vietnamese to investigate the initially selected unit during phonological encoding (IPU). Compared to control distractors, both onset and mora overlapping distractors resulted in faster naming latencies. Several alternative explanations for the pattern of results - proficiency in English, knowledge of Latin script, and downstream effects - are discussed. However, we conclude that Tongan phonological encoding likely natively uses the phoneme, and not the mora, as the IPU..

Abstract

People sometimes predict upcoming words during language comprehension, but debate remains on when and to what extent such predictions indeed occur. The rational adaptation hypothesis holds that predictions develop with expected utility: people predict more strongly when predictions are frequently confirmed (low prediction error) rather than disconfirmed. However, supporting evidence is mixed thus far and has only involved measuring responses to supposedly predicted nouns, not to preceding articles that may also be predicted. The current, large-sample (N = 200) ERP study on written discourse comprehension in Dutch therefore employs the well-known ‘pre-nominal prediction effect’: enhanced N400-like ERPs for articles that are unexpected given a likely upcoming noun’s gender (i.e., the neuter gender article ‘het’ when people expect the common gender noun phrase ‘de krant’, the newspaper) compared to expected articles. We investigated whether the pre-nominal prediction effect is larger when most of the presented stories contain predictable article-noun combinations (75% predictable, 25% unpredictable) compared to when most stories contain unpredictable combinations (25% predictable, 75% unpredictable). Our results show the pre-nominal prediction effect in both contexts, with little evidence to suggest that this effect depended on the percentage of predictable combinations. Moreover, the little evidence suggesting such a dependence was primarily observed for unexpected, neuter-gender articles (‘het’), which is inconsistent with the rational adaptation hypothesis. In line with recent demonstrations (Nieuwland, 2021a,b), our results suggest that linguistic prediction is less ‘rational’ or Bayes optimal than is often suggested.

Abstract

Does the way a word is written influence its spoken production? Previous studies suggest that orthography is involved only when the orthographic representation is highly relevant during speaking (e.g., in reading-aloud tasks). To address this issue, we carried out two experiments using the blocked cyclic picture-naming paradigm. In both experiments, participants were asked to name pictures repeatedly in orthographically homogeneous or heterogeneous blocks. In the naming task, the written form was not shown; however, the radical of the first character overlapped between the four pictures in this block type. A facilitative orthographic effect was found when picture names shared part of their written forms, compared with the heterogeneous condition. This facilitative effect was independent of the position of orthographic overlap (i.e., the left, the lower, or the outer part of the character). These findings strongly suggest that orthography can influence speaking even when it is not highly relevant (i.e., during picture naming) and the orthographic effect is less likely to be attributed to strategic preparation.

Abstract

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. α oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while β oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and β oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language comprehension. Twenty-two (18 female) Dutch native speakers listened to stories in Dutch and French while MEG was recorded. We used dependency parsing to identify three dependency states at each word: the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed forward models to predict α and β power from the dependency features. Results showed that dependency features predict α and β power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in α, while frontal and parietal, higher-order language regions, and motor regions are involved in β. Critically, α- and β-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. Because of the temporal similarity of the α-β responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and β oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.

Abstract

Research into the neural foundation of perception asserts a model where top-down predictions modulate the bottom-up processing of sensory input. Despite becoming increasingly influential in cognitive neuroscience, the precise account of this predictive coding framework remains debated. In this study, we aim to contribute to this debate by investigating how predictions about prosody facilitate speech perception, and to shed light especially on lexical access influenced by simultaneous predictions in different domains, inter alia, prosodic and semantic. Using a passive auditory oddball paradigm, we examined neural responses to prosodic changes, leading to a semantic change as in Dutch nouns canon [ˈkaːnɔn] ‘cannon’ vs kanon [kaːˈnɔn] ‘canon’, and used acoustically identical pseudowords as controls. Results from twenty-eight native speakers of Dutch (age range 18–32 years) indicated an enhanced P50/N100 complex to prosodic change in pseudowords as well as an MMN response to both words and pseudowords. The enhanced P50/N100 response to pseudowords is claimed to indicate that all relevant auditory information is still processed by the brain, whereas the reduced response to words might reflect the suppression of information that has already been encoded. The MMN response to pseudowords and words, on the other hand, is best justified by the unification of previously established prosodic representations with sensory and semantic input respectively. This pattern of results is in line with the predictive coding framework acting on multiple levels and is of crucial importance to indicate that predictions about linguistic prosodic information are utilized by the brain as early as 50 ms.