Publications

Abstract

Since the Enlightenment period, natural theories of speech and language evolution have florished in the language sciences. Four ever returning core issues are highlighted in this paper: Firstly, Is language natural to man or just an invention? Secondly, Is language a specific human ability (a ‘language instinct’) or does it arise from general cognitive capacities we share with other animals? Thirdly, Has the evolution of language been a gradual process or did it rather suddenly arise, due to some ‘evolutionary twist’? Lastly, Is the child's language acquisition an appropriate model for language evolution?

Abstract

PHD thesis, defended at the University of Leiden

Abstract

Demonstratives play a crucial role in the acquisition and use of language. Bringing together a team of leading scholars this detailed study, a first of its kind, explores meaning and use across fifteen typologically and geographically unrelated languages to find out what cross-linguistic comparisons and generalizations can be made, and how this might challenge current theory in linguistics, psychology, anthropology and philosophy. Using a shared experimental task, rounded out with studies of natural language use, specialists in each of the languages undertook extensive fieldwork for this comparative study of semantics and usage. An introduction summarizes the shared patterns and divergences in meaning and use that emerge.

Abstract

The evolution of language and spatial cognition may have been deeply interconnected. The argument
goes as follows: 1. Human native spatial abilities are poor, but we make up for it with linguistic
and cultural prostheses; 2. The explanation for the loss of native spatial abilities may be
that language has cannibalized the hippocampus, the mammalian mental ‘GPS’; 3. Consequently,
language may have borrowed conceptual primitives from spatial cognition (in line with ‘localism’),
these being differentially combined in different languages; 4. The hippocampus may have
been colonized because: (a) space was prime subject matter for communication, (b) gesture uses
space to represent space, and was likely precursor to language. In order to explain why the other
great apes haven’t gone in the same direction, we need to invoke other factors, notably the ‘interaction
engine’, the ensemble of interactional abilities that make cooperative communication possible
and provide the matrix for the evolution and learning of language.

Abstract

Wearing the hat of a cognitive anthropologist rather than an historian, I will try to amplify the ideas of Renn’s cited above. I argue that a particular subclass of material objects, namely “cognitive artifacts,” involves a close coupling of mind and artifact that acts like a brain prosthesis. Simple cognitive artifacts are external objects that act as aids to internal
computation, and not all cultures have extended inventories of these. Cognitive artifacts in this sense (e.g., calculating or measuring devices) have clearly played a central role in the history of science. But the notion can be widened to take in less material externalizations of cognition, like writing and language itself. A critical question here is how and why this close coupling of internal computation and external device actually works, a rather neglected question to which I’ll suggest some answers.

Abstract

Human communication displays a striking contrast between the diversity of languages and the universality of the principles underlying their use in conversation. Despite the importance of this interactional base, it is not obvious that it heavily imprints the structure of languages. However, a deep-time perspective suggests that early hominin communication was gestural, in line with all the other Hominidae. This gestural phase of early language development seems to have left its traces in the way in which spatial concepts, implemented in the hippocampus, provide organizing principles at the heart of grammar.

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

The present study investigates the construction with help followed by the bare or to-infinitive in seven varieties of web-based English from Australia, Ghana, Great Britain, Hong Kong, India, Jamaica and the USA. In addition to various factors known from the literature, such as register, minimization of cognitive complexity and avoidance of identity (horror aequi), it studies the effect of predictability of the infinitive given help and the other way round on the language user’s choice between the constructional variants. These probabilistic constraints are tested in a series of Bayesian generalized additive mixed-effects regression models. The results demonstrate that the to-infinitive is particularly frequent in contexts with low predictability, or, in information-theoretic terms, with high information content. This tendency is interpreted as communicatively efficient behaviour, when more predictable units of discourse get less formal marking, and less predictable ones get more formal marking. However, the strength, shape and directionality of predictability effects exhibit variation across the countries, which demonstrates the importance of the cross-lectal perspective in research on communicative efficiency and other universal functional principles.

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

Word classes play a central role in corpus linguistics under the name of parts of speech (POS). Many popular corpora are provided with POS tags. This chapter gives examples of popular tagsets and discusses the methods of automatic tagging. It also considers bottom-up approaches to POS induction, which are particularly important for the ‘poverty of stimulus’ debate in language acquisition research. The choice of optimal POS tagging involves many difficult decisions, which are related to the level of granularity, redundancy at different levels of corpus annotation, cross-linguistic applicability, language-specific descriptive adequacy, and dealing with fuzzy boundaries between POS. The chapter also discusses the problem of flexible word classes and demonstrates how corpus data with POS tags and syntactic dependencies can be used to quantify the level of flexibility in a language.

Abstract

Reinstatement of memory-related neural activity measured with high temporal precision potentially provides a useful index for real-time monitoring of the timing of activation of memory content during cognitive processing. The utility of such an index extends to any situation where one is interested in the (relative) timing of activation of different sources of information in memory, a paradigm case of which is tracking lexical activation during language processing. Essential for this approach is that memory reinstatement effects are robust, so that their absence (in the average) definitively indicates that no lexical activation is present. We used electroencephalography to test the robustness of a reported subsequent memory finding involving reinstatement of frequency-specific entrained oscillatory brain activity during subsequent recognition. Participants learned lists of words presented on a background flickering at either 6 or 15 Hz to entrain a steady-state brain response. Target words subsequently presented on a non-flickering background that were correctly identified as previously seen exhibited reinstatement effects at both entrainment frequencies. Reliability of these statistical inferences was however critically dependent on the approach used for multiple comparisons correction. We conclude that effects are not robust enough to be used as a reliable index of lexical activation during language processing.

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

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian Markov random fields. However, it is unclear whether it is possible to differentiate between phenotypic patterns associated with the differential diagnosis of schizophrenia and depression using this neurocognitive graph approach. In this study, we enrolled 215 first-episode patients with schizophrenia (FES), 125 with MDD, and 237 demographically-matched healthy controls (HCs). The cognitive performance of all participants was evaluated using a battery of neurocognitive tests. The graphical LASSO model was trained with a one-vs-one scenario to learn the conditional independent structure of neurocognitive features of each group. Participants in the holdout dataset were classified into different groups with the highest likelihood. A partial correlation matrix was transformed from the graphical model to further explore the neurocognitive graph for each group. The classification approach identified the diagnostic class for individuals with an average accuracy of 73.41% for FES vs HC, 67.07% for MDD vs HC, and 59.48% for FES vs MDD. Both of the neurocognitive graphs for FES and MDD had more connections and higher node centrality than those for HC. The neurocognitive graph for FES was less sparse and had more connections than that for MDD. Thus, neurocognitive graphs based on cognitive features are promising for describing endophenotypes that may discriminate schizophrenia from depression.

Abstract

Large language models that exhibit instruction-following behaviour represent one of the biggest recent upheavals in conversational interfaces, a trend in large part fuelled by the release of OpenAI's ChatGPT, a proprietary large language model for text generation fine-tuned through reinforcement learning from human feedback (LLM+RLHF). We review the risks of relying on proprietary software and survey the first crop of open-source projects of comparable architecture and functionality. The main contribution of this paper is to show that openness is differentiated, and to offer scientific documentation of degrees of openness in this fast-moving field. We evaluate projects in terms of openness of code, training data, model weights, RLHF data, licensing, scientific documentation, and access methods. We find that while there is a fast-growing list of projects billing themselves as 'open source', many inherit undocumented data of dubious legality, few share the all-important instruction-tuning (a key site where human labour is involved), and careful scientific documentation is exceedingly rare. Degrees of openness are relevant to fairness and accountability at all points, from data collection and curation to model architecture, and from training and fine-tuning to release and deployment.

Abstract

Speech recognition systems are a key intermediary in voice-driven human-computer interaction. Although speech recognition works well for pristine monologic audio, real-life use cases in open-ended interactive settings still present many challenges. We argue that timing is mission-critical for dialogue systems, and evaluate 5 major commercial ASR systems for their conversational and multilingual support. We find that word error rates for natural conversational data in 6 languages remain abysmal, and that overlap remains a key challenge (study 1). This impacts especially the recognition of conversational words (study 2), and in turn has dire consequences for downstream intent recognition (study 3). Our findings help to evaluate the current state of conversational ASR, contribute towards multidimensional error analysis and evaluation, and identify phenomena that need most attention on the way to build robust interactive speech technologies.

Abstract

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10−8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Abstract

For shared book reading to be effective for language development, the adult and child need to be highly engaged. The current paper adopted a mixed-methods approach to investigate caregiver’s language-boosting behaviours and children’s engagement during shared book reading. The results revealed there were more instances of joint attention and caregiver’s use of prompts during moments of higher engagement. However, instances of most language-boosting behaviours were similar across episodes of higher and lower engagement. Qualitative analysis assessing the link between children’s engagement and caregiver’s use of speech acts, revealed that speech acts do seem to contribute to high engagement, in combination with other aspects of the interaction.

Abstract

Reading is an important high‐level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large‐scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19–28 years old) and 16 children (11–13 years old), and graph theoretical analyses to investigate age‐related changes in large‐scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter‐regional connectivity and nodal degree in occipital regions, while children had stronger inter‐regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between‐task differences in inter‐regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults’ reading network is more specialized. (3) Children showed greater inter‐regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain‐general while others may be specific to the reading domain.

Abstract

Fundamental human traits, such as language and bipedalism, are associated with a range of anatomical adaptations in craniofacial shaping and skeletal remodeling. However, it is unclear how such morphological features arose during hominin evolution. FOXP2 is a brain-expressed transcription factor implicated in a rare disorder involving speech apraxia and language impairments. Analysis of its evolutionary history suggests that this gene may have contributed to the emergence of proficient spoken language. In the present study, through analyses of skeleton-specific knockout mice, we identified roles of Foxp2 in skull shaping and bone remodeling. Selective ablation of Foxp2 in cartilage disrupted pup vocalizations in a similar way to that of global Foxp2 mutants, which may be due to pleiotropic effects on craniofacial morphogenesis. Our findings also indicate that Foxp2 helps to regulate strength and length of hind limbs and maintenance of joint cartilage and intervertebral discs, which are all anatomical features that are susceptible to adaptations for bipedal locomotion. In light of the known roles of Foxp2 in brain circuits that are important for motor skills and spoken language, we suggest that this gene may have been well placed to contribute to coevolution of neural and anatomical adaptations related to speech and bipedal locomotion.

Abstract

Studies exploring the influence of executive functions (EF) on perspective-taking have focused on inhibition and working memory in young adults or clinical populations. Less consideration has been given to more complex capacities that also involve switching attention between perspectives, or to changes in EF and concomitant effects on perspective-taking across the lifespan. To address this, we assessed whether individual differences in inhibition and attentional switching in healthy adults (ages 17–84) predict performance on a task in which speakers identified targets for a listener with size-contrasting competitors in common or privileged ground. Modification differences across conditions decreased with age. Further, perspective taking interacted with EF measures: youngest adults’ sensitivity to perspective was best captured by their inhibitory performance; oldest adults’ sensitivity was best captured by switching performance. Perspective-taking likely involves multiple aspects of EF, as revealed by considering a wider range of EF tasks and individual capacities across the lifespan.

Abstract

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

Abstract

In recent years, there has been renewed interest in the biological and cultural evolution of music, and specifically in the role played by perceptual and cognitive factors in shaping core features of musical systems, such as melody, harmony, and rhythm. One proposal originates in the language sciences. It holds that aspects of musical systems evolve by adapting gradually, in the course of successive generations, to the structural and functional characteristics of the sensory and memory systems of learners and “users” of music. This hypothesis has found initial support in laboratory experiments on music transmission. In this article, we first review some of the most important theoretical and empirical contributions to the field of music evolution. Next, we identify a major current limitation of these studies, i.e., the lack of direct neural support for the hypothesis of cognitive adaptation. Finally, we discuss a recent experiment in which this issue was addressed by using event-related potentials (ERPs). We suggest that the introduction of neurophysiology in cultural transmission research may provide novel insights on the micro-evolutionary origins of forms of variation observed in cultural systems.

Abstract

The intergenerational stability of auditory symbolic systems, such as music, is thought to rely on brain processes that allow the faithful transmission of complex sounds. Little is known about the functional and structural aspects of the human brain which support this ability, with a few studies pointing to the bilateral organization of auditory networks as a putative neural substrate. Here, we further tested this hypothesis by examining the role of left–right neuroanatomical asymmetries between auditory cortices. We collected neuroanatomical images from a large sample of participants (nonmusicians) and analyzed them with Freesurfer’s surface-based morphometry method. Weeks after scanning, the same individuals participated in a laboratory experiment that simulated music transmission: the signaling games. We found that high accuracy in the intergenerational transmission of an artificial tone system was associated with reduced rightward asymmetry of cortical thickness in Heschl’s sulcus. Our study suggests that the high-fidelity copying of melodic material may rely on the extent to which computational neuronal resources are distributed across hemispheres. Our data further support the role of interhemispheric brain organization in the cultural transmission and evolution of auditory symbolic systems.

Abstract

Name signs are based on descriptions, initialization, and loan translations. Nyst and Baker (2003) have found crosslinguistic similarities in the phonology of name signs, such as a preference for one-handed signs and for the head location. Studying Kata Kolok (KK), a rural sign language without indigenous fingerspelling, strongly suggests that one-handedness is not correlated to initialization, but represents a more general feature of name sign phonology. Like in other sign languages, the head location is used frequently in both KK and Sign Language of the Netherlands (NGT) name signs. The use of nonmanuals, however, is strikingly different. NGT name signs are always accompanied by mouthings, which are absent in KK. Instead, KK name signs may use mouth gestures; these may disambiguate manually identical name signs, and even form independent name signs without any manual features

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

Is there a universal hierarchy of the senses, such that some senses (e.g., vision) are more accessible to consciousness and linguistic description than others (e.g., smell)? The long-standing presumption in Western thought has been that vision and audition are more objective than the other senses, serving as the basis of knowledge and understanding, whereas touch, taste, and smell are crude and of little value. This predicts that humans ought to be better at communicating about sight and hearing than the other senses, and decades of work based on English and related languages certainly suggests this is true. However, how well does this reflect the diversity of languages and communities worldwide? To test whether there is a universal hierarchy of the senses, stimuli from the five basic senses were used to elicit descriptions in 20 diverse languages, including 3 unrelated sign languages. We found that languages differ fundamentally in which sensory domains they linguistically code systematically, and how they do so. The tendency for better coding in some domains can be explained in part by cultural preoccupations. Although languages seem free to elaborate specific sensory domains, some general tendencies emerge: for example, with some exceptions, smell is poorly coded. The surprise is that, despite the gradual phylogenetic accumulation of the senses, and the imbalances in the neural tissue dedicated to them, no single hierarchy of the senses imposes itself upon language.

Abstract

People struggle to name odors, but this
limitation is not universal. Majid and
Kruspe investigate whether superior
olfactory performance is due to
subsistence, ecology, or language family.
By comparing closely related
communities in the Malay Peninsula, they
find that only hunter-gatherers are
proficient odor namers, suggesting that
subsistence is crucial.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Olfaction presents a particularly interesting arena to explore abstraction in language. Like other abstract domains, such as time, odours can be difficult to conceptualize. An odour cannot be seen or held, it can be difficult to locate in space, and for most people odours are difficult to verbalize. On the other hand, odours give rise to primary sensory experiences. Every time we inhale we are using olfaction to make sense of our environment. We present new experimental data from 30 Jahai hunter-gatherers from the Malay Peninsula and 30 matched Dutch participants from the Netherlands in an odour naming experiment. Participants smelled monomolecular odorants and named odours while reaction times, odour descriptors and facial expressions were measured. We show that while Dutch speakers relied on concrete descriptors, i.e. they referred to odour sources (e.g. smells like lemon), the Jahai used abstract vocabulary to name the same odours (e.g. musty). Despite this differential linguistic categorization, analysis of facial expressions showed that the two groups, nevertheless, had the same initial emotional reactions to odours. Critically, these cross-cultural data present a challenge for how to think about abstraction in language.

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

Boundary extension (BE) is a memory error in which observers remember more of a scene than they actually viewed. This error reflects one’s prediction that a scene naturally continues and is driven by scene schema and contextual knowledge. In two separate experiments we investigated the necessity of context and scene schema in BE. In Experiment 1, observers viewed scenes that either contained semantically consistent or inconsistent objects as well as objects on white backgrounds. In both types of scenes and in the no-background condition there was a BE effect; critically, semantic inconsistency in scenes reduced the magnitude of BE. In Experiment 2 when we used abstract shapes instead of meaningful objects, there was no BE effect. We suggest that although scene schema is necessary to elicit BE, contextual consistency is not required.

Abstract

The human experience is shaped by information from different perceptual channels, but it is still debated whether and how differential experience influences language use. To address this, we compared congenitally blind, blindfolded, and sighted people's descriptions of the same motion events experienced auditorily by all participants (i.e., via sound alone) and conveyed in speech and gesture. Comparison of blind and sighted participants to blindfolded participants helped us disentangle the effects of a lifetime experience of being blind versus the task-specific effects of experiencing a motion event by sound alone. Compared to sighted people, blind people's speech focused more on path and less on manner of motion, and encoded paths in a more segmented fashion using more landmarks and path verbs. Gestures followed the speech, such that blind people pointed to landmarks more and depicted manner less than sighted people. This suggests that visual experience affects how people express spatial events in the multimodal language and that blindness may enhance sensitivity to paths of motion due to changes in event construal. These findings have implications for the claims that language processes are deeply rooted in our sensory experiences.

Abstract

Each sensory modality has different affordances: vision has higher spatial acuity than audition, whereas audition has better temporal acuity. This may have consequences for the encoding of events and its subsequent multimodal language production—an issue that has received relatively little attention to date. In this study, we compared motion events presented as audio-only, visual-only, or multimodal (visual + audio) input and measured speech and co-speech gesture depicting path and manner of motion in Turkish. Input modality affected speech production. Speakers with audio-only input produced more path descriptions and fewer manner descriptions in speech compared to speakers who received visual input. In contrast, the type and frequency of gestures did not change across conditions. Path-only gestures dominated throughout. Our results suggest that while speech is more susceptible to auditory vs. visual input in encoding aspects of motion events, gesture is less sensitive to such differences.

Abstract

Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex. It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. To address this issue and to examine whether previous findings generalize to noninvasively measured neural activity in humans, we separately manipulated stimulus familiarity and expectation while noninvasively recording human brain activity using magnetoencephalography. We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex, the putative human homologue of monkey inferotemporal cortex. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

Abstract

Background

Autism is a dimensional condition, representing the extreme end of a continuum of social competence that extends throughout the general population. Currently, little is known about how autistic social traits (ASTs), measured across the full spectrum of severity, develop during childhood and adolescence, including whether there are developmental differences between boys and girls. Therefore, we sought to chart the trajectories of ASTs in the general population across childhood and adolescence, with a focus on gender differences.
Methods

Participants were 9,744 males (n = 4,784) and females (n = 4,960) from ALSPAC, a UK birth cohort study. ASTs were assessed when participants were aged 7, 10, 13 and 16 years, using the parent‐report Social Communication Disorders Checklist. Data were modelled using latent growth curve analysis.
Results

Developmental trajectories of males and females were nonlinear, showing a decline from 7 to 10 years, followed by an increase between 10 and 16 years. At 7 years, males had higher levels of ASTs than females (mean raw score difference = 0.88, 95% CI [.72, 1.04]), and were more likely (odds ratio [OR] = 1.99; 95% CI, 1.82, 2.16) to score in the clinical range on the SCDC. By 16 years this gender difference had disappeared: males and females had, on average, similar levels of ASTs (mean difference = 0.00, 95% CI [−0.19, 0.19]) and were equally likely to score in the SCDC's clinical range (OR = 0.91, 95% CI, 0.73, 1.10). This was the result of an increase in females’ ASTs between 10 and 16 years.
Conclusions

There are gender‐specific trajectories of autistic social impairment, with females more likely than males to experience an escalation of ASTs during early‐ and midadolescence. It remains to be discovered whether the observed female adolescent increase in ASTs represents the genuine late onset of social difficulties or earlier, subtle, pre‐existing difficulties becoming more obvious.

Abstract

We investigated cross-modal influences between speech and sign in hearing bimodal bilinguals, proficient in a spoken and a sign language, and its consequences on visual attention during message preparation using eye-tracking. We focused on spatial expressions in which sign languages, unlike spoken languages, have a modality-driven preference to mention grounds (big objects) prior to figures (smaller objects). We compared hearing bimodal bilinguals’ spatial expressions and visual attention in Dutch and Dutch Sign Language (N = 18) to those of their hearing non-signing (N = 20) and deaf signing peers (N = 18). In speech, hearing bimodal bilinguals expressed more ground-first descriptions and fixated grounds more than hearing non-signers, showing influence from sign. In sign, they used as many ground-first descriptions as deaf signers and fixated grounds equally often, demonstrating no influence from speech. Cross-linguistic influence of word order preference and visual attention in hearing bimodal bilinguals appears to be one-directional modulated by modality-driven differences.

Abstract

Language processing requires us to integrate incoming linguistic representations with representations of past input, often across intervening words and phrases. This computational situation has been argued to require retrieval of the appropriate representations from memory via a set of features or representations serving as retrieval cues. However, even within in a cue-based retrieval account of language comprehension, both the structure of retrieval cues and the particular computation that underlies direct-access retrieval are still underspecified. Evidence from two event-related brain potential (ERP) experiments that show cue-based interference from different types of linguistic representations during ellipsis comprehension are consistent with an architecture wherein different cue types are integrated, and where the interaction of cue with the recent contents of memory determines processing outcome, including expression of the interference effect in ERP componentry. I conclude that retrieval likely includes a computation where cues are integrated with the contents of memory via a linear weighting scheme, and I propose vector addition as a candidate formalization of this computation. I attempt to account for these effects and other related phenomena within a broader cue-based framework of language processing.

Abstract

Language comprehension involves coping with ambiguity and recovering from misanalysis. Syntactic ambiguity resolution is associated with increased reading times, a classic finding that has shaped theories of sentence processing. However, reaction times conflate the time it takes a process to complete with the quality of the behavior-related information available to the system. We therefore used the speed-accuracy tradeoff procedure (SAT) to derive orthogonal estimates of processing time and interpretation accuracy, and tested whether stronger retrieval cues (via semantic relatedness: neighed->horse vs. fell->horse) aid interpretation during recovery. On average, ambiguous sentences took 250ms longer (SAT rate) to interpret than unambiguous controls, demonstrating veridical differences in processing time. Retrieval cues more strongly related to the true subject always increased accuracy, regardless of ambiguity. These findings are consistent with a language processing architecture where cue-driven operations give rise to interpretation, and wherein diagnostic cues aid retrieval, regardless of parsing difficulty or structural uncertainty.

Abstract

Gene duplication events can drive evolution by providing genetic material for new gene functions, and they create opportunities for diverse developmental strategies to emerge between species. To study the contribution of duplicated genes to human early development, we examined the evolution and function of NANOGP1, a tandem duplicate of the transcription factor NANOG. We found that NANOGP1 and NANOG have overlapping but distinct expression profiles, with high NANOGP1 expression restricted to early epiblast cells and naïve-state pluripotent stem cells. Sequence analysis and epitope-tagging revealed that NANOGP1 is protein coding with an intact homeobox domain. The duplication that created NANOGP1 occurred earlier in primate evolution than previously thought and has been retained only in great apes, whereas Old World monkeys have disabled the gene in different ways, including homeodomain point mutations. NANOGP1 is a strong inducer of naïve pluripotency; however, unlike NANOG, it is not required to maintain the undifferentiated status of human naïve pluripotent cells. By retaining expression, sequence and partial functional conservation with its ancestral copy, NANOGP1 exemplifies how gene duplication and subfunctionalisation can contribute to transcription factor activity in human pluripotency and development.

Abstract

Listeners are known to use adjacent contextual speech rate in processing temporally ambiguous speech sounds. For instance, an ambiguous vowel between short /A/ and long /a:/ in Dutch sounds relatively long (i.e., as /a:/) embedded in a fast precursor sentence, but short in a slow sentence. Besides the local speech rate, listeners also track talker-specific global speech rates. However, it is yet unclear whether other talkers' global rates are encoded with reference to a listener's self-produced rate. Three experiments addressed this question. In Experiment 1, one group of participants was instructed to speak fast, whereas another group had to speak slowly. The groups were compared on their perception of ambiguous /A/-/a:/ vowels embedded in neutral rate speech from another talker. In Experiment 2, the same participants listened to playback of their own speech and again evaluated target vowels in neutral rate speech. Neither of these experiments provided support for the involvement of self-produced speech in perception of another talker's speech rate. Experiment 3 repeated Experiment 2 but with a new participant sample that was unfamiliar with the participants from Experiment 2. This experiment revealed fewer /a:/ responses in neutral speech in the group also listening to a fast rate, suggesting that neutral speech sounds slow in the presence of a fast talker and vice versa. Taken together, the findings show that self-produced speech is processed differently from speech produced by others. They carry implications for our understanding of the perceptual and cognitive mechanisms involved in rate-dependent speech perception in dialogue settings.

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

Individual differences in cognitive abilities are ubiquitous across the spectrum of proficient language users. Although speakers differ with regard to their memory capacity, ability for inhibiting distraction, and ability to shift between different processing levels, comprehension is generally successful. However, this does not mean it is identical across individuals; listeners and readers may rely on different processing strategies to exploit distributional information in the service of efficient understanding. In the following psycholinguistic reading experiment, we investigate potential sources of individual differences in the processing of co-occurring words. Participants read modifier-noun bigrams like absolute silence in a self-paced reading task. Backward transition probability (BTP) between the two lexemes was used to quantify the prominence of the bigram as a whole in comparison to the frequency of its parts. Of five individual difference measures (processing speed, verbal working memory, cognitive inhibition, global-local scope shifting, and personality), two proved to be significantly associated with the effect of BTP on reading times. Participants who could inhibit a distracting global environment in order to more efficiently retrieve a single part and those that preferred the local level in the shifting task showed greater effects of the co-occurrence probability of the parts. We conclude that some participants are more likely to retrieve bigrams via their parts and their co-occurrence statistics whereas others more readily retrieve the two words together as a single chunked unit.

Abstract

Iconicity in language is receiving increased attention from many fields, but our understanding of iconicity is only as good as the measures we use to quantify it. We collected iconicity measures for 304 Japanese words from English-speaking participants, using rating and guessing tasks. The words included ideophones (structurally marked depictive words) along with regular lexical items from similar semantic domains (e.g., fuwafuwa ‘fluffy’, jawarakai ‘soft’). The two measures correlated, speaking to their validity. However, ideophones received consistently higher iconicity ratings than other items, even when guessed at the same accuracies, suggesting the rating task is more sensitive to cues like structural markedness that frame words as iconic. These cues did not always guide participants to the meanings of ideophones in the guessing task, but they did make them more confident in their guesses, even when they were wrong. Consistently poor guessing results reflect the role different experiences play in shaping construals of iconicity. Using multiple measures in tandem allows us to explore the interplay between iconicity and these external factors. To facilitate this, we introduce a reproducible workflow for creating rating and guessing tasks from standardised wordlists, while also making improvements to the robustness, sensitivity and discriminability of previous approaches.

Abstract

Luthra, Peraza-Santiago, Beeson, Saltzman, Crinnion, and Magnuson (2021) present data from the lexically mediated compensation for coarticulation paradigm that they claim provides conclusive evidence in favor of top-down processing in speech perception. We argue here that this evidence does not support that conclusion. The findings are open to alternative explanations, and we give data in support of one of them (that there is an acoustic confound in the materials). Lexically mediated compensation for coarticulation thus remains elusive, while prior data from the paradigm instead challenge the idea that there is top-down processing in online speech recognition.

Abstract

Recurrent deletions of a ~600-kb region of 16p11.2 have been associated with a highly penetrant form of childhood apraxia of speech (CAS). Yet prior findings have been based on a small, potentially biased sample using retrospectively collected data. We examine the prevalence of CAS in a larger cohort of individuals with 16p11.2 deletion using a prospectively designed assessment battery. The broader speech and language phenotype associated with carrying this deletion was also examined. 55 participants with 16p11.2 deletion (47 children, 8 adults) underwent deep phenotyping to test for the presence of CAS and other speech and language diagnoses. Standardized tests of oral motor functioning, speech production, language, and non-verbal IQ were conducted. The majority of children (77%) and half of adults (50%) met criteria for CAS. Other speech outcomes were observed including articulation or phonological errors (i.e., phonetic and cognitive-linguistic errors, respectively), dysarthria (i.e., neuromuscular speech disorder), minimal verbal output, and even typical speech in some. Receptive and expressive language impairment was present in 73% and 70% of children, respectively. Co-occurring neurodevelopmental conditions (e.g., autism) and non-verbal IQ did not correlate with the presence of CAS. Findings indicate that CAS is highly prevalent in children with 16p11.2 deletion with symptoms persisting into adulthood for many. Yet CAS occurs in the context of a broader speech and language profile and other neurobehavioral deficits. Further research will elucidate specific genetic and neural pathways leading to speech and language deficits in individuals with 16p11.2 deletions, resulting in more targeted speech therapies addressing etiological pathways.

Abstract

The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.

Abstract

As conversation is the most important way of using language, linguists and psychologists should combine forces to investigate how interlocutors deal with the cognitive demands arising during conversation. Linguistic analyses of corpora of conversation are needed to understand the structure of conversations, and experimental work is indispensable for understanding the underlying cognitive processes. We argue that joint consideration of corpus and experimental data is most informative when the utterances elicited in a lab experiment match those extracted from a corpus in relevant ways. This requirement to compare like with like seems obvious but is not trivial to achieve. To illustrate this approach, we report two experiments where responses to polar (yes/no) questions were elicited in the lab and the response latencies were compared to gaps between polar questions and answers in a corpus of conversational speech. We found, as expected, that responses were given faster when they were easy to plan and planning could be initiated earlier than when they were harder to plan and planning was initiated later. Overall, in all but one condition, the latencies were longer than one would expect based on the analyses of corpus data. We discuss the implication of this partial match between the data sets and more generally how corpus and experimental data can best be combined in studies of conversation.

Abstract

Turn-taking in everyday conversation is fast, with median latencies in corpora of conversational speech often reported to be under 300 ms. This seems like magic, given that experimental research on speech planning has shown that speakers need much more time to plan and produce even the shortest of utterances. This paper reviews how language scientists have combined linguistic analyses of conversations and experimental work to understand the skill of swift turn-taking and proposes a tentative solution to the riddle of fast turn-taking.

Abstract

While recent laboratory studies suggest that the use of competing languages is a driving force in foreign language (FL) attrition (i.e. forgetting), research on “real” attriters has failed to demonstrate
such a relationship. We addressed this issue in a large-scale longitudinal study, following German students throughout a study abroad in Spain and their first six months back in Germany. Monthly,
percentage-based frequency of use measures enabled a fine-grained description of language use.
L3 Spanish forgetting rates were indeed predicted by the quantity and quality of Spanish use, and
correlated negatively with L1 German and positively with L2 English letter fluency. Attrition rates
were furthermore influenced by prior Spanish proficiency, but not by motivation to maintain
Spanish or non-verbal long-term memory capacity. Overall, this study highlights the importance
of language use for FL retention and sheds light on the complex interplay between language
use and other determinants of attrition.

Abstract

Gaze cues serve an important role in facilitating human conversations and are generally considered to be one of the most important non-verbal cues. Gaze cues are used to manage turn-taking, coordinate joint attention, regulate intimacy, and signal cognitive effort. In particular, it is well established that gaze aversion is used in conversations to avoid prolonged periods of mutual gaze. Given the numerous functions of gaze cues, there has been extensive work on modelling these cues in social robots. Researchers have also tried to identify the impact of robot gaze on human participants. However, the influence of robot gaze behavior on human gaze behavior has been less explored. We conducted a within-subjects user study (N = 33) to verify if a robot’s gaze aversion influenced human gaze aversion behavior. Our results show that participants tend to avert their gaze more when the robot keeps staring at them as compared to when the robot exhibits well-timed gaze aversions. We interpret our findings in terms of intimacy regulation: humans try to compensate for the robot’s lack of gaze aversion.

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

What are the phonological representations that listeners use to map information about the segmental content of speech onto the mental lexicon during spoken-word recognition? Recent evidence from perceptual-learning paradigms seems to support (context-dependent) allophones as the basic representational units in spoken-word recognition. But recent evidence from a selective-adaptation paradigm seems to suggest that context-independent phonemes also play a role. We present three experiments using selective adaptation that constitute strong tests of these representational hypotheses. In Experiment 1, we tested generalization of selective adaptation using different allophones of Dutch /r/ and /l/ – a case where generalization has not been found with perceptual learning. In Experiments 2 and 3, we tested generalization of selective adaptation using German back fricatives in which allophonic and phonemic identity were varied orthogonally. In all three experiments, selective adaptation was observed only if adaptors and test stimuli shared allophones. Phonemic identity, in contrast, was neither necessary nor sufficient for generalization of selective adaptation to occur. These findings and other recent data using the perceptual-learning paradigm suggest that pre-lexical processing during spoken-word recognition is based on allophones, and not on context-independent phonemes

Abstract

We investigated whether learning an artificial language at 17 months was predictive of children’s natural language vocabulary and grammar skills at 54 months. Children at 17 months listened to an artificial language containing non-adjacent dependencies, and were then tested on their learning to segment and to generalise the structure of the language. At 54 months, children were then tested on a range of standardised natural language tasks that assessed receptive and expressive vocabulary and grammar. A structural equation model demonstrated that learning the artificial language generalisation at 17 months predicted language abilities – a composite of vocabulary and grammar skills – at 54 months, whereas artificial language segmentation at 17 months did not predict language abilities at this age. Artificial language learning tasks – especially those that probe grammar learning – provide a valuable tool for uncovering the mechanisms driving children’s early language development.

Abstract

Propagation of novel linguistic terms is an important aspect of language use and language
change. Here, we test how social network size influences people’s likelihood of adopting novel
labels by examining hashtag use on Twitter. Specifically, we test whether following fewer Twitter
users leads to more varied and malleable hashtag use on Twitter , because each followed user is
ascribed greater weight and thus exerts greater influence on the following user. Focusing on Dutch
users tweeting about the terrorist attack in Brussels in 2016, we show that people who follow
fewer other users use a larger number of unique hashtags to refer to the event, reflecting greater
malleability and variability in use. These results have implications for theories of language learning, language use, and language change.

Abstract

Previous research examining the factors that determine language choice and voluntary switching mainly involved early bilinguals. Here, using picture naming, we investigated language choice and switching in late Dutch–English bilinguals. We found that naming was overall slower in cued than in voluntary switching, but switch costs occurred in both types of switching. The magnitude of switch costs differed depending on the task and language, and was moderated by L2 proficiency. Self-rated rather than objectively assessed proficiency predicted voluntary switching and ease of lexical access was associated with language choice. Between-language and within-language switch costs were not correlated. These results highlight self-rated proficiency as a reliable predictor of voluntary switching, with language modulating switch costs. As in early bilinguals, ease of lexical access was related to word-level language choice of late bilinguals.

Abstract

Communication disorder is common in Koolen de Vries syndrome (KdVS), yet its specific symptomatology has not been examined, limiting prognostic counselling and application of targeted therapies. Here we examine the communication phenotype associated with KdVS. Twenty-nine participants (12 males, 4 with KANSL1 variants, 25 with 17q21.31 microdeletion), aged 1.0–27.0 years were assessed for oral-motor, speech, language, literacy, and social functioning. Early history included hypotonia and feeding difficulties. Speech and language development was delayed and atypical from onset of first words (2; 5–3; 5 years of age on average). Speech was characterised by apraxia (100%) and dysarthria (93%), with stuttering in some (17%). Speech therapy and multi-modal communication (e.g., sign-language) was critical in preschool. Receptive and expressive language abilities were typically commensurate (79%), both being severely affected relative to peers. Children were sociable with a desire to communicate, although some (36%) had pragmatic impairments in domains, where higher-level language was required. A common phenotype was identified, including an overriding ‘double hit’ of oral hypotonia and apraxia in infancy and preschool, associated with severely delayed speech development. Remarkably however, speech prognosis was positive; apraxia resolved, and although dysarthria persisted, children were intelligible by mid-to-late childhood. In contrast, language and literacy deficits persisted, and pragmatic deficits were apparent. Children with KdVS require early, intensive, speech motor and language therapy, with targeted literacy and social language interventions as developmentally appropriate. Greater understanding of the linguistic phenotype may help unravel the relevance of KANSL1 to child speech and language development.

Abstract

Background
Heterozygous disruptions of FOXP2 were the first identified molecular cause for severe speech disorder; childhood apraxia of speech (CAS), yet few cases have been reported, limiting knowledge of the condition.

Methods
Here we phenotyped 29 individuals from 18 families with pathogenic FOXP2-only variants (13 loss-of-function, 5 missense variants; 14 males; aged 2 years to 62 years). Health and development (cognitive, motor, social domains) was examined, including speech and language outcomes with the first cross-linguistic analysis of English and German.

Results
Speech disorders were prevalent (24/26, 92%) and CAS was most common (23/26, 89%), with similar speech presentations across English and German. Speech was still impaired in adulthood and some speech sounds (e.g. ‘th’, ‘r’, ‘ch’, ‘j’) were never acquired. Language impairments (22/26, 85%) ranged from mild to severe. Comorbidities included feeding difficulties in infancy (10/27, 37%), fine (14/27, 52%) and gross (14/27, 52%) motor impairment, anxiety (6/28, 21%), depression (7/28, 25%), and sleep disturbance (11/15, 44%). Physical features were common (23/28, 82%) but with no consistent pattern. Cognition ranged from average to mildly impaired, and was incongruent with language ability; for example, seven participants with severe language disorder had average non-verbal cognition.

Conclusions
Although we identify increased prevalence of conditions like anxiety, depression and sleep disturbance, we confirm that the consequences of FOXP2 dysfunction remain relatively specific to speech disorder, as compared to other recently identified monogenic conditions associated with CAS. Thus, our findings reinforce that FOXP2 provides a valuable entrypoint for examining the neurobiological bases of speech disorder.

Abstract

A relatively new analysis technique, known as neural decoding or multivariate pattern analysis (MVPA), has become increasingly popular for cognitive neuroimaging studies over recent years. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. A field in which these techniques have led to novel insights in particular is that of visual working memory (VWM). In the present study, we subjected human volunteers to a combined VWM/imagery task while recording their neural signals using magnetoencephalography (MEG). We applied multivariate decoding analyses to uncover the temporal profile underlying the neural representations of the memorized item. Analysis of gaze position however revealed that our results were contaminated by systematic eye movements, suggesting that the MEG decoding results from our originally planned analyses were confounded. In addition to the eye movement analyses, we also present the original analyses to highlight how these might have readily led to invalid conclusions. Finally, we demonstrate a potential remedy, whereby we train the decoders on a functional localizer that was specifically designed to target bottom-up sensory signals and as such avoids eye movements. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.

Abstract

Caregiver abstract talk during shared reading predicts preschool-age children’s vocabulary development. However, previous research has focused on level of abstraction with less consideration of the style of extratextual talk. Here, we investigated the relation between these two dimensions of extratextual talk, and their contributions to variance in children’s vocabulary skills. Caregiver level of abstraction was associated with an interactive reading style. Controlling for socioeconomic status and child age, high interactivity predicted children’s concurrent vocabulary skills whereas abstraction did not. Controlling for earlier vocabulary skills, neither dimension of the extratextual talk predicted later vocabulary. Theoretical and practical relevance are discussed.

Abstract

Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.

Abstract

We conducted three neighborhood experiments with Dutch-English bilinguals to test effects of L2 proficiency and neighborhood characteristics within and between languages. In the past 20 years, the English (L2) proficiency of this population has considerably increased. To consider the impact of this development on neighborhood effects, we conducted a strict replication of the English lexical decision task by van Heuven, Dijkstra, & Grainger (1998, Exp. 4). In line with our prediction, English characteristics (neighborhood size, word and bigram frequency) dominated the word and nonword responses, while the nonwords also revealed an interaction of English and Dutch neighborhood size.
The prominence of English was tested again in two experiments introducing a stronger neighborhood manipulation. In English lexical decision and progressive demasking, English items with no orthographic neighbors at all were contrasted with items having neighbors in English or Dutch (‘hermits’) only, or in both languages. In both tasks, target processing was affected strongly by the presence of English neighbors, but only weakly by Dutch neighbors. Effects are interpreted in terms of two underlying processing mechanisms: language-specific global lexical activation and lexical competition.

Abstract

NBEA is a candidate gene for autism, and de novo variants have been reported in neurodevelopmental disease (NDD) cohorts. However, NBEA has not been rigorously evaluated as a disease gene, and associated phenotypes have not been delineated. We identified 24 de novo NBEA variants in patients with NDD, establishing NBEA as an NDD gene. Most patients had epilepsy with onset in the first few years of life, often characterized by generalized seizure types, including myoclonic and atonic seizures. Our data show a broader phenotypic spectrum than previously described, including a myoclonic-astatic epilepsy–like phenotype in a subset of patients.

Abstract

Many studies investigating the temporal alignment of co-speech
gestures to acoustic units in the speech signal find a close
coupling of the gestural landmarks and pitch accents or the
stressed syllable of pitch-accented words. In English, a pitch
accent is anchored in the lexically stressed syllable. Hence, it is
unclear whether it is the lexical phonological dimension of
stress, or the phrase-level prominence that determines the
details of speech-gesture synchronization. This paper explores
the relation between gestural phase transitions and accentual F0
peaks in Stockholm Swedish, which exhibits a lexical pitch
accent distinction. When produced with phrase-level
prominence, there are three different configurations of
lexicality of F0 peaks and the status of the syllable it is aligned
with. Through analyzing the alignment of the different F0 peaks
with gestural onsets in spontaneous dyadic conversations, we
aim to contribute to our understanding of the role of lexical
prosodic phonology in the co-production of speech and gesture.
The results, though limited by a small dataset, still suggest
differences between the three types of peaks concerning which
types of gesture phase onsets they tend to align with, and how
well these landmarks align with each other, although these
differences did not reach significance.

Abstract

Do people routinely pre-activate the meaning and even the phonological form of upcoming words? The most acclaimed evidence for phonological prediction comes from a 2005 Nature Neuroscience publication by DeLong, Urbach and Kutas, who observed a graded modulation of electrical brain potentials (N400) to nouns and preceding articles by the probability that people use a word to continue the sentence fragment (‘cloze’). In our direct replication study spanning 9 laboratories (N=334), pre-registered replication-analyses and exploratory Bayes factor analyses successfully replicated the noun-results but, crucially, not the article-results. Pre-registered single-trial analyses also yielded a statistically significant effect for the nouns but not the articles. Exploratory Bayesian single-trial analyses showed that the article-effect may be non-zero but is likely far smaller than originally reported and too small to observe without very large sample sizes. Our results do not support the view that readers routinely pre-activate the phonological form of predictable words.

Abstract

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific
aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond
temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise
magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data
are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a
principled solution to store, organise, process and share the multidimensional data volumes produced
by the modality. The standard also includes well-defined metadata, to facilitate future data
harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging
community and paves the way to further integration of other techniques in electrophysiology. MEGBIDS
builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several dataanalytics
software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data
resources available to everyone.

Abstract

Our senses are constantly bombarded with a myriad of signals. To make sense of this cacophony, the brain needs to integrate signals emanating from a common source, but segregate signals originating from the different sources. Thus, multisensory perception relies critically on inferring the world’s causal structure (i. e. one common vs. multiple independent sources). Behavioural research has shown that the brain arbitrates between sensory integration and segregation consistent with the principles of Bayesian Causal Inference. At the neural level, recent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) studies have shown that the brain accomplishes Bayesian Causal Inference by dynamically encoding multiple perceptual estimates across the sensory processing hierarchies. Only at the top of the hierarchy in anterior parietal cortices did the brain form perceptual estimates that take into account the observer’s uncertainty about the world’s causal structure consistent with Bayesian Causal Inference.

Abstract

Egophoric verbal marking is a typological feature common to Barbacoan languages, but otherwise unknown in the Andean sphere. The verbal systems of three out of the four living Barbacoan languages, Cha’palaa, Tsafiki and Awa Pit, have previously been shown to express egophoric contrasts. The status of Guambiano has, however, remained uncertain. In this chapter, I show that there are in fact two layers of egophoric or egophoric-like marking visible in Guambiano’s grammar. Guambiano patterns with certain other (non-Barbacoan) languages in having ego-categories which function within a broader evidential system. It is additionally possible to detect what is possibly a more archaic layer of egophoric marking in Guambiano’s verbal system. This marking may be inherited from a common Barbacoan system, thus pointing to a potential genealogical basis for the egophoric patterning common to these languages. The multiple formal expressions of egophoricity apparent both within and across the four languages reveal how egophoric contrasts are susceptible to structural renewal, suggesting a pan-Barbacoan preoccupation with the linguistic encoding of self-knowledge.

Abstract

The early recognition of fundamental social actions, like questions, is crucial for understanding the speaker’s intended message and planning a timely response in conversation. Questions themselves may express more than one social action category (e.g., an information request “What time is it?”, an invitation “Will you come to my party?” or a criticism “Are you crazy?”). Although human language use occurs predominantly in a multimodal context, prior research on social actions has mainly focused on the verbal modality. This study breaks new ground by investigating how conversational facial signals may map onto the expression of different types of social actions conveyed through questions. The distribution, timing, and temporal organization of facial signals across social actions was analysed in a rich corpus of naturalistic, dyadic face-to-face Dutch conversations. These social actions were: Information Requests, Understanding Checks, Self-Directed questions, Stance or Sentiment questions, Other-Initiated Repairs, Active Participation questions, questions for Structuring, Initiating or Maintaining Conversation, and Plans and Actions questions. This is the first study to reveal differences in distribution and timing of facial signals across different types of social actions. The findings raise the possibility that facial signals may facilitate social action recognition during language processing in multimodal face-to-face interaction.

Abstract

In conversation, recognizing social actions (similar to ‘speech acts’) early is important to quickly understand the speaker’s intended message and to provide a fast response. Fast turns are typical for fundamental social actions like questions, since a long gap can indicate a dispreferred response. In multimodal face-to-face interaction, visual signals may contribute to this fast dynamic. The face is an important source of visual signalling, and previous research found that prevalent facial signals such as eyebrow movements facilitate the rapid recognition of questions. We aimed to investigate whether early eyebrow movements with natural movement intensities facilitate question identification, and whether specific intensities are more helpful in detecting questions. Participants were instructed to view videos of avatars where the presence of eyebrow movements (eyebrow frown or raise vs. no eyebrow movement) was manipulated, and to indicate whether the utterance in the video was a question or statement. Results showed higher accuracies for questions with eyebrow frowns, and faster response times for questions with eyebrow frowns and eyebrow raises. No additional effect was observed for the specific movement intensity. This suggests that eyebrow movements that are representative of naturalistic multimodal behaviour facilitate question recognition.

Abstract

Conversation is a time-pressured environment. Recognizing a social action (the ‘‘speech act,’’ such as a question requesting information) early is crucial in conversation to quickly understand the intended message and plan a timely response. Fast turns between interlocutors are especially relevant for responses to questions since a long gap may be meaningful by itself. Human language is multimodal, involving speech as well as visual signals from the body, including the face. But little is known about how conversational facial signals contribute to the communication of social actions. Some of the most prominent facial signals in conversation are eyebrow movements. Previous studies found links between eyebrow movements and questions, suggesting that these facial signals could contribute to the rapid recognition of questions. Therefore, we aimed to investigate whether early eyebrow movements (eyebrow frown or raise vs. no eyebrow movement) facilitate question identification. Participants were instructed to view videos of avatars where the presence of eyebrow movements accompanying questions was manipulated. Their task was to indicate whether the utterance was a question or a statement as accurately and quickly as possible. Data were collected using the online testing platform Gorilla. Results showed higher accuracies and faster response times for questions with eyebrow frowns, suggesting a facilitative role of eyebrow frowns for question identification. This means that facial signals can critically contribute to the communication of social actions in conversation by signaling social action-specific visual information and providing visual cues to speakers’ intentions.

Abstract

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain’s white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

Abstract

Non-invasive brain stimulation techniques are popular tools to investigate brain function in health and disease. Although transcranial magnetic stimulation (TMS) is widely used in cognitive neuroscience research to probe causal structure-function relationships, studies often yield inconclusive results. To improve the effectiveness of TMS studies, we argue that the cognitive neuroscience community needs to revise the stimulation focality principle – the spatial resolution with which TMS can differentially stimulate cortical regions. In the motor domain, TMS can differentiate between cortical muscle representations of adjacent fingers. However, this high degree of spatial specificity cannot be obtained in all cortical regions due to the influences of cortical folding patterns on the TMS-induced electric field. The region-dependent focality of TMS should be assessed a priori to estimate the experimental feasibility. Post-hoc simulations allow modeling of the relationship between cortical stimulation exposure and behavioral modulation by integrating data across stimulation sites or subjects.

Abstract

Phonetic convergence—i.e., adapting one’s speech
towards that of an interlocutor—has been shown
to occur in human-human conversations as well as
human-machine interactions. Here, we investigate
the hypothesis that human-to-robot convergence is
influenced by the human’s perception of the robot
and by the conversation’s topic. We conducted a
within-subjects experiment in which 33 participants
interacted with two robots differing in their eye gaze
behavior—one looked constantly at the participant;
the other produced gaze aversions, similarly to a
human’s behavior. Additionally, the robot asked
questions with increasing intimacy levels.
We observed that the speakers tended to converge
on F0 to the robots. However, this convergence
to the robots was not modulated by how the
speakers perceived them or by the topic’s intimacy.
Interestingly, speakers produced lower F0 means
when talking about more intimate topics. We
discuss these findings in terms of current theories of
conversational convergence.

Abstract

Mice display a wide repertoire of vocalizations that varies with sex, strain, and context. Especially during social interaction, including sexually motivated dyadic interaction, mice emit sequences of ultrasonic vocalizations (USVs) of high complexity. As animals of both sexes vocalize, a reliable attribution of USVs to their emitter is essential. The state-of-the-art in sound localization for USVs in 2D allows spatial localization at a resolution of multiple centimeters. However, animals interact at closer ranges, e.g. snout-to-snout. Hence, improved algorithms are required to reliably assign USVs. We present a novel algorithm, SLIM (Sound Localization via Intersecting Manifolds), that achieves a 2–3-fold improvement in accuracy (13.1–14.3 mm) using only 4 microphones and extends to many microphones and localization in 3D. This accuracy allows reliable assignment of 84.3% of all USVs in our dataset. We apply SLIM to courtship interactions between adult C57Bl/6J wildtype mice and those carrying a heterozygous Foxp2 variant (R552H). The improved spatial accuracy reveals that vocalization behavior is dependent on the spatial relation between the interacting mice. Female mice vocalized more in close snout-to-snout interaction while male mice vocalized more when the male snout was in close proximity to the female's ano-genital region. Further, we find that the acoustic properties of the ultrasonic vocalizations (duration, Wiener Entropy, and sound level) are dependent on the spatial relation between the interacting mice as well as on the genotype. In conclusion, the improved attribution of vocalizations to their emitters provides a foundation for better understanding social vocal behaviors.

Abstract

Implicit up/down words, such as bird and foot, systematically influence performance on visual tasks involving immediately following targets in compatible vs. incompatible locations. Recent studies have observed that the semantic relation between prime words and target pictures can strongly influence the size and even the direction of the effect: Semantically related targets are processed faster in congruent vs. incongruent locations (location-specific priming), whereas unrelated targets are processed slower in congruent locations. Here, we used eye-tracking to investigate the moment-to-moment processes underlying this pattern. Our reaction time results for related targets replicated the location-specific priming effect and showed a trend towards interference for unrelated targets. We then used growth curve analysis to test how up/down words and their match vs. mismatch with immediately following targets in terms of semantics and vertical location influences concurrent saccadic eye movements. There was a strong main effect of spatial association on linear growth with up words biasing changes in y-coordinates over time upwards relative to down words (and vice versa). Similar to the RT data, this effect was strongest for semantically related targets and reversed for unrelated targets. Intriguingly, all conditions showed a bias in the congruent direction in the initial stage of the saccade. Then, at around halfway into the saccade the effect kept increasing in the semantically related condition, and reversed in the unrelated condition. These results suggest that online processing of up/down words triggers direction-specific oculomotor processes that are dynamically modulated by the semantic relation between prime words and targets.

Abstract

Gestures help speakers and listeners during communication and thinking, particularly for visual-spatial information. Speakers tend to use gestures to complement the accompanying spoken deictic constructions, such as demonstratives, when communicating spatial information (e.g., saying “The candle is here” and gesturing to the right side to express that the candle is on the speaker's right). Visual information conveyed by gestures enhances listeners’ comprehension. Whether and how listeners allocate overt visual attention to gestures in different speech contexts is mostly unknown. We asked if (a) listeners gazed at gestures more when they complement demonstratives in speech (“here”) compared to when they express redundant information to speech (e.g., “right”) and (b) gazing at gestures related to listeners’ information uptake from those gestures. We demonstrated that listeners fixated gestures more when they expressed complementary than redundant information in the accompanying speech. Moreover, overt visual attention to gestures did not predict listeners’ comprehension. These results suggest that the heightened communicative value of gestures as signaled by external cues, such as demonstratives, guides listeners’ visual attention to gestures. However, overt visual attention does not seem to be necessary to extract the cued information from the multimodal message.

Abstract

Although humans can understand speech using the auditory modality alone, in noisy environments visual speech information from the talker’s mouth can rescue otherwise unintelligible auditory speech. To investigate the neural substrates of multisensory speech perception, we compared neural activity from the human superior temporal gyrus (STG) in two datasets. One dataset consisted of direct neural recordings (electrocorticography, ECoG) from surface electrodes implanted in epilepsy patients (this dataset has been previously published). The second dataset consisted of indirect measures of neural activity using blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI). Both ECoG and fMRI participants viewed the same clear and noisy audiovisual speech stimuli and performed the same speech recognition task. Both techniques demonstrated a sharp functional boundary in the STG, spatially coincident with an anatomical boundary defined by the posterior edge of Heschl’s gyrus. Cortex on the anterior side of the boundary responded more strongly to clear audiovisual speech than to noisy audiovisual speech while cortex on the posterior side of the boundary did not. For both ECoG and fMRI measurements, the transition between the functionally distinct regions happened within 10 mm of anterior-to-posterior distance along the STG. We relate this boundary to the multisensory neural code underlying speech perception and propose that it represents an important functional division within the human speech perception network.

Abstract

Our ability to use language is multimodal and requires tight coordination between what is expressed in speech and in gesture, such as pointing or iconic gestures that convey semantic, syntactic and pragmatic information related to speakers’ messages. Interestingly, what is expressed in gesture and how it is coordinated with speech differs in speakers of different languages. This paper discusses recent findings on the development of children’s multimodal expressions taking cross-linguistic variation into account. Although some aspects of speech-gesture development show language-specificity from an early age, it might still take children until nine years of age to exhibit fully adult patterns of cross-linguistic variation. These findings reveal insights about how children coordinate different levels of representations given that their development is constrained by patterns that are specific to their languages.

Abstract

Use of language in face-to-face context is multimodal. Production and perception of speech take place in the context of visual articulators such as lips, face, or hand gestures which convey relevant information to what is expressed in speech at different levels of language. While lips convey information at the phonological level, gestures contribute to semantic, pragmatic, and syntactic information, as well as to discourse cohesion. This chapter overviews recent findings showing that speech and gesture (e.g. a drinking gesture as someone says, “Would you like a drink?”) interact during production and comprehension of language at the behavioral, cognitive, and neural levels. Implications of these findings for current psycholinguistic theories and how they can be expanded to consider the multimodal context of language processing are discussed.

Abstract

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study
long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is
nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear
correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear
source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based
connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed.
Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular
in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here,
however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large
numbers of spurious false positive connections through field spread in the vicinity of true interactions. This
fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most
importantly, beyond defining and illustrating the problem of spurious, or “ghost” interactions, we provide a
rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal
mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that
spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when
using measures that are immune to zero-lag correlations.

Abstract

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across
diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed,
Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment
based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the
retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any
age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age,
sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies
provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23
datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and
association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-
analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA
was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of
low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-
quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections
subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition
parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may
enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to
consistency and comparability among studies, and should be addressed in future investigations.

Abstract

Visual selective attention operates through top–down mechanisms of signal enhancement and suppression, mediated by a-band oscillations. The effects of such top–down signals on local processing in primary visual cortex (V1) remain poorly understood. In this work, we characterize the interplay between large-s cale interactions and local activity changes in V1 that orchestrat es selective attention, using Granger-causality and phase-amplitude coupling (PAC) analysis of EEG source signals. The task required participants to either attend to or ignore oriented gratings. Results from time-varying, directed connectivity analysis revealed frequency-specific effects of attentional selection: bottom–up g-band influences from visual areas increased rapidly in response to attended stimuli while distributed top–down a-band influences originated from parietal cortex in response to ignored stimuli. Importantly, the results revealed a critical interplay between top–down parietal signals and a–g PAC in visual areas.
Parietal a-band influences disrupted the a–g coupling in visual cortex, which in turn reduced the amount of g-band outflow from visual area s. Our results are a first demon stration of how directed interactions affect cross-frequency coupling in downstream areas depending on task demands. These findings suggest that parietal cortex realizes selective attention by disrupting cross-frequency coupling at target regions, which prevents them from propagating task-irrelevant information.