Publications

Abstract

Prediction of upcoming words facilitates language processing. Individual differences in social experience, however, might influence prediction ability by influencing input variability and representativeness. This paper explores how individual differences in social network size influence prediction and how this influence differs across linguistic levels. In Experiment 1, participants predicted likely sentence completions from several plausible endings differing in meaning or only form (e.g. work vs. job). In Experiment 2, participants’ pupil size was measured as they listened to sentences whose ending was the dominant one or deviated from it in either meaning or form. Both experiments show that people with larger social networks are better at predicting upcoming meanings but not the form they would take. The results thus show that people with different social experience process language differently, and shed light on how social dynamics interact with the structure of the linguistic level to influence learning of linguistic patterns.

Abstract

Language is a social phenomenon. The author learns, processes, and uses it in social contexts. In other words, the social environment shapes the linguistic knowledge and use of the knowledge. To a degree, this is trivial. A child exposed to Japanese will become fluent in Japanese, whereas a child exposed to only Spanish will not understand Japanese but will master the sounds, vocabulary, and grammar of Spanish. Language is a structured system. Sounds and words do not occur randomly but are characterized by regularities. Learners are sensitive to these regularities and exploit them when learning language. People differ in the sizes of their social networks. Some people tend to interact with only a few people, whereas others might interact with a wide range of people. This is reflected in people’s holiday greeting habits: some people might send cards to only a few people, whereas other would send greeting cards to more than 350 people.

Abstract

The evolution of speech and language has been a returning topic in the language sciences since the so-called “cognitive revolution.”

Abstract

This paper considers the AGL literature from a psycholinguistic perspective. It first presents a taxonomy of the experimental familiarization test procedures used, which is followed by a consideration of shortcomings and potential improvements of the empirical methodology. It then turns to reconsidering the issue of grammar learning from the point of view of acquiring constraints, instead of the traditional AGL approach in terms of acquiring sets of rewrite rules. This is, in particular, a natural way of handling long‐distance dependences. The final section addresses an underdeveloped issue in the AGL literature, namely how to detect latent hierarchical structure in AGL response patterns.

Abstract

The deep structural diversity of languages suggests that our language capacities are not based on
any single template but rather on an underlying ability and motivation for infants to acquire a
culturally transmitted system. The hypothesis is that this ability has an interactional base that has
discernable precursors in other primates. In this paper I explore a specific evolutionary route for the
most puzzling aspect of this interactional base in humans, namely the development of an empathetic
intentional stance. The route involves a generalization of mother-infant interaction patterns to all
adults via a process (‘ cuteness selection’ ) analogous to, but distinct from, RA Fisher’s runaway
sexual selection. This provides a cornerstone for the carrying capacity for language.

Abstract

This is a comprehensive description of a language spoken some 450 km offshore from the mainland of Papua New Guinea. The language is remarkable for its phonological, morphological and syntactic complexity. As the sole surviving member of its language family, and with little historical contact with surrounding languages, the language provides evidence of the kind of languages spoken in this part of the world before the Austronesian expansion.

The grammar provides detailed information on the phoneme inventory, morphology, syntax and select semantic fields. Remarkable features include a 90 phoneme inventory including unique sounds, a morphology with thousands of non-compositional portmanteau elements, complex rules for negation, and extensive ergative syntax. Unusual patterns are also found in the organization of semantic fields, for example in partonymies of the body, taxonomies of the natural world, verbal semantics and kinship terms. The combination of linguistic ‘rara’ suggest that linguistic evolution under low contact can yield baroque and unusual patterns. The volume should be of special interest to linguists, typologists, sociolinguists, anthropologists and researchers in Oceania and Melanesia.

Abstract

Zipf’s law of abbreviation, which posits a negative correlation between word frequency and length, is one of the most famous and robust cross-linguistic generalizations. At the same time, it has been shown that contextual informativity (average surprisal given previous context) is more strongly correlated with word length, although this tendency is not observed consistently, depending on several methodological choices. The present study examines a more diverse sample of languages than the previous studies (Arabic, Finnish, Hungarian, Indonesian, Russian, Spanish and Turkish). I use large web-based corpora from the Leipzig Corpora Collection to estimate word lengths in UTF-8 characters and in phonemes (for some of the languages), as well as word frequency, informativity given previous word and informativity given next word, applying different methods of bigrams processing. The results show different correlations between word length and the corpus-based measure for different languages. I argue that these differences can be explained by the properties of noun phrases in a language, most importantly, by the order of heads and modifiers and their relative morphological complexity, as well as by orthographic conventions

Abstract

We investigate the correlations between A- and P-lability for verbal arguments with other typological parameters using large, syntactically annotated corpora of online news in 28 languages. To estimate how much lability is observed in a language, we measure associations between Verbs or Verb + Noun combinations and the alternating constructions in which they occur. Our correlational analyses show that high P-lability scores correlate strongly with the following parameters: little or no case marking; weaker associations between lexemes and the grammatical roles A and P; rigid order of Subject and Object; and a high proportion of verb-medial clauses (SVO). Low P-lability correlates with the presence of case marking, stronger associations between nouns and grammatical roles, relatively flexible ordering of Subject and Object, and verb-final order. As for A-lability, it is not correlated with any other parameters. A possible reason is that A-lability is a result of more universal discourse processes, such as deprofiling of the object, and also exhibits numerous lexical and semantic idiosyncrasies. The fact that P-lability is strongly correlated with other parameters can be interpreted as evidence for a more general typology of languages, in which some tend to have highly informative morphosyntactic and lexical cues, whereas others rely predominantly on contextual environment, which is possibly due to fixed word order. We also find that P-lability is more strongly correlated with the other parameters than any of these parameters are with each other, which means that it can be a very useful typological variable.

Abstract

There is ample psycholinguistic evidence that speakers behave efficiently, using shorter and less effortful constructions when the meaning is more predictable, and longer and more effortful ones when it is less predictable. However, the Principle of No Synonymy requires that all formally distinct variants should also be functionally different. The question is how much two related constructions should overlap semantically and pragmatically in order to be used for the purposes of efficient communication. The case study focuses on want to + Infinitive and its reduced variant with wanna, which have different stylistic and sociolinguistic connotations. Bayesian mixed-effects regression modelling based on the spoken part of the British National Corpus reveals a very limited effect of efficiency: predictability increases the chances of the reduced variant only in fast speech. We conclude that efficient use of more and less effortful variants is restricted when two variants are associated with different registers or styles. This paper also pursues a methodological goal regarding missing values in speech corpora. We impute missing data based on the existing values. A comparison of regression models with and without imputed values reveals similar tendencies. This means that imputation is useful for dealing with missing values in corpora.

Abstract

The present paper discusses connectivity and proximity maps of causative constructions and combines them with different types of typological data. In the first case study, I show how one can create a connectivity map based on a parallel corpus. This allows us to solve many problems, such as incomplete descriptions, inconsistent terminology and the problem of determining the semantic nodes. The second part focuses on proximity maps based on Multidimensional Scaling and compares the most important semantic distinctions, which are inferred from a parallel corpus of film subtitles and from grammar descriptions. The results suggest that corpus-based maps of tokens are more sensitive to cultural and genre-related differences in the prominence of specific causation scenarios than maps based on constructional types, which are described in reference grammars. The grammar-based maps also reveal a less clear structure, which can be due to incomplete semantic descriptions in grammars. Therefore, each approach has its shortcomings, which researchers need to be aware of.

Abstract

Over the last few years, the number of corpora that can be used for language comparison has dramatically increased. The corpora are so diverse in their structure, size and annotation style, that a novice might not know where to start. The present paper charts this new and changing territory, providing a few landmarks, warning signs and safe paths. Although no corpora corpus at present can replace the traditional type of typological data based on language description in reference grammars, they corpora can help with diverse tasks, being particularly well suited for investigating probabilistic and gradient properties of languages and for discovering and interpreting cross-linguistic generalizations based on processing and communicative mechanisms. At the same time, the use of corpora for typological purposes has not only advantages and opportunities, but also numerous challenges. This paper also contains an empirical case study addressing two pertinent problems: the role of text types in language comparison and the problem of the word as a comparative concept.

Abstract

The present paper discusses the benefits and challenges of token-based typology, which takes into account the frequencies of words and constructions in language use. This approach makes it possible to introduce new criteria for language classification, which would be difficult or impossible to achieve with the traditional, type-based approach. This point is illustrated by several quantitative studies of word order variation, which can be measured as entropy at different levels of granularity. I argue that this variation can be explained by general functional mechanisms and pressures, which manifest themselves in language use, such as optimization of processing (including avoidance of ambiguity) and grammaticalization of predictable units occurring in chunks. The case studies are based on multilingual corpora, which have been parsed using the Universal Dependencies annotation scheme.

Abstract

Schizophrenia is a common and complex mental disorder with neuroimaging alterations. Recent neuroanatomical pattern recognition studies attempted to distinguish individuals with schizophrenia by structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). 1, 2 Applications of cutting-edge machine learning approaches in structural neuroimaging studies have revealed potential pathways to classification of schizophrenia based on regional gray matter volume (GMV) or density or cortical thickness. 3–5 Additionally, cortical folding may have high discriminatory value in correctly identifying symptom severity in schizophrenia. 6 Regional GMV and cortical thickness have also been combined in attempts to differentiate individuals with schizophrenia from healthy controls (HCs). 7 Applications of machine learning algorithms to diffusion imaging data analysis to predict individuals with first-episode schizophrenia (FES) have achieved encouraging accuracy. 8–10 White matter (WM) abnormalities in schizophrenia as estimated by DTI appear to be present in the early stage of the disorder, most likely reflecting the developmental stage of the sample of interest.

Abstract

Identifying data-driven biotypes of major depressive disorder (MDD) has promise for the clarification of diagnostic heterogeneity. However, few studies have focused on white-matter abnormalities for MDD subtyping. This study included 116 patients with MDD and 118 demographically-matched healthy controls assessed by diffusion tensor imaging and neurocognitive evaluation. Hierarchical clustering was applied to the major fiber tracts, in conjunction with tract-based spatial statistics, to reveal white-matter alterations associated with MDD. Clinical and neurocognitive differences were compared between identified subgroups and healthy controls. With fractional anisotropy extracted from 20 fiber tracts, cluster analysis revealed 3 subgroups based on the patterns of abnormalities. Patients in each subgroup versus healthy controls showed a stepwise pattern of white-matter alterations as follows: subgroup 1 (25.9% of patient sample), widespread white-matter disruption; subgroup 2 (43.1% of patient sample), intermediate and more localized abnormalities in aspects of the corpus callosum and left cingulate; and subgroup 3 (31.0% of patient sample), possible mild alterations, but no statistically significant tract disruption after controlling for family-wise error. The neurocognitive impairment in each subgroup accompanied the white-matter alterations: subgroup 1, deficits in sustained attention and delayed memory; subgroup 2, dysfunction in delayed memory; and subgroup 3, no significant deficits. Three subtypes of white-matter abnormality exist in individuals with major depression, those having widespread abnormalities suffering more neurocognitive impairments, which may provide evidence for parsing the heterogeneity of the disorder and help optimize type-specific treatment approaches.

Abstract

Response tokens (also known as backchannels, continuers, or feedback) are a frequent feature of human interaction, where they serve to display understanding and streamline turn-taking. We propose a bottom-up method to study responsive behaviour across 16 languages (8 language families). We use sequential context and recurrence of turns formats to identify candidate response tokens in a language-agnostic way across diverse conversational corpora. We then use UMAP clustering directly on speech signals to represent structure and variation. We find that (i) written orthographic annotations underrepresent the attested variation, (ii) distinctions between formats can be gradient rather than discrete, (iii) most languages appear to make available a broad distinction between a minimal nasal format `mm' and a fuller `yeah’-like format. Charting this aspect of human interaction contributes to our understanding of interactional infrastructure across languages and can inform the design of speech technologies.

Abstract

We present an analysis pipeline and best practice guidelines for building and curating corpora of everyday conversation in diverse languages. Surveying language documentation corpora and other resources that cover 67 languages and varieties from 28 phyla, we describe the compilation and curation process, specify minimal properties of a unified format for interactional data, and develop methods for quality control that take into account turn-taking and timing. Two case studies show the broad utility of conversational data for (i) charting human interactional infrastructure and (ii) tracing challenges and opportunities for current ASR solutions. Linguistically diverse conversational corpora can provide new insights for the language sciences and stronger empirical foundations for language technology.

Abstract

Prediction is an important part of language processing. An open question is to what extent people predict language in challenging circumstances. Here we tested the limits of prediction by asking bilingual Dutch native speakers to interpret Dutch sentences into their English counterparts. In two visual world experiments, we recorded participants’ eye movements to co-present visual objects while they engaged in interpreting tasks (consecutive and simultaneous interpreting). Most participants showed anticipatory eye movements to semantically-related upcoming target words in their L1 source language during both consecutive and simultaneous interpretation. A quarter of participants during simultaneous interpretation however did not move their eyes, an extremely unusual participant behaviour in visual world studies. Overall, the findings suggest that most people predict in the source language under challenging interpreting situations. Further work is required to understand the causes of the absence of (anticipatory) eye movements during simultaneous interpretation in a substantial subset of individuals.

Abstract

As many distributional learning (DL) studies have shown, adult listeners can achieve discrimination of a difficult non-native contrast after a short repetitive exposure to tokens falling at the extremes of that contrast. Such studies have shown using behavioural methods that a short distributional training can induce perceptual learning of vowel and consonant contrasts. However, much less is known about the neurological correlates of DL, and few studies have examined non-native lexical tone contrasts. Here, Australian-English speakers underwent DL training on a Mandarin tone contrast using behavioural (discrimination, identification) and neural (oddball-EEG) tasks, with listeners hearing either a bimodal or a unimodal distribution. Behavioural results show that listeners learned to discriminate tones after both unimodal and bimodal training; while EEG responses revealed more learning for listeners exposed to the bimodal distribution. Thus, perceptual learning through exposure to brief sound distributions (a) extends to non-native tonal contrasts, and (b) is sensitive to task, phonetic distance, and acoustic cue-weighting. Our findings have implications for models of how auditory and phonetic constraints influence speech learning.

Abstract

Verb learning is important for young children. While most
previous research has focused on linguistic and conceptual
challenges in early verb learning (e.g. Gentner, 1982, 2006),
the present paper examined early verb learning at the
attentional level and quantified the input for early verb learning
by measuring verb-action co-occurrence statistics in parent-
child interaction from the learner’s perspective. To do so, we
used head-mounted eye tracking to record fine-grained
multimodal behaviors during parent-infant joint play, and
analyzed parent speech, parent and infant action, and infant
attention at the moments when parents produced verb labels.
Our results show great variability across different action verbs,
in terms of frequency of verb utterances, frequency of
corresponding actions related to verb meanings, and infants’
attention to verbs and actions, which provide new insights on
why some verbs are harder to learn than others.

Abstract

Recurrent processing is a crucial feature in human visual processing supporting perceptual grouping, figure-ground segmentation, and recognition under challenging conditions. There is a clear need to incorporate recurrent processing in deep convolutional neural networks (DCNNs) but the computations underlying recurrent processing remain unclear. In this paper, we tested a form of recurrence in deep residual networks (ResNets) to capture recurrent processing signals in the human brain. Though ResNets are feedforward networks, they approximate an excitatory additive form of recurrence. Essentially, this form of recurrence consists of repeating excitatory activations in response to a static stimulus. Here, we used ResNets of varying depths (reflecting varying levels of recurrent processing) to explain electroencephalography (EEG) activity within a visual masking paradigm. Sixty-two humans and fifty artificial agents (10 ResNet models of depths - 4, 6, 10, 18 and 34) completed an object categorization task. We show that deeper networks (ResNet-10, 18 and 34) explained more variance in brain activity compared to shallower networks (ResNet-4 and 6). Furthermore, all ResNets captured differences in brain activity between unmasked and masked trials, with differences starting at ∼98ms (from stimulus onset). These early differences indicated that EEG activity reflected ‘pure’ feedforward signals only briefly (up to ∼98ms). After ∼98ms, deeper networks showed a significant increase in explained variance which peaks at ∼200ms, but only within unmasked trials, not masked trials. In summary, we provided clear evidence that excitatory additive recurrent processing in ResNets captures some of the recurrent processing in humans.

Abstract

Typological comparisons have revealed that signers can use manual elements and/or a non-manual marker to express standard negation, but little is known about how such systematic marking emerges from its gestural counterparts as a new sign language arises. We analyzed 1.73 h of spontaneous language data, featuring six deaf native signers from generations III-V of the sign language isolate Kata Kolok (Bali). These data show that Kata Kolok cannot be classified as a manual dominant or non-manual dominant sign language since both the manual negative sign and a side-to-side headshake are used extensively. Moreover, the intergenerational comparisons indicate a considerable increase in the use of headshake spreading for generation V which is unlikely to have resulted from contact with Indonesian Sign Language varieties. We also attest a specialized negative existential marker, namely, tongue protrusion, which does not appear in co-speech gesture in the surrounding community. We conclude that Kata Kolok is uniquely placed in the typological landscape of sign language negation, and that grammaticalization theory is essential to a deeper understanding of the emergence of grammatical structure from gesture.

Abstract

Endophoric demonstratives such as this and that are among the most frequently used words in written texts. Nevertheless, it remains unclear how exactly they should be subdivided and classified in terms of their different types of use. Here, we develop a new taxonomy of endophoric demonstratives based on a large-scale corpus including three written genres: news items, encyclopedic texts, and book reviews. The taxonomy enables analysts to reliably code endophoric demonstratives based on objectively applicable criteria, while at the same time making them aware of many subtle borderline cases. We consider the taxonomy as a theoretical foundation for future theoretical and empirical work into endophoric demonstratives, and as an analytical tool allowing researchers to unify and compare the results of studies on endophoric demonstratives coming from different genres and languages.

Abstract

Continuous Bag of Words (CBOW) is a powerful text embedding method. Due to its strong capabilities to encode word content, CBOW embeddings perform well on a wide range of downstream tasks while being efficient to compute. However, CBOW is not capable of capturing the word order. The reason is that the computation of CBOW's word embeddings is commutative, i.e., embeddings of XYZ and ZYX are the same. In order to address this shortcoming, we propose a
learning algorithm for the Continuous Matrix Space Model, which we call Continual Multiplication of Words (CMOW). Our algorithm is an adaptation of word2vec, so that it can be trained on large quantities of unlabeled text. We empirically show that CMOW better captures linguistic properties, but it is inferior to CBOW in memorizing word content. Motivated by these findings, we propose a hybrid model that combines the strengths of CBOW and CMOW. Our results show that the hybrid CBOW-CMOW-model retains CBOW's strong ability to memorize word content while at the same time substantially improving its ability to encode other linguistic information by 8%. As a result, the hybrid also performs better on 8 out of 11 supervised downstream tasks with an average improvement of 1.2%.

Abstract

The existence of language-specific abstract sound-structure units (such as the phoneme) is largely uncontroversial in phonology. However, whether the brain performs abstractions comparable to those assumed in phonology has been difficult to ascertain. Using intracranial electroencephalography (EEG) recorded during a passive listening task, this study investigates the representation of phonological units in the brain and the relationship between those units, auditory sensory input, and higher levels of language organization, namely morphology. Leveraging the phonological neutralization of coronal stops to tap in English, this study provides evidence of a dissociation between acoustic similarity and phonemic identity in the neural response to speech. Moreover, leveraging morphophonological alternations of the regular plural and past tense, this study further demonstrates early (<500ms) evidence of dissociation between phonological form and morphological exponence. Together these results highlight the central nature of language-specific knowledge in sublexical language processing and improve our understanding of the ways language-specific knowledge structures and organizes speech perception in the brain.

Abstract

Background

Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs).
Methods

A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms.
Results

GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program.
Conclusions

Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

Abstract

When two people read the same story, they might both end up liking it very much. However, this does not necessarily mean that their reasons for liking it were identical. We therefore ask what factors contribute to “liking” a story, and—most importantly—how people vary in this respect. We found that readers like stories because they find them interesting, amusing, suspenseful and/or beautiful. However, the degree to which these components of appreciation were related to how much readers liked stories differed between individuals. Interestingly, the individual slopes of the relationships between many of the components and liking were (positively or negatively) correlated. This indicated, for instance, that individuals displaying a relatively strong relationship between interest and liking, generally display a relatively weak relationship between sadness and liking. The individual differences in the strengths of the relationships between the components and liking were not related to individual differences in expertize, a characteristic strongly associated with aesthetic appreciation of visual art. Our work illustrates that it is important to take into consideration the fact that individuals differ in how they arrive at their evaluation of literary stories, and that it is possible to quantify these differences in empirical experiments. Our work suggests that future research should be careful about “overfitting” theories of aesthetic appreciation to an “idealized reader,” but rather take into consideration variations across individuals in the reason for liking a particular story.

Abstract

People engage in simulation when reading literary narratives. In this study, we tried to pinpoint how different kinds of simulation (perceptual and motor simulation, mentalising) affect reading behaviour. Eye-tracking (gaze durations, regression probability) and questionnaire data were collected from 102 participants, who read three literary short stories. In a pre-test, 90 additional participants indicated which parts of the stories were high in one of the three kinds of simulation-eliciting content. The results show that motor simulation reduces gaze duration (faster reading), whereas perceptual simulation and mentalising increase gaze duration (slower reading). Individual differences in the effect of simulation on gaze duration were found, which were related to individual differences in aspects of story world absorption and story appreciation. These findings suggest fundamental differences between different kinds of simulation and confirm the role of simulation in absorption and appreciation.

Abstract

Studies have claimed that blind people’s spatial representations are different from sighted people, and blind people display superior auditory processing. Due to the nature of auditory and haptic information, it has been proposed that blind people have spatial representations that are more sequential than sighted people. Even the temporary loss of sight—such as through blindfolding—can affect spatial representations, but not much research has been done on this topic. We compared blindfolded and sighted people’s linguistic spatial expressions and non-linguistic localization accuracy to test how blindfolding affects the representation of path in auditory motion events. We found that blindfolded people were as good as sighted people when localizing simple sounds, but they outperformed sighted people when localizing auditory motion events. Blindfolded people’s path related speech also included more sequential, and less holistic elements. Our results indicate that even temporary loss of sight influences spatial representations of auditory motion events

Abstract

Prediction of upcoming input is thought to be a main characteristic of language processing (e.g. Altmann & Mirkovic, 2009; Dell & Chang, 2014; Federmeier, 2007; Ferreira & Chantavarin, 2018; Pickering & Gambi, 2018; Hale, 2001; Hickok, 2012; Huettig 2015; Kuperberg & Jaeger, 2016; Levy, 2008; Norris, McQueen, & Cutler, 2016; Pickering & Garrod, 2013; Van Petten & Luka, 2012). One of the main pillars of experimental support for this notion comes from studies that have attempted to measure electrophysiological markers of prediction when participants read or listened to sentences ending in highly predictable words. The N400, a negative-going and centro-parietally distributed component of the ERP occurring approximately 400ms after (target) word onset, has been frequently interpreted as indexing prediction of the word (or the semantic representations and/or the phonological form of the predicted word, see Kutas & Federmeier, 2011; Nieuwland, 2019; Van Petten & Luka, 2012; for review). A major difficulty for interpreting N400 effects in language processing however is that it has been difficult to establish whether N400 target word modulations conclusively reflect prediction rather than (at least partly) ease of integration. In the present exploratory study, we attempted to distinguish lexical prediction (i.e. ‘top-down’ activation) from lexical integration (i.e. ‘bottom-up’ activation) accounts of ERP N400 modulations in language processing.

Abstract

Speech produced in noise (Lombard speech) is more intelligible than speech produced in quiet (plain speech). Previous research on the Lombard intelligibility benefit focused almost entirely on how native speakers produce and perceive Lombard speech. In this study, we investigate the size of the Lombard intelligibility benefit of both native (American-English) and non-native (native Dutch) English for native and non-native listeners (Dutch and Spanish). We used a glimpsing metric to measure the energetic masking potential of speech, which predicted that both native and non-native Lombard speech could withstand greater amounts of masking to a similar extent, compared to plain speech. In an intelligibility experiment, native English, Spanish, and Dutch listeners listened to the same words, mixed with noise. While the non-native listeners appeared to benefit more from Lombard speech than the native listeners did, each listener group experienced a similar benefit for native and non-native Lombard speech. Energetic masking, as captured by the glimpsing metric, only accounted for part of the Lombard benefit, indicating that the Lombard intelligibility benefit does not only result from a shift in spectral distribution. Despite subtle native language influences on non-native Lombard speech, both native and non-native speech provides a Lombard benefit.

Abstract

Lombard speech, speech produced in noise, is acoustically different from speech produced in quiet (plain speech) in several ways, including having a higher and wider F0 range (pitch). Extensive research on native Lombard speech does not consider that non-natives experience a higher cognitive load while producing
speech and that the native language may influence the non-native speech. We investigated pitch range in plain and Lombard speech in native and non-natives.
Dutch and American-English speakers read contrastive question-answer pairs in quiet and in noise in English, while the Dutch also read Dutch sentence pairs. We found that Lombard speech is characterized by a wider pitch range than plain speech, for all speakers (native English, non-native English, and native Dutch).
This shows that non-natives also widen their pitch range in Lombard speech. In sentences with early-focus, we see the same increase in pitch range when going from plain to Lombard speech in native and non-native English, but a smaller increase in native Dutch. In sentences with late-focus, we see the biggest increase for the native English, followed by non-native English and then native Dutch. Together these results indicate an effect of the native language on non-native Lombard speech.

Abstract

Lombard speech, speech produced in noise, is
typically produced with a higher fundamental
frequency (F0, pitch) compared to speech in quiet. This paper examined the potential differences in native and non-native Lombard speech by analyzing median pitch in sentences with early- or late-focus produced in quiet and noise. We found an increase in pitch in late-focus sentences in noise for Dutch speakers in both English and Dutch, and for American-English speakers in English. These results
show that non-native speakers produce Lombard speech, despite their higher cognitive load. For the early-focus sentences, we found a difference between the Dutch and the American-English speakers. Whereas the Dutch showed an increased F0 in noise
in English and Dutch, the American-English speakers did not in English. Together, these results suggest that some acoustic characteristics of Lombard speech, such as pitch, may be language-specific, potentially
resulting in the native language influencing the non-native Lombard speech.

Abstract

Human thought and language have extraordinary expressive power because meaningful parts can be assembled into more complex semantic structures. This partly underlies our ability to compose meanings into endlessly novel configurations, and sets us apart from other species and current computing devices. Crucially, human behaviour, including language use and linguistic data, indicates that composing parts into complex structures does not threaten the existence of constituent parts as independent units in the system: parts and wholes exist simultaneously yet independently from one another in the mind and brain. This independence is evident in human behaviour, but it seems at odds with what is known about the brain's exquisite sensitivity to statistical patterns: everyday language use is productive and expressive precisely because it can go beyond statistical regularities. Formal theories in philosophy and linguistics explain this fact by assuming that language and thought are compositional: systems of representations that separate a variable (or role) from its values (fillers), such that the meaning of a complex expression is a function of the values assigned to the variables. The debate on whether and how compositional systems could be implemented in minds, brains and machines remains vigorous. However, it has not yet resulted in mechanistic models of semantic composition: how, then, are the constituents of thoughts and sentences put and held together? We review and discuss current efforts at understanding this problem, and we chart possible routes for future research.

Abstract

Neither neurobiological nor process models of meaning composition specify the operator through which constituent parts are bound together into compositional structures. In this paper, we argue that a neurophysiological computation system cannot achieve the compositionality exhibited in human thought and language if it were to rely on a multiplicative operator to perform binding, as the tensor product (TP)-based systems that have been widely adopted in cognitive science, neuroscience and artificial intelligence do. We show via simulation and two behavioural experiments that TPs violate variable-value independence, but human behaviour does not. Specifically, TPs fail to capture that in the statements fuzzy cactus and fuzzy penguin, both cactus and penguin are predicated by fuzzy(x) and belong to the set of fuzzy things, rendering these arguments similar to each other. Consistent with that thesis, people judged arguments that shared the same role to be similar, even when those arguments themselves (e.g., cacti and penguins) were judged to be dissimilar when in isolation. By contrast, the similarity of the TPs representing fuzzy(cactus) and fuzzy(penguin) was determined by the similarity of the arguments, which in this case approaches zero. Based on these results, we argue that neural systems that use TPs for binding cannot approximate how the human mind and brain represent compositional information during processing. We describe a contrasting binding mechanism that any physiological or artificial neural system could use to maintain independence between a role and its argument, a prerequisite for compositionality and, thus, for instantiating the expressive power of human thought and language in a neural system.

Abstract

Humans learn to represent complex structures (e.g. natural language, music, mathematics) from experience with their environments. Often such structures are latent, hidden, or not encoded in statistics about sensory representations alone. Accounts of human cognition have long emphasized the importance of structured representations, yet the majority of contemporary neural networks do not learn structure from experience. Here, we describe one way that structured, functionally symbolic representations can be instantiated in an artificial neural network. Then, we describe how such latent structures (viz. predicates) can be learned from experience with unstructured data. Our approach exploits two principles from psychology and neuroscience: comparison of representations, and the naturally occurring dynamic properties of distributed computing across neuronal assemblies (viz. neural oscillations). We discuss how the ability to learn predicates from experience, to represent information compositionally, and to extrapolate knowledge to unseen data is core to understanding and modeling the most complex human behaviors (e.g. relational reasoning, analogy, language processing, game play).

Abstract

Active communication between researchers and society is necessary for the scientific community’s involvement in developing sciencebased
policies. This need is recognized by governmental and funding agencies that compel scientists to increase their public engagement
and disseminate research findings in an accessible fashion. Storytelling techniques can help convey science by engaging people’s imagination
and emotions. Yet, many researchers are uncertain about how to approach scientific storytelling, or feel they lack the tools to
undertake it. Here we explore some of the techniques intrinsic to crafting scientific narratives, as well as the reasons why scientific
storytellingmaybe an optimal way of communicating research to nonspecialists.Wealso point out current communication gaps between
science and society, particularly in the context of neurodiverse audiences and those that include neurological and psychiatric patients.
Present shortcomings may turn into areas of synergy with the potential to link neuroscience education, research, and advocacy

Abstract

Listeners are known to track statistical regularities in speech. Yet, which temporal cues
are encoded is unclear. This study tested effects of talker-specific habitual speech rate
and talker-independent average speech rate (heard over a longer period of time) on
the perception of the temporal Dutch vowel contrast /A/-/a:/. First, Experiment 1
replicated that slow local (surrounding) speech contexts induce fewer long /a:/
responses than faster contexts. Experiment 2 tested effects of long-term habitual
speech rate. One high-rate group listened to ambiguous vowels embedded in `neutral'
speech from talker A, intermixed with speech from fast talker B. Another low-rate group
listened to the same `neutral' speech from talker A, but to talker B being slow.
Between-group comparison of the `neutral' trials showed that the high-rate group
demonstrated a lower proportion of /a:/ responses, indicating that talker A's habitual
speech rate sounded slower when B was faster. In Experiment 3, both talkers
produced speech at both rates, removing the different habitual speech rates of talker A
and B, while maintaining the average rate differing between groups. This time no
global rate effect was observed. Taken together, the present experiments show that a
talker's habitual rate is encoded relative to the habitual rate of another talker, carrying
implications for episodic and constraint-based models of speech perception.

Abstract

Speech can be produced at different rates. Listeners take this rate variation into account by normalizing vowel duration for contextual speech rate: An ambiguous Dutch word /m?t/ is perceived as short /mAt/ when embedded in a slow context, but long /ma:t/ in a fast context. Whilst some have argued that this rate normalization involves low-level automatic perceptual processing, there is also evidence that it arises at higher-level cognitive processing stages, such as decision making. Prior research on rate-dependent speech perception has only used explicit recognition tasks to investigate the phenomenon, involving both perceptual processing and decision making. This study tested whether speech rate normalization can be observed without explicit decision making, using a cross-modal repetition priming paradigm. Results show that a fast precursor sentence makes an embedded ambiguous prime (/m?t/) sound (implicitly) more /a:/-like, facilitating lexical access to the long target word "maat" in a (explicit) lexical decision task. This result suggests that rate normalization is automatic, taking place even in the absence of an explicit recognition task. Thus, rate normalization is placed within the realm of everyday spoken conversation, where explicit categorization of ambiguous sounds is rare.

Abstract

In the following self-paced reading study, we assess the cognitive realism of six widely used corpus-derived measures of association strength between words (collocated modifier–noun combinations like vast majority): MI, MI3, Dice coefficient, T-score, Z-score, and log-likelihood. The ability of these collocation metrics to predict reading times is tested against predictors of lexical processing cost that are widely established in the psycholinguistic and usage-based literature, respectively: forward/backward transition probability and bigram frequency. In addition, the experiment includes the treatment variable of task: it is split into two blocks which only differ in the format of interleaved comprehension questions (multiple choice vs. typed free response). Results show that the traditional corpus-linguistic metrics are outperformed by both backward transition probability and bigram frequency. Moreover, the multiple-choice condition elicits faster overall reading times than the typed condition, and the two winning metrics show stronger facilitation on the critical word (i.e. the noun in the bigrams) in the multiple-choice condition. In the typed condition, we find an effect that is weaker and, in the case of bigram frequency, longer lasting, continuing into the first spillover word. We argue that insufficient attention to task effects might have obscured the cognitive correlates of association scores in earlier research.

Abstract

Scientists who study the brain try to understand how it performs everyday behaviors like language, memory, and emotion. Scientists learn a lot by studying how these behaviors change when the brain is damaged. Over the past 200 years, they have made many discoveries by studying individuals with brain damage. For example, one patient could not form sentences after damaging a specific area of his brain. The scientist who studied him concluded that the damaged brain area was important for producing speech. This approach is called the lesion method, and it has taught us a lot about the brain. In this article, we introduce five patients throughout history who forever changed our understanding of the brain. We describe how researchers use these early discoveries to ask new questions about the brain, and we conclude by discussing how the lesion method is used today.

Abstract

Poor recognition of other-race faces is ubiquitous around the world. We resolve a longstanding contradiction in the literature concerning whether interracial social contact improves the other-race effect. For the first time, we measure the age at which contact was experienced. taking advantage of
unusual demographics allowing dissociation of childhood from adult contact, results show sufficient childhood contact eliminated poor other-race recognition altogether (confirming inter-country adoption
studies). Critically, however, the developmental window for easy acquisition of other-race faces closed by approximately 12 years of age and social contact as an adult — even over several years and involving many other-race friends — produced no improvement. Theoretically, this pattern of developmental change in plasticity mirrors that found in language, suggesting a shared origin grounded in the
functional importance of both skills to social communication. Practically, results imply that, where parents wish to ensure their offspring develop the perceptual skills needed to recognise other-race people easily, childhood experience should be encouraged: just as an English-speaking person who moves to France as a child (but not an adult) can easily become a native speaker of French, we can easily
become “native recognisers” of other-race faces via natural social exposure obtained in childhood, but not later

Abstract

Language is a unique trait of the human species, of which the genetic architecture remains largely unknown. Through language disorders studies, many candidate genes were identified. However, such complex and multifactorial trait is unlikely to be driven by only few genes and case-control studies, suffering from a lack of power, struggle to uncover significant variants. In parallel, neuroimaging has significantly contributed to the understanding of structural and functional aspects of language in the human brain and the recent availability of large scale cohorts like UK Biobank have made possible to study language via image-derived endophenotypes in the general population. Because of its strong relationship with task-based fMRI (tbfMRI) activations and its easiness of acquisition, resting-state functional MRI (rsfMRI) have been more popularised, making it a good surrogate of functional neuronal processes. Taking advantage of such a synergistic system by aggregating effects across spatially distributed traits, we performed a multivariate genome-wide association study (mvGWAS) between genetic variations and resting-state functional connectivity (FC) of classical brain language areas in the inferior frontal (pars opercularis, triangularis and orbitalis), temporal and inferior parietal lobes (angular and supramarginal gyri), in 32,186 participants from UK Biobank. Twenty genomic loci were found associated with language FCs, out of which three were replicated in an independent replication sample. A locus in 3p11.1, regulating EPHA3 gene expression, is found associated with FCs of the semantic component of the language network, while a locus in 15q14, regulating THBS1 gene expression is found associated with FCs of the perceptual-motor language processing, bringing novel insights into the neurobiology of language.

Abstract

Background

While it is well established that second language (L2) learning success changes with age and across individuals, the underlying neural mechanisms responsible for this developmental shift and these individual differences are largely unknown. We will study the behavioral and neural factors that subserve new grammar and word learning in a large cross-sectional developmental sample. This study falls under the NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Dutch Research Council]) Language in Interaction consortium (website: https://www.languageininteraction.nl/).
Methods

We will sample 360 healthy individuals across a broad age range between 8 and 25 years. In this paper, we describe the study design and protocol, which involves multiple study visits covering a comprehensive behavioral battery and extensive magnetic resonance imaging (MRI) protocols. On the basis of these measures, we will create behavioral and neural fingerprints that capture age-based and individual variability in new language learning. The behavioral fingerprint will be based on first and second language proficiency, memory systems, and executive functioning. We will map the neural fingerprint for each participant using the following MRI modalities: T1‐weighted, diffusion-weighted, resting-state functional MRI, and multiple functional-MRI paradigms. With respect to the functional MRI measures, half of the sample will learn grammatical features and half will learn words of a new language. Combining all individual fingerprints allows us to explore the neural maturation effects on grammar and word learning.
Discussion

This will be one of the largest neuroimaging studies to date that investigates the developmental shift in L2 learning covering preadolescence to adulthood. Our comprehensive approach of combining behavioral and neuroimaging data will contribute to the understanding of the mechanisms influencing this developmental shift and individual differences in new language learning. We aim to answer: (I) do these fingerprints differ according to age and can these explain the age-related differences observed in new language learning? And (II) which aspects of the behavioral and neural fingerprints explain individual differences (across and within ages) in grammar and word learning? The results of this study provide a unique opportunity to understand how the development of brain structure and function influence new language learning success.

Abstract

During speech processing, neural activity in non-autistic adults and infants tracks the speech envelope. Recent research in adults indicates that this neural tracking relates to linguistic knowledge and may be reduced in autism. Such reduced tracking, if present already in infancy, could impede language development. In the current study, we focused on children with a family history of autism, who often show a delay in first language acquisition. We investigated whether differences in tracking of sung nursery rhymes during infancy relate to language development and autism symptoms in childhood. We assessed speech-brain coherence at either 10 or 14 months of age in a total of 22 infants with high likelihood of autism due to family history and 19 infants without family history of autism. We analyzed the relationship between speech-brain coherence in these infants and their vocabulary at 24 months as well as autism symptoms at 36 months. Our results showed significant speech-brain coherence in the 10- and 14-month-old infants. We found no evidence for a relationship between speech-brain coherence and later autism symptoms. Importantly, speech-brain coherence in the stressed syllable rate (1–3 Hz) predicted later vocabulary. Follow-up analyses showed evidence for a relationship between tracking and vocabulary only in 10-month-olds but not 14-month-olds and indicated possible differences between the likelihood groups. Thus, early tracking of sung nursery rhymes is related to language development in childhood.

Abstract

Humans learn language by interaction with their environment and listening to other humans. It should also be possible for computational models to learn language directly from speech but so far most approaches require text. We improve on existing neural network approaches to create visually grounded embeddings for spoken utterances. Using a combination of a multi-layer GRU, importance sampling, cyclic learning rates, ensembling and vectorial self-attention our results show a remarkable increase in image-caption retrieval performance over previous work. Furthermore, we investigate which layers in the model learn to recognise words in the input. We find that deeper network layers are better at encoding word presence, although the final layer has slightly lower performance. This shows that our visually grounded sentence encoder learns to recognise words from the input even though it is not explicitly trained for word recognition.

Abstract

Current approaches to learning semantic representations of sentences often use prior word-level knowledge. The current study aims to leverage visual information in order to capture sentence level semantics without the need for word embeddings. We use a multimodal sentence encoder trained on a corpus of images with matching text captions to produce visually grounded sentence embeddings. Deep Neural Networks are trained to map the two modalities to a common embedding space such that for an image the corresponding caption can be retrieved and vice versa. We show that our model achieves results comparable to the current state of the art on two popular image-caption retrieval benchmark datasets: Microsoft Common Objects in Context (MSCOCO) and Flickr8k. We evaluate the semantic content of the resulting sentence embeddings using the data from the Semantic Textual Similarity (STS) benchmark task and show that the multimodal embeddings correlate well with human semantic similarity judgements. The system achieves state-of-the-art results on several of these benchmarks, which shows that a system trained solely on multimodal data, without assuming any word representations, is able to capture sentence level semantics. Importantly, this result shows that we do not need prior knowledge of lexical level semantics in order to model sentence level semantics. These findings demonstrate the importance of visual information in semantics.

Abstract

Distributional semantic models capture word-level meaning that is useful in many natural language processing tasks and have even been shown to capture cognitive aspects of word meaning. The majority of these models are purely text based, even though the human sensory experience is much richer. In this paper we create visually grounded word embeddings by combining English text and images and compare them to popular text-based methods, to see if visual information allows our model to better capture cognitive aspects of word meaning. Our analysis shows that visually grounded embedding similarities are more predictive of the human reaction times in a large priming experiment than the purely text-based embeddings. The visually grounded embeddings also correlate well with human word similarity ratings.Importantly, in both experiments we show that he grounded embeddings account for a unique portion of explained variance, even when we include text-based embeddings trained on huge corpora. This shows that visual grounding allows our model to capture information that cannot be extracted using text as the only source of information.

Abstract

Thirty years ago, Pim Levelt published Speaking. During the 10th International Workshop on Language Production held at the Max Planck Institute for Psycholinguistics in Nijmegen in July 2018, researchers reflected on the impact of the book in the field, developments since its publication, and current research trends. The contributions in this Special Issue are closely related to the presentations given at the workshop. In this editorial, we sketch the research agenda set by Speaking, review how different aspects of this agenda are taken up in the papers in this volume and outline directions for further research.

Abstract

The field of second language acquisition (SLA) is by nature of its subject a highly interdisciplinary area of research. Learning a (foreign) language, for example, involves encoding new words, consolidating and committing them to long-term memory, and later retrieving them. All of these processes have direct parallels in the domain of human memory and have been thoroughly studied by researchers in that field. Yet, despite these clear links, the two fields have largely developed in parallel and in isolation from one another. The present paper aims to promote more cross-talk between SLA and memory science. We focus on foreign language (FL) attrition as an example of a research topic in SLA where the parallels with memory science are especially apparent. We discuss evidence that suggests that competition between languages is one of the mechanisms of FL attrition, paralleling the interference process thought to underlie forgetting in other domains of human memory. Backed up by concrete suggestions, we advocate the use of paradigms from the memory literature to study these interference effects in the language domain. In doing so, we hope to facilitate future cross-talk between the two fields, and to further our understanding of FL attrition as a memory phenomenon.

Abstract

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

Abstract

In everyday life, we actively engage in different activities from a first-person perspective. However, experimental psychological research in the field of event perception is often limited to relatively passive, third-person computer-based paradigms. In the present study, we tested the feasibility of using immersive virtual reality in combination with eye tracking with participants in active motion. Behavioral research has shown that speakers of aspectual and non-aspectual languages attend to goals (endpoints) in motion events differently, with speakers of non-aspectual languages showing relatively more attention to goals (endpoint bias). In the current study, native speakers of German (non-aspectual) and English (aspectual) walked on a treadmill across 3-D terrains in VR, while their eye gaze was continuously tracked. Participants encountered landmark objects on the side of the road, and potential endpoint objects at the end of it. Using growth curve analysis to analyze fixation patterns over time, we found no differences in eye gaze behavior between German and English speakers. This absence of cross-linguistic differences was also observed in behavioral tasks with the same participants. Methodologically, based on the quality of the data, we conclude that our dynamic eye-tracking setup can be reliably used to study what people look at while moving through rich and dynamic environments that resemble the real world.

Abstract

Grammatically masculine role-nouns (e.g., Studenten-masc.‘students’) can refer to men and women, but may favor an interpretation where only men are considered the referent. If true, this has implications for a society aiming to achieve equal representation in the workplace since, for example, job adverts use such role descriptions. To investigate the interpretation of role-nouns, the present ERP study assessed grammatical gender processing in German. Twenty participants read sentences where a role-noun (masculine or feminine) introduced a group of people, followed by a congruent (masculine–men, feminine–women) or incongruent (masculine–women, feminine–men) continuation. Both for feminine-men and masculine-women continuations a P600 (500 to 800 ms) was observed; another positivity was already present from 300 to 500 ms for feminine-men continuations, but critically not for masculine-women continuations. The results imply a male-biased rather than gender-neutral interpretation of the masculine—despite widespread usage of the masculine as a gender-neutral form—suggesting masculine forms are inadequate for representing genders equally.

Abstract

Gaze cues play an important role in human communication and are used to coordinate turn-taking and joint attention, as well as to regulate intimacy. In order to have fluent conversations with people, social robots need to exhibit humanlike gaze behavior. Previous Gaze Control Systems (GCS) in HRI have automated robot gaze using data-driven or heuristic approaches. However, these systems tend to be mainly reactive in nature. Planning the robot gaze ahead of time could help in achieving more realistic gaze behavior and better eye-head coordination. In this paper, we propose and implement a novel planning-based GCS. We evaluate our system in a comparative within-subjects user study (N=26) between a reactive system and our proposed system. The results show that the users preferred the proposed system and that it was significantly more interpretable and better at regulating intimacy.

Abstract

The anterior lordosis of the cervical spine is thought
to contribute to pitch (fo) production by influencing
cricoid rotation as a function of larynx height. This
study examines the matter of inter-individual
variation in cervical spine shape and whether this has
an influence on how fo is produced along increasing
or decreasing scales, using the ArtiVarK dataset,
which contains real-time MRI pitch production data.
We find that the cervical spine actively participates in
fo production, but the amount of displacement
depends on individual shape. In general, anterior
spine motion (tending toward cervical lordosis)
occurs for low fo, while posterior movement (tending
towards cervical kyphosis) occurs for high fo.

Abstract

Autosomal recessive Achromatopsia (ACHM) is a rare inherited disorder associated with dysfunctional cone photoreceptors resulting in a congenital absence of cone input to visual cortex. This might lead to distinct changes in cortical architecture with a negative impact on the success of gene augmentation therapies. To investigate the status of the visual cortex in these patients, we performed a multi-centre study focusing on the cortical structure of regions that normally receive predominantly cone input. Using high-resolution T1-weighted MRI scans and surface-based morphometry, we compared cortical thickness, surface area and grey matter volume in foveal, parafoveal and paracentral representations of primary visual cortex in 15 individuals with ACHM and 42 normally sighted, healthy controls (HC). In ACHM, surface area was reduced in all tested representations, while thickening of the cortex was found highly localized to the most central representation. These results were comparable to more widespread changes in brain structure reported in congenitally blind individuals, suggesting similar developmental processes, i.e., irrespective of the underlying cause and extent of vision loss. The cortical differences we report here could limit the success of treatment of ACHM in adulthood. Interventions earlier in life when cortical structure is not different from normal would likely offer better visual outcomes for those with ACHM.

Abstract

The sound of words has been shown to relate to the meaning that the words denote, an effect that extends beyond morphological properties of the word. Studies of these sound-symbolic relations have described this iconicity in terms of individual phonemes, or alternatively due to acoustic properties (expressed in phonological features) relating to meaning. In this study, we investigated whether individual phonemes or phoneme features best accounted for iconicity effects. We tested 92 participants’ judgements about the appropriateness of 320 nonwords presented in written form, relating to 8 different semantic attributes. For all 8 attributes, individual phonemes fitted participants’ responses better than general phoneme features. These results challenge claims that sound-symbolic effects for visually presented words can access broad, cross-modal associations between sound and meaning, instead the results indicate the operation of individual phoneme to meaning relations. Whether similar effects are found for nonwords presented auditorially remains an open question.

Abstract

Languages change due to social, cultural, and cognitive influences. In this paper, we provide an assessment of these cognitive influences on diachronic change in the vocabulary. Previously, tests of stability and change of vocabulary items have been conducted on small sets of words where diachronic change is imputed from cladistics studies. Here, we show for a substantially larger set of words that stability and change in terms of documented borrowings of words into English and into Dutch can be predicted by psycholinguistic properties of words that reflect their representational fidelity. We found that grammatical category, word length, age of acquisition, and frequency predict borrowing rates, but frequency has a non-linear relationship. Frequency correlates negatively with probability of borrowing for high-frequency words, but positively for low-frequency words. This borrowing evidence documents recent, observable diachronic change in the vocabulary enabling us to distinguish between change associated with transmission during language acquisition and change due to innovations by proficient speakers.

Abstract

How does the human brain combine a finite number of words to form an infinite variety of sentences? According to the Memory, Unification and Control (MUC) model, sentence processing requires long-range feedback from the left inferior frontal cortex (LIFC) to left posterior temporal cortex (LPTC). Single word processing however may only require feedforward propagation of semantic information from sensory regions to LPTC. Here we tested the claim that long-range feedback is required for sentence processing by reducing visual awareness of words using a masking technique. Masking disrupts feedback processing while leaving feedforward processing relatively intact. Previous studies have shown that masked single words still elicit an N400 ERP effect, a neural signature of semantic incongruency. However, whether multiple words can be combined to form a sentence under reduced levels of awareness is controversial. To investigate this issue, we performed two experiments in which we measured electroencephalography (EEG) while 40 subjects performed a masked priming task. Words were presented either successively or simultaneously, thereby forming a short sentence that could be congruent or incongruent with a target picture. This sentence condition was compared with a typical single word condition. In the masked condition we only found an N400 effect for single words, whereas in the unmasked condition we observed an N400 effect for both unmasked sentences and single words. Our findings suggest that long-range feedback processing is required for sentence processing, but not for single word processing.

Abstract

Increasing evidence implicates the sensorimotor systems with high-level cognition, but the extent to which these systems play a functional role remains debated. Using an elegant design, Shebani and Pulvermüller (2013) reported that carrying out a demanding rhythmic task with the hands led to selective impairment of working memory for hand-related words (e.g., clap), while carrying out the same task with the feet led to selective memory impairment for foot-related words (e.g., kick). Such a striking double dissociation is acknowledged even by critics to constitute strong evidence for an embodied account of working memory. Here, we report on an attempt at a direct replication of this important finding. We followed a sequential sampling design and stopped data collection at N=77 (more than five times the original sample size), at which point the evidence for the lack of the critical selective interference effect was very strong (BF01 = 91). This finding constitutes strong evidence against a functional contribution of the motor system to keeping action words in working memory. Our finding fits into the larger emerging picture in the field of embodied cognition that sensorimotor simulations are neither required nor automatic in high-level cognitive processes, but that they may play a role depending on the task. Importantly, we urge researchers to engage in transparent, high-powered, and fully pre-registered experiments like the present one to ensure the field advances on a solid basis.

Abstract

Much research has been dedicated to the effects of bilingualism on executive control (EC). For bilinguals with aphasia, the interplay with EC is complex. In this systematic review, we synthesize research on this topic and provide an overview of the current state of the field. First, we examine the evidence for EC deficits in bilingual persons with aphasia (bPWA). We then discuss the domain generality of bilingual language control impairments. Finally, we evaluate the bilingual advantage hypothesis in bPWA. We conclude that (1) EC impairments in bPWA are frequently observed, (2) experimental results on the relationship between linguistic and domain-general control are mixed, (3) bPWA with language control problems in everyday communication have domain-general EC problems, and (4) there are indications for EC advantages in bPWA. We end with directions for experimental work that could provide better insight into the intricate relationship between EC and bilingual aphasia.

Abstract

Background

Glioma (brain tumour) patients can suffer from mild linguistic and non-linguistic cognitive problems when the glioma is localised in an eloquent brain area. Word-finding problems are among the most frequently reported complaints. However, mild problems are difficult to measure with standard language tests because they are generally designed for more severe aphasic patients.

Aims

The aim of the present study was to investigate whether word-finding problems reported by patients with a glioma can be objectified with a standard object naming test, and a linguistic processing speed test. In addition, we examined whether word-finding problems and linguistic processing speed are related to non-verbal cognitive abilities.

Methods & Procedures

We tested glioma patients (N=36) as part of their standard pre-treatment clinical work-up. Word-finding problems were identified by a clinical linguist during the anamnesis. Linguistic processing speed was assessed with a newly designed sentence judgment test (SJT) as part of the Diagnostic Instrument for Mild Aphasia (DIMA), lexical retrieval with the Boston Naming Test (BNT), presence of aphasia with a Token Test (TT), and non-verbal processing with the Trail Making Test A and B (TMT). Test performances of glioma patients were compared to those of healthy control participants (N=35).

Outcomes & Results

The results show that many glioma patients (58%) report word-finding problems; these complaints were in only half of the cases supported by deviant scores on the BNT. Moreover, the presence of reported word-finding problems did not correlate with the BNT scores. However, word-finding problems were significantly correlated with reaction times on the SJT and the TMT. Although there were no significant differences between the patient and control group on the SJT, a subgroup of patients with a glioma in the frontal lobe of the language-dominant hemisphere was slower on the SJT. Finally, performance on the SJT and TMT were significantly correlated in the patient group but not in the control group.

Conclusions

Linguistic processing speed appears to be an important factor in explaining reported word-finding problems. Moreover, the overlap between speed of language processing and non-verbal processing indicates that patients may rely on more domain-general cognitive abilities as compared to healthy participants. The variability observed between patients emphasises the need for tailored neuro-linguistic assessments including an extensive anamnesis regarding language problems in clinical work-up.

Abstract

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre- registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

Abstract

Cultural evolution is the product of the psychological mechanisms that underlie individual decision making. One commonly studied learning mechanism is a disproportionate preference for majority opinions, known as conformist transmission. While most theoretical and experimental work approaches the majority in terms of the number of individuals that perform a behaviour or hold a belief, some recent experimental studies approach the majority in terms of the number of instances a behaviour is performed. Here, we use a mathematical model to show that disagreement between these two notions of the majority can arise when behavioural variants are performed at different rates, with different salience or in different contexts (variant overrepresentation) and when a subset of the population act as demonstrators to the whole population (model biases). We also show that because conformist transmission changes the distribution of behaviours in a population, how observers approach the majority can cause populations to diverge, and that this can happen even when the two approaches to the majority agree with regards to which behaviour is in the majority. We discuss these results in light of existing findings, ranging from political extremism on twitter to studies of animal foraging behaviour. We conclude that the factors we considered (variant overrepresentation and model biases) are plausibly widespread. As such, it is important to understand how individuals approach the majority in order to understand the effects of majority influence in cultural evolution.

Abstract

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

Abstract

The common carotid artery (CCA) usually runs along the long axis of the neck, although it is occasionally found in an abnormal position or is displaced. We report a case of an 86-year-old woman in whom the CCA was identified in the submandibular area. The patient visited our clinic and reported soft tissue swelling in the right submandibular area. It resembled a tumor mass or a swollen lymph node. Computed tomography showed that it was the right CCA that had been bent forward and was running along the submandibular subcutaneous area. Ultrasonography verified the diagnosis. No other lesions were found on the diagnostic images. Consequently, the patient was diagnosed as having abnormal CCA positioning. Although this condition generally requires no treatment, it is important to follow-up the abnormality with diagnostic imaging because of the risk of cerebrovascular disorders.

Abstract

ObjectivesPatients undergoing osteoporosis treatment benefit greatly from early detection. We previously developed a computer-aided diagnosis (CAD) system to identify osteoporosis using panoramic radiographs. However, the region of interest (ROI) was relatively small, and the method to select suitable ROIs was labor-intensive. This study aimed to expand the ROI and perform semi-automatized extraction of ROIs. The diagnostic performance and operating time were also assessed.MethodsWe used panoramic radiographs and skeletal bone mineral density data of 200 postmenopausal women. Using the reference point that we defined by averaging 100 panoramic images as the lower mandibular border under the mental foramen, a 400x100-pixel ROI was automatically extracted and divided into four 100x100-pixel blocks. Valid blocks were analyzed using program 1, which examined each block separately, and program 2, which divided the blocks into smaller segments and performed scans/analyses across blocks. Diagnostic performance was evaluated using another set of 100 panoramic images.ResultsMost ROIs (97.0%) were correctly extracted. The operation time decreased to 51.4% for program 1 and to 69.3% for program 2. The sensitivity, specificity, and accuracy for identifying osteoporosis were 84.0, 68.0, and 72.0% for program 1 and 92.0, 62.7, and 70.0% for program 2, respectively. Compared with the previous conventional system, program 2 recorded a slightly higher sensitivity, although it occasionally also elicited false positives.ConclusionsPatients at risk for osteoporosis can be identified more rapidly using this new CAD system, which may contribute to earlier detection and intervention and improved medical care.

Abstract

Using individual differences approaches, a growing body of literature finds positive associations between musicality and language-related abilities, complementing prior findings of links between musical training and language skills. Despite these associations, musicality has been often overlooked in mainstream models of individual differences in language acquisition and development. To better understand the biological basis of these individual differences, we propose the Musical Abilities, Pleiotropy, Language, and Environment (MAPLE) framework. This novel integrative framework posits that musical and language-related abilities likely share some common genetic architecture (i.e., genetic pleiotropy) in addition to some degree of overlapping neural endophenotypes, and genetic influences on musically and linguistically enriched environments. Drawing upon recent advances in genomic methodologies for unraveling pleiotropy, we outline testable predictions for future research on language development and how its underlying neurobiological substrates may be supported by genetic pleiotropy with musicality. In support of the MAPLE framework, we review and discuss findings from over seventy behavioral and neural studies, highlighting that musicality is robustly associated with individual differences in a range of speech-language skills required for communication and development. These include speech perception-in-noise, prosodic perception, morphosyntactic skills, phonological skills, reading skills, and aspects of second/foreign language learning. Overall, the current work provides a clear agenda and framework for studying musicality-language links using individual differences approaches, with an emphasis on leveraging advances in the genomics of complex musicality and language traits.

Abstract

This study investigated whether the phonological representation of a word is modulated by its orthographic representation in case of a mismatch between the two representations. Such a mismatch is found in Persian, where short vowels are represented phonemically but not orthographically. Persian adult literates, Persian adult illiterates, and German adult literates were presented with two auditory tasks, an AX-discrimination task and a reversal task. We assumed that if orthographic representations influence phonological representations, Persian literates should perform worse than Persian illiterates or German literates on items with short vowels in these tasks. The results of the discrimination tasks showed that Persian literates and illiterates as well as German literates were approximately equally competent in discriminating short vowels in Persian words and pseudowords. Persian literates did not well discriminate German words containing phonemes that differed only in vowel length. German literates performed relatively poorly in discriminating German homographic words that differed only in vowel length. Persian illiterates were unable to perform the reversal task in Persian. The results of the other two participant groups in the reversal task showed the predicted poorer performance of Persian literates on Persian items containing short vowels compared to items containing long vowels only. German literates did not show this effect in German. Our results suggest two distinct effects of orthography on phonemic representations: whereas the lack of orthographic representations seems to affect phonemic awareness, homography seems to affect the discriminability of phonemic representations.

Abstract

All languages instantiate a consonant/vowel contrast. This contrast has processing consequences at different levels of spoken-language recognition throughout the lifespan. In adulthood, lexical processing is more strongly associated with consonant than with vowel processing; this has been demonstrated across 13 languages from seven language families and in a variety of auditory lexical-level tasks (deciding whether a spoken input is a word, spotting a real word embedded in a minimal context, reconstructing a word minimally altered into a pseudoword, learning new words or the “words” of a made-up language), as well as in written-word tasks involving phonological processing. In infancy, a consonant advantage in word learning and recognition is found to emerge during development in some languages, though possibly not in others, revealing that the stronger lexicon–consonant association found in adulthood is learned. Current research is evaluating the relative contribution of the early acquisition of the acoustic/phonetic and lexical properties of the native language in the emergence of this association

Abstract

Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits.

Abstract

Moving in synchrony to the beat is a fundamental component of musicality. Here we conducted a genome-wide association study to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with 69 loci reaching genome-wide significance (P < 5 × 10−8) and single-nucleotide-polymorphism-based heritability (on the liability scale) of 13%–16%. Heritability was enriched for genes expressed in brain tissues and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central-nervous-system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through separate experiments) and of the genome-wide association study (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.