Publications

Abstract

Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of semantic and world knowledge to influence children's and adults' moment-by-moment interpretation of a story. Seven-year- olds were less effective at bypassing stored semantic and world knowledge during real-time interpretation than adults. Nevertheless, an effect of discourse context on comprehension was still apparent.

Abstract

People learn language from their social environment. As individuals differ in their social networks, they might be exposed to input with different lexical distributions, and these might influence their linguistic representations and lexical choices. In this article we test the relation between linguistic performance and 3 social network properties that should influence input variability, namely, network size, network heterogeneity, and network density. In particular, we examine how these social network properties influence lexical prediction, lexical access, and lexical use. To do so, in Study 1, participants predicted how people of different ages would name pictures, and in Study 2 participants named the pictures themselves. In both studies, we examined how participants’ social network properties related to their performance. In Study 3, we ran simulations on norms we collected to see how age variability in one’s network influences the distribution of different names in the input. In all studies, network age heterogeneity influenced performance leading to better prediction, faster response times for difficult-to-name items, and less entropy in input distribution. These results suggest that individual differences in social network properties can influence linguistic behavior. Specifically, they show that having a more heterogeneous network is associated with better performance. These results also show that the same factors influence lexical prediction and lexical production, suggesting the two might be related.

Abstract

Speakers constantly learn language from the environment by sampling their linguistic input and adjusting their representations accordingly. Logically, people should attend more to the environment and adjust their behavior in accordance with it more the lower their success in the environment is. We test whether the learning of linguistic input follows this general principle in two studies: a corpus analysis of a TV game show, Jeopardy, and a laboratory task modeled after Go Fish. We show that lower (non-linguistic) success in the task modulates learning of and reliance on linguistic patterns in the environment. In Study 1, we find that poorer performance increases conformity with linguistic norms, as reflected by increased preference for frequent grammatical structures. In Study 2, which consists of a more interactive setting, poorer performance increases learning from the immediate social environment, as reflected by greater repetition of others’ grammatical structures. We propose that these results have implications for models of language production and language learning and for the propagation of language change. In particular, they suggest that linguistic changes might spread more quickly in times of crisis, or when the gap between more and less successful people is larger. The results might also suggest that innovations stem from successful individuals while their propagation would depend on relatively less successful individuals. We provide a few historical examples that are in line with the first suggested implication, namely, that the spread of linguistic changes is accelerated during difficult times, such as war time and an economic downturn

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

Foreign-accented speech is generally harder to understand than native-accented speech. This difficulty is reduced for non-native listeners who share their first language with the non-native speaker. It is currently unclear, however, how non-native listeners deal with foreign-accented speech produced by speakers of a different language. We show that the process of (second) language acquisition is associated with an increase in the relative difficulty of processing foreign-accented speech. Therefore, experiencing greater relative difficulty with foreign-accented speech compared with native speech is a marker of language proficiency. These results contribute to our understanding of how phonological categories are acquired during second language learning.

Abstract

We learn language from our social environment. In general, the more sources we have, the less informative each of them is, and the less weight we should assign it. If this is the case, people who interact with fewer others should be more susceptible to the influence of each of their interlocutors. This paper tests whether indeed people who interact with fewer other people have more malleable phonological representations. Using a perceptual learning paradigm, this paper shows that individuals who regularly interact with fewer others are more likely to change their boundary between /d/ and /t/ following exposure to an atypical speaker. It further shows that the effect of number of interlocutors is not due to differences in ability to learn the speaker’s speech patterns, but specific to likelihood of generalizing the learned pattern. These results have implications for both language learning and language change, as they suggest that individuals with smaller social networks might play an important role in propagating linguistic changes.

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

This paper introduces a special issue of Cognition on lexical access in speech production. Over the last quarter century, the psycholinguistic study of speaking, and in particular of accessing words in speech, received a major new impetus from the analysis of speech errors, dysfluencies and hesitations, from aphasiology, and from new paradigms in reaction time research. The emerging theoretical picture partitions the accessing process into two subprocesses, the selection of an appropriate lexical item (a “lemma”) from the mental lexicon, and the phonological encoding of that item, that is, the computation of a phonetic program for the item in the context of utterance. These two theoretical domains are successively introduced by outlining some core issues that have been or still have to be addressed. The final section discusses the controversial question whether phonological encoding can affect lexical selection. This partitioning is also followed in this special issue as a whole. There are, first, four papers on lexical selection, then three papers on phonological encoding, and finally one on the interaction between selection and phonological encoding.

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

It is argued that the dominantly successive nature of language is largely mode-independent and holds equally for sign and for spoken language. A preliminary distinction is made between what is simultaneous or successive in the signal, and what is in the process; these need not coincide, and it is the successiveness of the process that is at stake. It is then discussed extensively for the word/sign level, and in a more preliminary fashion for the clause and discourse level that online processes are parallel in that they can simultaneously draw on various sources of knowledge (syntactic, semantic, pragmatic), but successive in that they can work at the interpretation of only one unit at a time. This seems to hold for both sign and spoken language. In the final section, conjectures are made about possible evolutionary explanations for these properties of language processing.

Abstract

In this article, we present an account of developmental data regarding the acquisition of syllable types. The data come from a longitudinal corpus of phonetically transcribed speech of 12 children acquiring Dutch as their first language. A developmental order of acquisition of syllable types was deduced by aligning the syllabified data on a Guttman scale. This order could be analyzed as following from an initial ranking and subsequent rerankings in the grammar of the structural constraints ONSET, NO-CODA, *COMPLEX-O, and *COMPLEX-C; some local conjunctions of these constraints; and a faithfulness constraint FAITH. The syllable type frequencies in the speech surrounding the language learner are also considered. An interesting correlation is found between the frequencies and the order of development of the different syllable types.

Abstract

In his paper, MacKay reviews his Node Structure theory of error detection, but precedes it with a critical discussion of the Perceptual Loop theory of self-monitoring proposed in Levelt (1983, 1989). The present commentary is concerned with this latter critique and shows that there are more than casual problems with MacKay’s argumentation.

Abstract

It is quite normal for us to produce one or two million word tokens every year. Speaking is a dear occupation and producing words is at the core of it. Still, producing even a single word is a highly complex affair. Recently, Levelt, Roelofs, and Meyer (1999) reviewed their theory of lexical access in speech production, which dissects the word-producing mechanism as a staged application of various dedicated operations. The present paper begins by presenting a bird eye's view of this mechanism. We then square the complexity by asking how speakers control multiple access in generating simple utterances such as a table and a chair. In particular, we address two issues. The first one concerns dependency: Do temporally contiguous access procedures interact in any way, or do they run in modular fashion? The second issue concerns temporal alignment: How much temporal overlap of processing does the system tolerate in accessing multiple content words, such as table and chair? Results from picture-word interference and eye tracking experiments provide evidence for restricted cases of dependency as well as for constraints on the temporal alignment of access procedures.

Abstract

This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.

Abstract

This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.

Abstract

Comment on Sperber and Wilson

Abstract

These classic tasks can be used to explore spatial reference in field settings. They provide a language-independent metric for eliciting spatial language, using a “director-matcher” paradigm. The Man and Tree task deals with location on the horizontal plane with both featured (man) and non-featured (e.g., tree) objects. The Space Games depict various objects (e.g. bananas, lemons) and elicit spatial contrasts not obviously lexicalisable in English.

Abstract

Survey article

Abstract

The essential insight of speech act theory was that when we use language, we perform actions—in a more modern parlance, core language use in interaction is a form of joint action. Over the last thirty years, speech acts have been relatively neglected in linguistic pragmatics, although important work has been done especially in conversation analysis. Here we review the core issues—the identifying characteristics, the degree of universality, the problem of multiple functions, and the puzzle of speech act recognition. Special attention is drawn to the role of conversation structure, probabilistic linguistic cues, and plan or sequence inference in speech act recognition, and to the centrality of deep recursive structures in sequences of speech acts in conversation

Abstract

This paper is one in a series that develops a pragmatic framework in loose confederation with Jay Atlas and Larry Horn: thus they may or may not be responsible for the ideas contained herein. Jay Atlas provided many comments which I have utilized or perverted as the case may be. The Australian data to which this framework is applied was collected with the financial and personal assistance of many people and agencies acknowledged separately below; but I must single out for special thanks John Haviland, who recommended the study of Guugu Yimidhirr anaphora to me and upon whose grammatical work on Guugu Yimidhirr this paper is but a minor (and perhaps flawed) elaboration. A grant from the British Academy allowed me to visit Haviland in September 1986 to discuss many aspects of Guugu Yimidhirr with him, and I am most grateful to the Academy for funding this trip and to Haviland for generously making available his time, his texts (from which I have drawn many examples, not always with specific acknowledgement) and most especially his expertise. Where I have diverged from his opinion I may well learn to regret it. I must also thank Nigel Vincent for putting me in touch with a number of recent relevant developments in syntax (only some of which I have been able to address) and for suggestions for numerous improvements. In addition, I have benefited immensely for comments on a distinct but related paper (Levinson, 1987) kindly provided by Jay Atlas, John Haviland, John Heritage, Phil Johnson-Laird, John Lyons, Tanya Reinhart, Emanuel Schegloff and an anonymous referee; and from comments on this paper by participants in the Cambridge Linguistics Department seminar where it was first presented (especial thanks to John Lyons and Huang Yan for further comments, and Mary Smith for a counter-example). Despite all this help, there are sure to be errors of data and analysis that I have persisted in. Aid in gathering the Australian data is acknowledged separately below.

Abstract

The theory of basic color terms was a crucial factor in the demise of linguistic relativity. The theory is now once again under scrutiny and fundamental revision. This article details a case study that undermines one of the central claims of the classical theory, namely that languages universally treat color as a unitary domain, to be exhaustively named. Taken together with other cases, the study suggests that a number of languages have only an incipient color terminology, raising doubts about the linguistic universality of such terminology.

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

In this study, we used electroencephalography to investigate the influence of discourse-level semantic coherence on electrophysiological signatures of local sentence-level processing. Participants read groups of four sentences that could either form coherent stories or were semantically unrelated. For semantically coherent discourses compared to incoherent ones, the N400 was smaller at sentences 2–4, while the visual N1 was larger at the third and fourth sentences. Oscillatory activity in the beta frequency range (13–21 Hz) was higher for coherent discourses. We relate the N400 effect to a disruption of local sentence-level semantic processing when sentences are unrelated. Our beta findings can be tentatively related to disruption of local sentence-level syntactic processing, but it cannot be fully ruled out that they are instead (or also) related to disrupted local sentence-level semantic processing. We conclude that manipulating discourse-level semantic coherence does have an effect on oscillatory power related to local sentence-level processing.

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

Arbitrary communication systems can emerge from iconic beginnings through processes of conventionalisation via interaction. Here, we explore whether this process of conventionalisation occurs with continuous, auditory signals. We conducted an artificial signalling experiment. Participants either created signals for themselves, or for a partner in a communication game. We found no evidence that the speech-like signals in our experiment became less iconic or simpler through interaction. We hypothesise that the reason for our results is that when it is difficult to be iconic initially because of the constraints of the modality, then iconicity needs to emerge to enable grounding before conventionalisation can occur. Further, pressures for discrimination, caused by the expanding meaning space in our study, may cause more complexity to emerge, again as a result of the restrictive signalling modality. Our findings have possible implications for the processes of conventionalisation possible in signed and spoken languages, as the spoken modality is more restrictive than the manual modality.

Abstract

In language evolution research, the use of computational and experimental methods to investigate the emergence of structure in language is exploding. In this review, we look exclusively at work exploring the emergence of structure in speech, on both a categorical level (what drives the emergence of an inventory of individual speech sounds), and a combinatorial level (how these individual speech sounds emerge and are reused as part of larger structures). We show that computational and experimental methods for investigating population-level processes can be effectively used to explore and measure the effects of learning, communication and transmission on the emergence of structure in speech. We also look at work on child language acquisition as a tool for generating and validating hypotheses for the emergence of speech categories. Further, we review the effects of noise, iconicity and production effects.

Abstract

How did human sound systems get to be the way they are? Collecting contributions implementing a wealth of methods to address this question, this special issue treats language and speech as being the result of a complex adaptive system. The work throughout provides evidence and theory at the levels of phylogeny, glossogeny and ontogeny. In taking a multi-disciplinary approach that considers interactions within and between these levels of selection, the papers collectively provide a valuable, integrated contribution to existing work on the evolution of speech and sound systems.

Abstract

Previous research has shown that repeated interactions can cause iconicity in signals to reduce. However, data from several recent studies has shown the opposite trend: an increase in iconicity as the result of repeated interactions. Here, we discuss whether signals may become less or more iconic as a result of the modality used to produce them. We review several recent experimental results before presenting new data from multi-modal signals, where visual input creates audio feedback. Our results show that the growth in iconicity present in the audio information may come at a cost to iconicity in the visual information. Our results have implications for how we think about and measure iconicity in artificial signalling experiments. Further, we discuss how iconicity in real world speech may stem from auditory, kinetic or visual information, but iconicity in these different modalities may conflict.

Abstract

In language, a small number of meaningless building blocks can be combined into an unlimited set of meaningful utterances. This is known as combinatorial structure. One hypothesis for the initial emergence of combinatorial structure in language is that recombining elements of signals solves the problem of overcrowding in a signal space. Another hypothesis is that iconicity may impede the emergence of combinatorial structure. However, how these two hypotheses relate to each other is not often discussed. In this paper, we explore how signal space dimensionality relates to both overcrowding in the signal space and iconicity. We use an artificial signalling experiment to test whether a signal space and a meaning space having similar topologies will generate an iconic system and whether, when the topologies differ, the emergence of combinatorially structured signals is facilitated. In our experiments, signals are created from participants' hand movements, which are measured using an infrared sensor. We found that participants take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory predictability, measures of variance, and Hidden Markov Models to measure the use of structure within the signals produced and found that when topologies do not match, then there is more evidence of combinatorial structure. The results from these experiments are interpreted in the context of the differences between the emergence of combinatorial structure in different linguistic modalities (speech and sign).

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

Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

Abstract

In every-day conversations, the gap between turns of conversational partners is most frequently between 0 and 200 ms. We were interested how speakers achieve such fast transitions. We designed an experiment in which participants listened to pre-recorded questions about images presented on a screen and were asked to answer these questions. We tested whether speakers already prepare their answers while they listen to questions and whether they can prepare for the time of articulation by anticipating when questions end. In the experiment, it was possible to guess the answer at the beginning of the questions in half of the experimental trials. We also manipulated whether it was possible to predict the length of the last word of the questions. The results suggest when listeners know the answer early they start speech production already during the questions. Speakers can also time when to speak by predicting the duration of turns. These temporal predictions can be based on the length of anticipated words and on the overall probability of turn durations.

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

Vocabulary knowledge is central to a speaker's command of their language. In previous research, greater vocabulary knowledge has been associated with advantages in language processing. In this study, we examined the relationship between individual differences in vocabulary and language processing performance more closely by (i) using a battery of vocabulary tests instead of just one test, and (ii) testing not only university students (Experiment 1) but young adults from a broader range of educational backgrounds (Experiment 2). Five vocabulary tests were developed, including multiple-choice and open antonym and synonym tests and a definition test, and administered together with two established measures of vocabulary. Language processing performance was measured using a lexical decision task. In Experiment 1, vocabulary and word frequency were found to predict word recognition speed while we did not observe an interaction between the effects. In Experiment 2, word recognition performance was predicted by word frequency and the interaction between word frequency and vocabulary, with high-vocabulary individuals showing smaller frequency effects. While overall the individual vocabulary tests were correlated and showed similar relationships with language processing as compared to a composite measure of all tests, they appeared to share less variance in Experiment 2 than in Experiment 1. Implications of our findings concerning the assessment of vocabulary size in individual differences studies and the investigation of individuals from more varied backgrounds are discussed.

Abstract

The project that we describe in this chapter has the theme ‘Language of the senses’. This theme is
based on the research of Asifa Majid and her team regarding the influence of language and culture on
sensory perception. The chapter consists of two sections. Section 2.1 describes how different sensory
perceptions are spoken of in different languages. Teachers can use this section as substantive preparation
before they launch this theme in the classroom. Section 2.2 describes how teachers can handle
this theme in accordance with the seven phases of inquiry-based learning. Chapter 1, in which the
general guideline of the seven phases is described, forms the basis for this. We therefore recommend
the use of chapter 1 as the starting point for the execution of a project in the classroom. This chapter
provides the thematic additions.

Abstract

Taal der zintuigen gaat over de invloed van taal en cultuur op zintuiglijke waarnemingen. Hoe omschrijf je wat je ziet, voelt, proeft of ruikt? In sommige culturen zijn er veel verschillende woorden voor kleur, in andere culturen juist weer heel weinig. Worden we geboren met deze verschillende kleurgroepen? En bepaalt hoe je ergens over praat ook wat je waarneemt?

Abstract

Olfaction is often viewed as difficult, yet the empirical evidence suggests a different picture. A closer look shows people around the world differ in their ability to detect, discriminate, and name odors. This gives rise to the question of what influences our ability to smell. Instead of focusing on olfactory deficiencies, this review presents a positive perspective by focusing on factors that make someone a better smeller. We consider three driving forces in improving olfactory ability: one’s biological makeup, one’s experience, and the environment. For each factor, we consider aspects proposed to improve odor perception and critically examine the evidence; as well as introducing lesser discussed areas. In terms of biology, there are cases of neurodiversity, such as olfactory synesthesia, that serve to enhance olfactory ability. Our lifetime experience, be it typical development or unique training experience, can also modify the trajectory of olfaction. Finally, our odor environment, in terms of ambient odor or culinary traditions, can influence odor perception too. Rather than highlighting the weaknesses of olfaction, we emphasize routes to harnessing our olfactory potential.

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

This study addresses the question of whether native Mandarin Chinese speakers process and comprehend subject-extracted relative clauses (SRC) more readily than objectextracted relative clauses (ORC) in Mandarin Chinese. Presently, this has been a hotly debated issue, with various studies producing contrasting results. Using two eye-tracking experiments with ambiguous and unambiguous RCs, this study shows that both ORCs and SRCs have different processing requirements depending on the locus and time course during reading. The results reveal that ORC reading was possibly facilitated by linear/ temporal integration and canonicity. On the other hand, similarity-based interference made ORCs more difficult, and expectation-based processing was more prominent for unambiguous ORCs. Overall, RC processing in Mandarin should not be broken down to a single ORC (dis) advantage, but understood as multiple interdependent factors influencing whether ORCs are either more difficult or easier to parse depending on the task and context at hand.

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

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

Biological systems often detect species-specific signals in the environment. In humans, speech and language are species-specific signals of fundamental biological importance. To detect the linguistic signal, human brains must form hierarchical representations from a sequence of perceptual inputs distributed in time. What mechanism underlies this ability? One hypothesis is that the brain repurposed an available neurobiological mechanism when hierarchical linguistic representation became an efficient solution to a computational problem posed to the organism. Under such an account, a single mechanism must have the capacity to perform multiple, functionally related computations, e.g., detect the linguistic signal and perform other cognitive functions, while, ideally, oscillating like the human brain. We show that a computational model of analogy, built for an entirely different purpose—learning relational reasoning—processes sentences, represents their meaning, and, crucially, exhibits oscillatory activation patterns resembling cortical signals elicited by the same stimuli. Such redundancy in the cortical and machine signals is indicative of formal and mechanistic alignment between representational structure building and “cortical” oscillations. By inductive inference, this synergy suggests that the cortical signal reflects structure generation, just as the machine signal does. A single mechanism—using time to encode information across a layered network—generates the kind of (de)compositional representational hierarchy that is crucial for human language and offers a mechanistic linking hypothesis between linguistic representation and cortical computation

Abstract

While structural priming makes a valuable contribution to psycholinguistics, it does not allow direct observation of representation, nor escape “source ambiguity.” Structural priming taps into implicit memory representations and processes that may differ from what is used online. We question whether implicit memory for language can and should be equated with linguistic representation or with language processing.

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

The mapping between the physical speech signal and our internal representations is rarely straightforward. When faced with uncertainty, higher-order information is used to parse the signal and because of this, the lexicon and some aspects of sentential context have been shown to modulate the identification of ambiguous phonetic segments. Here, using a phoneme identification task (i.e., participants judged whether they heard [o] or [a] at the end of an adjective in a noun–adjective sequence), we asked whether grammatical gender cues influence phonetic identification and if this influence is shaped by the phonetic properties of the agreeing elements. In three experiments, we show that phrase-level gender agreement in Spanish affects the identification of ambiguous adjective-final vowels. Moreover, this effect is strongest when the phonetic characteristics of the element triggering agreement and the phonetic form of the agreeing element are identical. Our data are consistent with models wherein listeners generate specific predictions based on the interplay of underlying morphosyntactic knowledge and surface phonetic cues.