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Longstanding cross-linguistic work on event representations in spoken languages have argued for a robust mapping between an event's underlying representation and its syntactic encoding, such that-for example-the agent of an event is most frequently mapped to subject position. In the same vein, sign languages have long been claimed to construct signs that visually represent their meaning, i.e., signs that are iconic. Experimental research on linguistic parameters such as plurality and aspect has recently shown some of them to be visually universal in sign, i.e. recognized by non-signers as well as signers, and have identified specific visual cues that achieve this mapping. However, little is known about what makes action representations in sign language iconic, or whether and how the mapping of underlying event representations to syntactic encoding is visually apparent in the form of a verb sign. To this end, we asked what visual cues non-signers may use in evaluating transitivity (i.e., the number of entities involved in an action). To do this, we correlated non-signer judgments about transitivity of verb signs from American Sign Language (ASL) with phonological characteristics of these signs. We found that non-signers did not accurately guess the transitivity of the signs, but that non-signer transitivity judgments can nevertheless be predicted from the signs' visual characteristics. Further, non-signers cue in on just those features that code event representations across sign languages, despite interpreting them differently. This suggests the existence of visual biases that underlie detection of linguistic categories, such as transitivity, which may uncouple from underlying conceptual representations over time in mature sign languages due to lexicalization processes., Competing Interests: The authors have declared that no competing interests exist.

The surge of post-truth political argumentation suggests that we are living in a special historical period when it comes to the balance between emotion and reasoning. To explore if this is indeed the case, we analyze language in millions of books covering the period from 1850 to 2019 represented in Google nGram data. We show that the use of words associated with rationality, such as "determine" and "conclusion," rose systematically after 1850, while words related to human experience such as "feel" and "believe" declined. This pattern reversed over the past decades, paralleled by a shift from a collectivistic to an individualistic focus as reflected, among other things, by the ratio of singular to plural pronouns such as "I"/"we" and "he"/"they." Interpreting this synchronous sea change in book language remains challenging. However, as we show, the nature of this reversal occurs in fiction as well as nonfiction. Moreover, the pattern of change in the ratio between sentiment and rationality flag words since 1850 also occurs in New York Times articles, suggesting that it is not an artifact of the book corpora we analyzed. Finally, we show that word trends in books parallel trends in corresponding Google search terms, supporting the idea that changes in book language do in part reflect changes in interest. All in all, our results suggest that over the past decades, there has been a marked shift in public interest from the collective to the individual, and from rationality toward emotion., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Raw linguistic data within psychotherapy sessions may provide important information about clients' progress and well-being. In the current study, computerized text analytic techniques were applied to examine whether linguistic features were associated with clients' experiences of distress within and between clients and whether changes in linguistic features were associated with changes in treatment outcome. Transcripts of 729 psychotherapy sessions from 58 clients treated by 52 therapists were analyzed. Prior to each session, clients reported their distress level. Linguistic features were extracted automatically by using natural language parser for first-person singular identification and using positive and negative emotion words lexicon. The association between linguistic features and levels of distress was examined using multilevel models. At the within-client level, fewer first-person singular words, fewer negative emotional words and more positive emotional words were associated with lower distress in the same session; and fewer negative emotion words were associated with lower next session distress (rather small f2 effect sizes = 0.011 < f2 < 0.022). At the between-client level, only first session use of positive emotion words was associated with first session distress (ηp2 effect size = 0.08). A drop in the use of first-person singular words was associated with improved outcome from pre- to posttreatment (small ηp2 effect size = 0.05). The findings provide preliminary support for the association between clients' linguistic features and their fluctuating experience of distress. They point to the potential value of computerized linguistic measures to track therapeutic outcomes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial semantics of implied spatial information are rarely preserved. Geographic information retrieval (GIR) methods have focused on this issue; however, they sometimes fail to solve the problem because the spatial and textual similarities of words are considered and calculated separately. In this paper, from the perspective of spatial context, we consider the two parts as a whole-spatial context semantics, and we propose a method that measures spatial semantic similarity using a sliding geospatial context window for geo-tagged words. The proposed method was first validated with a set of simulated data and then applied to a real-world dataset from Flickr. As a result, a spatial semantic similarity model at different scales is presented. We believe this model is a necessary supplement for traditional textual-language semantic analyses of words obtained by word-embedding technologies. This study has the potential to improve the quality of recommendation systems by considering relevant spatial context semantics, and benefits linguistic semantic research by emphasising the spatial cognition among words., Competing Interests: The authors have declared that no competing interests exist.

Stretched words like 'heellllp' or 'heyyyyy' are a regular feature of spoken language, often used to emphasize or exaggerate the underlying meaning of the root word. While stretched words are rarely found in formal written language and dictionaries, they are prevalent within social media. In this paper, we examine the frequency distributions of 'stretchable words' found in roughly 100 billion tweets authored over an 8 year period. We introduce two central parameters, 'balance' and 'stretch', that capture their main characteristics, and explore their dynamics by creating visual tools we call 'balance plots' and 'spelling trees'. We discuss how the tools and methods we develop here could be used to study the statistical patterns of mistypings and misspellings and be used as a basis for other linguistic research involving stretchable words, along with the potential applications in augmenting dictionaries, improving language processing, and in any area where sequence construction matters, such as genetics., Competing Interests: We have the following interests: TJG, CMD, and PSD were supported by a gift from MassMutual. There are no patents, products in development, or marketed products to declare. This does not alter our adherence to all of the PLOS ONE policies on sharing data and materials.

The novel finding of Balakrishnan, Miller & Shankar (2008) that investors, overwhelmed by the plethora of stock investment offerings, limit their analysis and daily choices to only a small subset of stocks (i.e., herding behavior) now seems to be common wisdom (Iosebashvili, 2019). We investigate whether the introduction of an innovation in financial products designed to allow investors to trade the entire product bundle of S&P 500 stocks, namely S&P 500 index funds, altered "herding behavior" by creating a new class of index investors. We model the distribution of daily trading concentration as a power law function and examine changes over the last six decades. Intriguingly, we discover a unique pattern in the trading concentration distribution that exhibits two distinct trends. For the period 1960-75, the trading concentration of the S&P 500 stocks tracks the increasing trend for the entire market, i.e., the unevenness in trading has steadily increased. However, after the introduction of S&P 500 index funds in 1975, concentration of trading in the S&P 500 stocks has steadily decreased, i.e., trading distribution has become more even across all 500 stocks, contrary to the current belief of equity analysts. This is also in sharp contrast to the case of U.S. stocks that are not in the S&P 500 index where trading concentration has steadily increased. We further corroborate the uniqueness of the inverted V-shape by a counterfactual investigation of the trading concentration patterns for other sets of 500 stock portfolios. This uniquely distinctive trading concentration pattern for S&P 500 stocks appears to be driven by the increasing dominance of bundle trading by index investors., Competing Interests: The authors have declared that no competing interests exist.

Recently, prominent theoretical linguists have argued for an explicit scenario for the evolution of the human language capacity on the basis of its computational properties. Concretely, the simplicity of a minimalist formulation of the operation Merge, which allows humans to recursively compute hierarchical relations in language, has been used to promote a sudden-emergence, single-mutation scenario. In support of this view, Merge is said to be either fully present or fully absent: one cannot have half-Merge. On this basis, it is inferred that the emergence of our fully fledged language capacity had to be sudden. Thus, proponents of this view draw a parallelism between the formal complexity of the operation at the computational level and the number of evolutionary steps it must imply. Here, we examine this argument in detail and show that the jump from the atomicity of Merge to a single-mutation scenario is not valid and therefore cannot be used as justification for a theory of language evolution along those lines., Competing Interests: The authors have declared that no competing interests exist.

Hearing in noisy environments is a complicated task that engages attention, memory, linguistic knowledge, and precise auditory-neurophysiological processing of sound. Accumulating evidence in school-aged children and adults suggests these mechanisms vary with the task's demands. For instance, co-located speech and noise demands a large cognitive load and recruits working memory, while spatially separating speech and noise diminishes this load and draws on alternative skills. Past research has focused on one or two mechanisms underlying speech-in-noise perception in isolation; few studies have considered multiple factors in tandem, or how they interact during critical developmental years. This project sought to test complementary hypotheses involving neurophysiological, cognitive, and linguistic processes supporting speech-in-noise perception in young children under different masking conditions (co-located, spatially separated). Structural equation modeling was used to identify latent constructs and examine their contributions as predictors. Results reveal cognitive and language skills operate as a single factor supporting speech-in-noise perception under different masking conditions. While neural coding of the F0 supports perception in both co-located and spatially separated conditions, neural timing predicts perception of spatially separated listening exclusively. Together, these results suggest co-located and spatially separated speech-in-noise perception draw on similar cognitive/linguistic skills, but distinct neural factors, in early childhood., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Dyslexia is often characterized by disordered word recognition and spelling, though dysfunction on various non-linguistic tasks suggests a more pervasive deficit may underlie reading and spelling abilities. The serial-order learning impairment in dyslexia (SOLID) hypothesis proposes that sequence learning impairments fundamentally disrupt cognitive abilities, including linguistic processes, among individuals with dyslexia; yet only some studies report sequence learning deficits in people with dyslexia relative to controls. Evidence may be mixed because traditional sequence learning tasks often require strong motor demands, working memory processes and/or executive functions, wherein people with dyslexia can show impairments. Thus, observed sequence learning deficits in dyslexia may only appear to the extent that comorbid motor-based processes, memory capacity, or executive processes are involved. The present study measured sequence learning in college-aged students with and without dyslexia using a single task that evaluates sequencing and non-sequencing components but without strong motor, executive, or memory demands. During sequencing, each additional link in a sequence of stimuli leading to a reward is trained step-by-step, until a complete sequence is acquired. People with dyslexia made significantly more sequencing errors than controls, despite equivalent performance on non-sequencing components. Mediation analyses further revealed that sequence learning accounted for a large portion of the variance between dyslexia status and linguistic abilities, particularly pseudo-word reading. These findings extend the SOLID hypothesis by showing difficulties in the ability to acquire sequences that may play an underlying role in literacy acquisition., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Associating human genetic makeup with the faculty of language has long been a goal for biolinguistics. This stimulated the idea that language is attributed to genes and language disabilities are caused by genetic mutations. However, application of genetic knowledge on language intervention is still a gap in the existing literature. In an effort to bridge this gap, this article presents an account of genetic and neural associations of language and synthesizes the genetic, neural, epigenetic and environmental facets involved in language. In addition to describing the association of genes with language, the neural and epigenetic aspects of language are also explored. Further, the environmental aspects of language such as language input, emotion and cognition are also traced back to gene expressions. Therefore, effective language intervention for language learning difficulties must offer genetics-informed solutions, both linguistic and medical.

The roots of gender disparities in science achievement take hold in early childhood. The present studies aimed to identify a modifiable feature of young children's environments that could be targeted to reduce gender differences in science behavior among young children. Four experimental studies with children ( N = 501) revealed that describing science in terms of actions ("Let's do science! Doing science means exploring the world!") instead of identities ("Let's be scientists! Scientists explore the world!") increased girls' subsequent persistence in new science games designed to illustrate the scientific method. These studies thus identified subtle but powerful linguistic cues that could be targeted to help reduce gender disparities in science engagement in early childhood.

Verbal working memory-intensive sentence processing declines with age. This might reflect older adults' difficulties with reducing the memory load by grouping single words into multiword chunks. Here we used a serial order task emphasizing syntactic and semantic relations. We evaluated the extent to which older compared with younger adults may differentially use linguistic constraints during sentence processing to cope with verbal working memory limitations. Probing syntactic-semantic interactions, age differences were hypothesized to be confined to the use of syntactic constraints and to be accompanied by an increased reliance on semantic information. Two experiments varying in verbal working memory demands were conducted: the sequence length was increased from eight items in Experiment 1 to 11 items in Experiment 2. We found the use of syntactic constraints to be compromised with aging, while the benefit of semantic information for sentence processing was comparable across age groups. Hence, we suggest that semantic information processing may become relatively more important for successful sentence processing with advancing adult age, possibly inducing a syntactic-to-semantic-processing strategy shift. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investigate the lexical-level differences between AD and healthy speech., Objective: Our goals include obtaining state-of-art performance of automatic AD detection, emphasizing N-gram LMs as powerful tools for distinguishing AD patients' narratives from those of healthy controls, and discovering the differences of lexical usages between AD patients and healthy people., Method: We utilize a subset of the DementiaBank corpus, including 242 control samples from 99 control participants and 256 AD samples from 169 "PossibleAD" or "ProbableAD" participants. Baseline models are built through area under curve-based feature selection and using five machine learning algorithms for comparison. Perplexity features are extracted using LMs to build enhanced detection models. Finally, the differences of lexical usages between AD patients and healthy people are investigated by a proportion test based on unigram probabilities., Results: Our baseline model obtains a detection accuracy of 80.7%. This accuracy increases to 85.4% after integrating the perplexity features derived from LMs. Further investigations show that AD patients tend to use more general, less informative, and less accurate words to describe characters and actions than healthy controls., Conclusion: The perplexity features extracted by LMs can benefit the automatic AD detection from continuous speech. There exist lexical-level differences between AD and healthy speech that can be captured by statistical N-gram LMs.

Despite the large number of elderly bilinguals at risk for Alzheimer's disease (AD) and dementia worldwide, significant questions remain about the relationship between speaking more than one language and later cognitive decline. Bilingualism may impact on cognitive and neural reserve, time of onset of dementia symptoms and neuropathology, and linguistic competency in dementia. This review indicates increased cognitive reserve from executive (monitoring, selecting, inhibiting) control of two languages and increased neural reserve involving left frontal and related areas for language control. Many, but not all, studies indicate a delay in dementia symptom onset but worse hippocampal and mesiotemporal atrophy among bilinguals versus monolinguals with AD. In contrast, bilinguals do worse on language measures, and bilinguals with AD or dementia have difficulty maintaining and monitoring their second language. Together, these studies suggest that early-acquired and proficient bilingualism increases reserve through frontal-predominant executive control, and these executive abilities compensate for early dementia symptoms, delaying their onset but not the neuropathology of their disease. Finally, as executive control decreases further with advancing dementia, there is increasing difficulty inhibiting the dominant first language and staying in the second language. These conclusions must be interpreted with caution, given the problems inherent in this type of research; however, they do recommend more work on the pre-dementia neuroprotective effects and the dementia-related language impairments of bilingualism.

There are more than 7,000 languages spoken in the world today 1 . It has been argued that the natural and social environment of languages drives this diversity 2-13 . However, a fundamental question is how strong are environmental pressures, and does neutral drift suffice as a mechanism to explain diversification? We estimate the phylogenetic signals of geographic dimensions, distance to water, climate and population size on more than 6,000 phylogenetic trees of 46 language families. Phylogenetic signals of environmental factors are generally stronger than expected under the null hypothesis of no relationship with the shape of family trees. Importantly, they are also-in most cases-not compatible with neutral drift models of constant-rate change across the family tree branches. Our results suggest that language diversification is driven by further adaptive and non-adaptive pressures. Language diversity cannot be understood without modelling the pressures that physical, ecological and social factors exert on language users in different environments across the globe.

The effects of Communicative functions and Mind-Mindedness on children's language development have been typically investigated in separate studies. The present longitudinal research was therefore designed to yield new insight into the simultaneous impact of these two dimensions of maternal responsiveness on the acquisition of expressive language skills in a sample of 25 mother-child dyads. The frequencies of five communicative functions (Tutorial, Didactic, Conversational, Control and Asynchronous) and two types of mind-related comments (attuned vs. non-attuned) were assessed from a 15-min play session at 16 months. Children's expressive language was examined at both 16 months (number of word types and tokens produced, and number of words attributed to the child in the Questionnaire for Communication and Early Language development) and 20 months (number of internal and non-internal words attributed to the child in the Italian version of the Mac Arthur-Bates Communicative Development Inventory). The main finding was that mothers' use of attuned mind-related comments at 16 months predicted internal state language at 20 months, above and beyond the effects of CFs and children's linguistic ability at 16 months; in addition, mothers' Tutorial function at 16 months marginally predicted non-internal state language at 20 months, after controlling for MM and children's linguistic ability at 16 months. These results suggest that different expressions of maternal responsiveness influence distinct aspects of children's expressive language in the second year of life, although the effects of MM appear to be more robust., (Copyright © 2017 Elsevier Inc. All rights reserved.)

It is tempting to treat frequency trends from the Google Books data sets as indicators of the "true" popularity of various words and phrases. Doing so allows us to draw quantitatively strong conclusions about the evolution of cultural perception of a given topic, such as time or gender. However, the Google Books corpus suffers from a number of limitations which make it an obscure mask of cultural popularity. A primary issue is that the corpus is in effect a library, containing one of each book. A single, prolific author is thereby able to noticeably insert new phrases into the Google Books lexicon, whether the author is widely read or not. With this understood, the Google Books corpus remains an important data set to be considered more lexicon-like than text-like. Here, we show that a distinct problematic feature arises from the inclusion of scientific texts, which have become an increasingly substantive portion of the corpus throughout the 1900 s. The result is a surge of phrases typical to academic articles but less common in general, such as references to time in the form of citations. We use information theoretic methods to highlight these dynamics by examining and comparing major contributions via a divergence measure of English data sets between decades in the period 1800-2000. We find that only the English Fiction data set from the second version of the corpus is not heavily affected by professional texts. Overall, our findings call into question the vast majority of existing claims drawn from the Google Books corpus, and point to the need to fully characterize the dynamics of the corpus before using these data sets to draw broad conclusions about cultural and linguistic evolution.

Our understanding of the cognitive and neural underpinnings of language has traditionally been firmly based on spoken Indo-European languages and on language studied as speech or text. However, in face-to-face communication, language is multimodal: speech signals are invariably accompanied by visual information on the face and in manual gestures, and sign languages deploy multiple channels (hands, face and body) in utterance construction. Moreover, the narrow focus on spoken Indo-European languages has entrenched the assumption that language is comprised wholly by an arbitrary system of symbols and rules. However, iconicity (i.e. resemblance between aspects of communicative form and meaning) is also present: speakers use iconic gestures when they speak; many non-Indo-European spoken languages exhibit a substantial amount of iconicity in word forms and, finally, iconicity is the norm, rather than the exception in sign languages. This introduction provides the motivation for taking a multimodal approach to the study of language learning, processing and evolution, and discusses the broad implications of shifting our current dominant approaches and assumptions to encompass multimodal expression in both signed and spoken languages., (© 2014 The Author(s) Published by the Royal Society. All rights reserved.)

Global patterns of ethnolinguistic diversity vary tremendously. Some regions show very little variation even across vast expanses, whereas others exhibit dense mosaics of different languages spoken alongside one another. Compared with the rest of Native North America, prehistoric California exemplified the latter. Decades of linguistic, genetic, and archaeological research have produced detailed accounts of the migrations that aggregated to build California's diverse ethnolinguistic mosaic, but there have been few have attempts to explain the process underpinning these migrations and why such a mosaic did not develop elsewhere. Here we show that environmental productivity predicts both the order of migration events and the population density recorded at contact. The earliest colonizers occupied the most suitable habitats along the coast, whereas subsequent Mid-Late Holocene migrants settled in more marginal habitats. Other Late Holocene patterns diverge from this trend, reflecting altered dynamics linked to food storage and increased sedentism. Through repeated migration events, incoming populations replaced resident populations occurring at lower densities in lower-productivity habitats, thereby resulting in the fragmentation of earlier groups and the development of one of the most diverse ethnolinguistic patterns in the Americas. Such a process may account for the distribution of ethnolinguistic diversity worldwide.

This is a report of the main points I made in an informal "conversation" with Paul Fletcher and the audience at the 14th ICPLA conference in Cork. The observations arose randomly, as part of an unstructured 1-h Q&A, so they do not provide a systematic account of the subject, but simply reflect the issues which were raised by the conference participants during that time.

We explored variation in the linguistic environments of hearing children of Deaf parents and how it was associated with their early bilingual language development. For that purpose we followed up the children's productive vocabulary (measured with the MCDI; MacArthur Communicative Development Inventory) and syntactic complexity (measured with the MLU10; mean length of the 10 longest utterances the child produced during videorecorded play sessions) in both Finnish Sign Language and spoken Finnish between the ages of 12 and 30 months. Additionally, we developed new methodology for describing the linguistic environments of the children (N = 10). Large variation was uncovered in both the amount and type of language input and language acquisition among the children. Language exposure and increases in productive vocabulary and syntactic complexity were interconnected. Language acquisition was found to be more dependent on the amount of exposure in sign language than in spoken language. This was judged to be related to the status of sign language as a minority language. The results are discussed in terms of parents' language choices, family dynamics in Deaf-parented families and optimal conditions for bilingual development.

It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

Objective and Background: Linguistic function is one of vulnerable aspects of traumatic brain injury (TBI) which may have destructive effects on patients' communicative activities and daily life, years following trauma. This paper attempts to answer the controversy whether surgery affects increase and decrease of linguistic impairment or not., Materials and Methods: Two hundred forty-one TBI patients aged 18-65 with abnormal CT findings and at least 20 minute post-trauma amnesia (PTA), who were conscious at discharge, participated in this study. Based on operative intervention, the samples were divided into two groups: operative and nonoperative. Cognitive and aphasic deficits were inspected formally and pragmatic disorder was informally appraised at discharge., Results: The groups had no significant differences in aphasia incidence and language pragmatic impairment, though they were significantly distinctive in aphasia subcategories and cognitive deficit after trauma. Fluent aphasia was more common in both groups alike. In aphasia subcategories, however, transcortical sensory aphasia (TSA) in operative and anomia in nonoperative group were the most prevalent. Several variables appeared strikingly related to higher aphasia in operative groups as follows: moderate to severe injury, 18-35 and over 50 years of age, more than 1 week PTA, intracranial surgery of multiple lesions in left or bilateral hemisphere fronto-temporal cortex plus post-trauma cognitive and pragmatic impairments, and diffuse axonal injuries., Discussion: Almost certainly, meaningful drop of cognitive function post surgery roots back in significant loss of initial consciousness level. Related factors to postoperative aphasia suggest taking policies through surgery intervention. Discerning the indispensable contributions of neurosurgeons, neurolinguists, and neuroscientists, results inspire more clinical future studies., (Copyright © 2012 Elsevier B.V. All rights reserved.)

As the world grows less biologically diverse, it is becoming less linguistically and culturally diverse as well. Biologists estimate annual loss of species at 1,000 times or more greater than historic rates, and linguists predict that 50-90% of the world's languages will disappear by the end of this century. Prior studies indicate similarities in the geographic arrangement of biological and linguistic diversity, although conclusions have often been constrained by use of data with limited spatial precision. Here we use greatly improved datasets to explore the co-occurrence of linguistic and biological diversity in regions containing many of the Earth's remaining species: biodiversity hotspots and high biodiversity wilderness areas. Results indicate that these regions often contain considerable linguistic diversity, accounting for 70% of all languages on Earth. Moreover, the languages involved are frequently unique (endemic) to particular regions, with many facing extinction. Likely reasons for co-occurrence of linguistic and biological diversity are complex and appear to vary among localities, although strong geographic concordance between biological and linguistic diversity in many areas argues for some form of functional connection. Languages in high biodiversity regions also often co-occur with one or more specific conservation priorities, here defined as endangered species and protected areas, marking particular localities important for maintaining both forms of diversity. The results reported in this article provide a starting point for focused research exploring the relationship between biological and linguistic-cultural diversity, and for developing integrated strategies designed to conserve species and languages in regions rich in both.

The paper is devoted to the peculiarities of medical discourse in pathological anatomy as coherent speech and as a linguistic correlate of medical practice taking into account the analysis of its strategies and tactics. The purpose of the paper is to provide a multifaceted analysis of the speech strategies and tactics of pathological anatomy discourse and ways of their implementation. The main strategies of medical discourse in pathological anatomy are an anticipating strategy, a diagnosing strategy and an explaining one. The supporting strategies are pragmatic, conversational and a rhetorical one. The pragmatic strategy is implemented through contact establishing tactics, the conversational one - with the help of control tactics, the rhetorical one - with the help of attention correction tactics. The above mentioned tactics and strategies are used in the distinguishing of major, closely interrelated strategies: "the contact strategy" (to establish contact with a patient's relatives - phatic replicas of greeting and addressing) and "the strategy of explanation" (used in the practice of a pathologist for a detailed explanation of the reasons of a patient's death). The ethic aspect of speech conduct of a doctor-pathologist is analyzed.

Computational methods have revolutionized evolutionary biology. In this paper we explore the impact these methods are now having on our understanding of the forces that both affect the diversification of human languages and shape human cognition. We show how these methods can illuminate problems ranging from the nature of constraints on linguistic variation to the role that social processes play in determining the rate of linguistic change. Throughout the paper we argue that the cognitive sciences should move away from an idealized model of human cognition, to a more biologically realistic model where variation is central., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Language is the best example of a cultural evolutionary system, able to retain a phylogenetic signal over many thousands of years. The temporal stability (conservatism) of basic vocabulary is relatively well understood, but the stability of the structural properties of language (phonology, morphology, syntax) is still unclear. Here we report an extensive Bayesian phylogenetic investigation of the structural stability of numerous features across many language families and we introduce a novel method for analyzing the relationships between the "stability profiles" of language families. We found that there is a strong universal component across language families, suggesting the existence of universal linguistic, cognitive and genetic constraints. Against this background, however, each language family has a distinct stability profile, and these profiles cluster by geographic area and likely deep genealogical relationships. These stability profiles seem to show, for example, the ancient historical relationships between the Siberian and American language families, presumed to be separated by at least 12,000 years, and possible connections between the Eurasian families. We also found preliminary support for the punctuated evolution of structural features of language across families, types of features and geographic areas. Thus, such higher-level properties of language seen as an evolutionary system might allow the investigation of ancient connections between languages and shed light on the peopling of the world.

Human languages evolve continuously, and a puzzling problem is how to reconcile the apparent robustness of most of the deep linguistic structures we use with the evidence that they undergo possibly slow, yet ceaseless, changes. Is the state in which we observe languages today closer to what would be a dynamical attractor with statistically stationary properties or rather closer to a non-steady state slowly evolving in time? Here we address this question in the framework of the emergence of shared linguistic categories in a population of individuals interacting through language games. The observed emerging asymptotic categorization, which has been previously tested--with success--against experimental data from human languages, corresponds to a metastable state where global shifts are always possible but progressively more unlikely and the response properties depend on the age of the system. This aging mechanism exhibits striking quantitative analogies to what is observed in the statistical mechanics of glassy systems. We argue that this can be a general scenario in language dynamics where shared linguistic conventions would not emerge as attractors, but rather as metastable states.

The language sciences—Linguistics, Psycholinguistics, and Computational Linguistics—have not been broadly represented at the Cognitive Science Society meetings of the past 30 years, but they are an important part of the heart of cognitive science. This article discusses several major themes that have dominated the controversies and consensus in the study of language and suggests the most pressing issues of the future. These themes include differences among the language science disciplines in their view of numbers and symbols and of modular and distributed cognition, and the need for an increasing prominence of questions concerning language and the brain.

Darwinism appears in many more academic areas than just evolutionary biology. New disciplines are created out of its fusion with existing fields of study. However, this practise is criticised for a lack of evidence-based justification, and for adopting gene-oriented reductionism in the social sciences. This article briefly considers seven examples of new disciplines for which Darwinism has been appropriated. In each case, succinct background information precedes quotes provided for this purpose by a leading researcher.

As the only species that evolved to possess a language faculty, humans have been surprisingly generative in creating a diverse array of language systems. These systems vary in phonology, morphology, syntax, and written forms. Before the advent of modern brain-imaging techniques, little was known about how differences across languages are reflected in the brain. This chapter aims to provide an overview of an emerging area of research - cultural neurolinguistics - that examines systematic cross-cultural/crosslinguistic variations in the neural networks of languages. We first briefly describe general brain networks for written and spoken languages. We then discuss language-specific brain regions by highlighting differences in neural bases of different scripts (logographic vs. alphabetic scripts), orthographies (transparent vs. nontransparent orthographies), and tonality (tonal vs. atonal languages). We also discuss neural basis of second language and the role of native language experience in second-language acquisition. In the last section, we outline a general model that integrates culture and neural bases of language and discuss future directions of research in this area.

ASPM, a gene that regulates brain growth, has evolved considerably in the primate lineage that leads to humans. It continued to evolve even after the emergence of modern humans, with the latest ASPM variant arising about 6000 years ago somewhere in the Middle East. The new variant then proliferated within and outside this region, reaching higher incidences in the Middle East (37-52%) and in Europe (38-50%) than in East Asia (0-25%). Despite its apparent selective advantage, this variant does not seem to improve cognitive performance, at least not on standard IQ tests. At present, we can only say that it probably assists performance on a task that exhibited the same geographic expansion from a Middle Eastern origin roughly 6000 years ago. The closest match seems to be the invention of alphabetical writing, specifically the task of transcribing speech and copying texts into alphabetical script. Though more easily learned than ideographs, alphabetical characters place higher demands on mental processing, especially under premodern conditions (continuous text with little or no punctuation, real-time stenography, absence of automated assistance for publishing or copying, etc.). This task was largely delegated to scribes of various sorts who enjoyed privileged status and probably superior reproductive success. Such individuals may have served as vectors for spreading the new ASPM variant.

Natural language processing is the study of computer programs that can understand and produce human language. An important goal in the research to produce such technology is identifying the right meaning of words and phrases. In this paper, we give an overview of current research in three areas: (i) inducing word meaning; (ii) distinguishing different meanings of words used in context; and (iii) determining when the meaning of a phrase cannot straightforwardly be obtained from its parts. Manual construction of resources is labour intensive and costly and furthermore may not reflect the meanings that are useful for the task or data at hand. For this reason, we focus particularly on systems that use samples of language data to learn about meanings, rather than examples annotated by humans.

A linguistic analysis of a series of letters written by a young man who died by suicide to 1 friend over a period of 2 years prior to his death revealed several trends, including a decrease in negative emotion words and an increase in death words. The implication of these trends was discussed.

In the last 25 years, characterization of aphasia has shifted from descriptions of the language tasks that are impaired by brain damage to identification of the disrupted cognitive processes underlying language. At the same time advances in technology, including functional imaging, electrophysiologic studies, perfusion imaging, diffusion tensor imaging, and transcranial magnetic stimulation, have led to new insights regarding the relationships between language and the brain. These insights, together with computational models of language processes, converge on the view that a given language task relies on a complex set of cognitive processes and representations carried out by an intricate network of neural regions working together. Recovery from aphasia depends on restoration of tissue function or reorganization of the cognitive/neural network underlying language, which can be facilitated by a number of diverse interventions. The original research by the author reported in this article was supported by NIH R01 DC05375.

We constructed a connectionist model with multilayer perceptron networks for the simulation of word production errors in the Finnish language. Such errors occur as slips of the tongue in healthy subjects and even more often in aphasic patients suffering from brain damage. Word production errors are of theoretical interest as they open an avenue to inner workings of the language production system. Here we present our coding schemes for semantic and phoneme information of words, investigate the general properties of the model, and compare the results of the model against empirical naming error data from ten aphasic patients. The model was reasonable in simulating word production errors in this heterogeneous group of aphasic patients.

The world's language system is undergoing rapid change because of demographic trends, new technology, and international communication. These changes will affect both written and spoken communication. English may not be the dominant language of the future, and the need to be multilingual will be enhanced. Although many languages are going extinct, new ones are emerging in cities and extended social groups.

Pitch is used to signal different aspects of language such as speaker identity, intonation, emphatic stress, and word identity (as signaled by lexical tones). This article reviews research studies investigating hemispheric specialization of these pitch patterns in the context of two competing hypotheses. The functional hypothesis states that pitch patterns are lateralized to different hemispheres of the brain depending on their functions. Those pitch patterns that carry a greater linguistic load (e.g., lexical tones) are lateralized to the left hemisphere, while those that carry a less linguistic load (e.g., intonation patterns signaling affective moods) are lateralized to the right hemisphere. The alternative hypothesis, the acoustic hypothesis, states that all pitch patterns, regardless of their functions, are lateralized to one hemisphere (the right hemisphere in particular). Although most researchers support the functional hypothesis, a comprehensive review, which includes lesion, dichotic-listening, and functional imaging studies of different types of pitch patterns, does not support this view. Moreover, little evidence exists for the alternative hypothesis. Possible methodological problems of these studies, alternative hypotheses, and considerations for future research are noted., (Copyright 2002 Elsevier Science Inc.)