A Study of Using Metaphoric and Beat Gestures with Motion-Based and Non-Motion-Based Metaphors during Retelling Stories.

In this paper, we classify metaphors into four categories: motion-based metaphors, static space-based metaphors, static object-based metaphors, and static event-based metaphors. Then, a study that investigated the use of gestures with these types of metaphors is reported. The aim was to examine how these types of metaphors are used with metaphoric and beat gestures during the process of re-telling stories. The participants of the study listened to three audio stories. Each story contained two motion-based metaphors, two static space-based metaphors, two static object-based metaphors, and two static event-based metaphors. After listening to each story, they had to retell the stories in front of a camera. The videos were analyzed to determine the number of metaphoric gestures and beat gestures that had been used by participants during the retelling of the stories. The results showed that the highest number of metaphoric gestures had been used with static space-based metaphors. This was followed by motion-based metaphors, static object-based metaphors, and static event-based metaphors, respectively. On the other hand, the highest number of beat gestures was used with static event-based metaphors. These findings indicate that the use of metaphoric gestures and beat gestures accompanying metaphors is highly dependent on the spatial and motoric properties of the base of the metaphors, which supports the idea of embodied metaphor comprehension.

Simpler grammar, larger vocabulary: How population size affects language.

Languages with many speakers tend to be structurally simple while small communities sometimes develop languages with great structural complexity. Paradoxically, the opposite pattern appears to be observed for non-structural properties of language such as vocabulary size. These apparently opposite patterns pose a challenge for theories of language change and evolution. We use computational simulations to show that this inverse pattern can depend on a single factor: ease of diffusion through the population. A population of interacting agents was arranged on a network, passing linguistic conventions to one another along network links. Agents can invent new conventions, or replicate conventions that they have previously generated themselves or learned from other agents. Linguistic conventions are either Easy or Hard to diffuse, depending on how many times an agent needs to encounter a convention to learn it. In large groups, only linguistic conventions that are easy to learn, such as words, tend to proliferate, whereas small groups where everyone talks to everyone else allow for more complex conventions, like grammatical regularities, to be maintained. Our simulations thus suggest that language, and possibly other aspects of culture, may become simpler at the structural level as our world becomes increasingly interconnected.

Acceptability of Dative Argument Structure in Spanish: Assessing Semantic and Usage-Based Factors.

Multiple constraints, including semantic, lexical, and usage-based factors, have been shown to influence dative alternation across different languages. This work explores whether fine-grained statistics and semantic properties of the verb affect the acceptability of dative constructions in Spanish. First, a corpus analysis reveals that verbs of different semantic classes occur naturally in alternative dative constructions, a pattern quite different from English. The fact that dative alternation appears independent of semantic classes challenges traditional semantic-based approaches. Second, acceptability rating tasks reveal that dative constructions containing highly entrenched word combinations and frequent word order are judged more acceptable regardless of the verbs' semantics. The results are interpreted in favor of usage-based accounts: Acceptability of dative constructions may be language-specific and depend on patterns of use and conventionalization.

Examining the Link between Math Anxiety and Math Performance in Colombian Students / Examinando la Relación entre la Ansiedad Matemática y el Desempeño Matemático en Estudiantes Colombianos / Examinando a Relação entre a Ansiedade Matemática e o Desempenho Matemático em Estudantes Colombianos

This study examines the link between math anxietyand math performance in a group of Colombian students. A total of 296 students between 8 and 16 years of age took part in this study. Analyses by gender and grade were conducted, while controlling for other types of anxiety (i.e., general and test anxiety). In line with that reported in other countries, a negative correlation was found between performance in mathematics and math anxiety. Importantly, this trend was stronger in girls than in boys. Given the limited number of studies exploring the relationship between math anxiety and math performance in Latin America and, particularly, in Colombia, this study fills an important gap in the literature. The results are particularly relevant in view of the poor performance of Colombian students in mathematics, revealed by the most recent PISA reports.

El presente estudio examina la relación entre la ansiedad matemática y el desempeño matemático, en un grupo de estudiantes colombianos. Un total de 296 estudiantes entre 8 y 16 años de edad participaron en la investigación. Se realizaron análisis por género y grado escolar, controlando por otros tipos de ansiedad (i.e., general y relacionada con exámenes). En línea con lo reportado en otros países, se encontró una correlación negativa entre el desempeño en matemática y la ansiedad matemática. Aún más importante, esta tendencia fue mayor en las niñas que en los niños. Dados los pocos estudios que han explorado la relación entre ansiedad matemática y desempeño matemático en Latinoamérica y, particularmente, en Colombia, este estudio llena un vacío importante. Los resultados son particularmente relevantes a la luz del pobre desempeño de los estudiantes colombianos en matemáticas, revelado recientemente por las pruebas PISA.

O presente estudo examina a relação entre a ansiedade matemática e o desempenho matemático num grupo de estudantes colombianos. Um total de 296 estudantes entre 8 e 16 anos participaram da pesquisa. Realizaram-se análise por gênero e grau escolar, controlando por outros tipos de ansiedade (por exemplo, geral e relacionada com exames). Em consonância com o relatado por outros países, constatou-se uma correlação negativa entre o desempenho em matemática e a ansiedade matemática. Ainda mais importante, essa tendência foi maior nas meninas do que nos meninos. Tendo em vista os poucos estudos que exploram a relação entre ansiedade matemática e desempenho matemático na América Latina e, particularmente, na Colômbia, este estudo preenche um vazio importante. Os resultados são relevantes à luz do pobre desempenho dos estudantes colombianos em matemáticas, revelado recentemente pelas provas do Programa Internacional de Avaliação de Estudantes (Pisa, por sua sigla em inglês).

How we think about depression: The role of linguistic framing / Como pensamos sobre la depresión: el rol del encuadre lingüístico

Descriptions of emotional disorders vary according to cultural and historical context. Framing mental illness as a disease - as opposed to being a consequence of psychosocial factors - has been proposedías a strategy to fight stigma in recent years. Here we combine two studies, a corpus analysis and an experimental survey, to explore this issue in the case of Spanish. First, we conducted a corpus analysis to investigate the patterns of linguistic framing of depression -including disease like descriptions and metaphorical frames using data from Latin American countries. Two main patterns were identified: (1) depression is frequently framedías a brain disease. In line with medicalization trends observed worldwide, this pattern has increased over time. (2) The data showed that depression is also metaphorically construedías a place in space or as an opponent. Second, we investigated whether the instantiation of subtle linguis tic cues influences people's perception of a description of a hypothetical case of depression. A survey experiment conducted among Colombian students revealed that when depression was framedías a disease, the participants' perception of the depressed person's responsibility was reduced. Moreover, disease-like descriptions and metaphorical frames influenced participants' initial interpretations of the role of social causal factors.

Las descripciones de los desórdenes emocionales varian de acuerdo a la cultura y los contextos históricos. Recientemente, se ha propuesto que enmarcar lingüisticamente estos desórdenes como enfermedades - en contraposición a consecuencias de factores psicosociales - podría ser una estrategia para combatir estigmas. En este trabajo combinamos un análisis del corpus lingüistico y un estudio experimental para explorar las caracteristicas y consecuencias del enmarque lingüistico en español para el caso de la depresión. En primer lugar investigamos la frecuencia de distintos patrones de enmarque - incluyendo enmarque de enfermedad y otros enmarques metafóricos usando datos provenientes de distintos paises de Latinoamérica. Dos patrones emergen: (a) La depresión es frecuentemente enmarcada como una enfermedad cerebral y (b) La depresión se describe metafóricamente como un lugar en el espacio o un oponente. En segundo lugar, investigamos si el enmarque lingüistico afecta la percepción de un caso hipotético de depresión. Una encuesta a estudiantes colombianos reveló que cuando la depresión se describe como una enfermedad, los participantes tienden a percibir una menor responsabilidad de la persona afectada. Por otra parte, los resultados revelan que los distintos enmarques metafóricos estudiados inciden en las interpretaciones de los participantes sobre el rol de las causas sociales.

Biological adaptations for functional features of language in the face of cultural evolution.

Although there may be no true language universals, it is nonetheless possible to discern several family resemblance patterns across the languages of the world. Recent work on the cultural evolution of language indicates the source of these patterns is unlikely to be an innate universal grammar evolved through biological adaptations for arbitrary linguistic features. Instead, it has been suggested that the patterns of resemblance emerge because language has been shaped by the brain, with individual languages representing different but partially overlapping solutions to the same set of nonlinguistic constraints. Here, we use computational simulations to investigate whether biological adaptation for functional features of language, deriving from cognitive and communicative constraints, may nonetheless be possible alongside rapid cultural evolution. Specifically, we focus on the Baldwin effect as an evolutionary mechanism by which previously learned linguistic features might become innate through natural selection across many generations of language users. The results indicate that cultural evolution of language does not necessarily prevent functional features of language from becoming genetically fixed, thus potentially providing a particularly informative source of constraints on cross-linguistic resemblance patterns.

Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift.

Scientists studying how languages change over time often make an analogy between biological and cultural evolution, with words or grammars behaving like traits subject to natural selection. Recent work has exploited this analogy by using models of biological evolution to explain the properties of languages and other cultural artefacts. However, the mechanisms of biological and cultural evolution are very different: biological traits are passed between generations by genes, while languages and concepts are transmitted through learning. Here we show that these different mechanisms can have the same results, demonstrating that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright-Fisher model of genetic drift. This simple learning mechanism thus provides a justification for the use of models of genetic drift in studying language evolution. In addition to providing an explicit connection between biological and cultural evolution, this allows us to define a 'neutral' model that indicates how languages can change in the absence of selection at the level of linguistic variants. We demonstrate that this neutral model can account for three phenomena: the s-shaped curve of language change, the distribution of word frequencies, and the relationship between word frequencies and extinction rates.

The biological and cultural foundations of language.

A key challenge for theories of language evolution is to explain why language is the way it is and how it came to be that way. It is clear that how we learn and use language is governed by genetic constraints. However, the nature of these innate constraints has been the subject of much debate. Although many accounts of language evolution have emphasized the importance of biological adaptations specific to language, we discuss evidence from computer simulations pointing to strong restrictions on such adaptations. Instead, we argue that processes of cultural evolution have been the primary factor affecting the evolution of linguistic structure, suggesting that the genetic constraints on language largely predate the emergence of language itself.

The evolution of frequency distributions: relating regularization to inductive biases through iterated learning.

The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this paper we explore how regular linguistic structures can emerge from language evolution by iterated learning, in which one person's linguistic output is used to generate the linguistic input provided to the next person. We use a model of iterated learning with Bayesian agents to show that this process can result in regularization when learners have the appropriate inductive biases. We then present three experiments demonstrating that simulating the process of language evolution in the laboratory can reveal biases towards regularization that might not otherwise be obvious, allowing weak biases to have strong effects. The results of these experiments suggest that people tend to regularize inconsistent word-meaning mappings, and that even a weak bias towards regularization can allow regular languages to be produced via language evolution by iterated learning.

Restrictions on biological adaptation in language evolution.

Language acquisition and processing are governed by genetic constraints. A crucial unresolved question is how far these genetic constraints have coevolved with language, perhaps resulting in a highly specialized and species-specific language "module," and how much language acquisition and processing redeploy preexisting cognitive machinery. In the present work, we explored the circumstances under which genes encoding language-specific properties could have coevolved with language itself. We present a theoretical model, implemented in computer simulations, of key aspects of the interaction of genes and language. Our results show that genes for language could have coevolved only with highly stable aspects of the linguistic environment; a rapidly changing linguistic environment does not provide a stable target for natural selection. Thus, a biological endowment could not coevolve with properties of language that began as learned cultural conventions, because cultural conventions change much more rapidly than genes. We argue that this rules out the possibility that arbitrary properties of language, including abstract syntactic principles governing phrase structure, case marking, and agreement, have been built into a "language module" by natural selection. The genetic basis of human language acquisition and processing did not coevolve with language, but primarily predates the emergence of language. As suggested by Darwin, the fit between language and its underlying mechanisms arose because language has evolved to fit the human brain, rather than the reverse.

Word chunk frequencies affect the processing of pronominal object-relative clauses.

We present experimental support for the view that fine-grained statistical information may play a crucial role in the processing of centre-embedded linguistic structure. Using both offline and online methods, we show that the processing of pronominal object-relative clauses is influenced by the frequency of co-occurrence of the word combinations (chunks) forming the clause. We use materials that are controlled for capacity-based factors that have been previously shown to influence comprehension of relative clauses. The results suggest that, other factors being equal, the frequency of the word chunk forming the clause affects processing difficulty. Analyses of the data indicate that the results cannot be explained by differential access to individual lexical items. Following recent constructivist approaches, we argue that frequency of co-occurrence influences the chunking mechanism by which multiword sequences may become fused into processing units that are easier to access.

Inefficient conjunction search made efficient by concurrent spoken delivery of target identity.

Visual search based on a conjunction of two features typically elicits reaction times that increase linearly as a function of the number of distractors, whereas search based on a single feature is essentially unaffected by set size. These and related findings have often been interpreted as evidence of a serial search stage that follows a parallel search stage. However, a wide range of studies has been showing a form of blending of these two processes. For example, when a spoken instruction identifies the conjunction target concurrently with the visual display, the effect of set size is significantly reduced, suggesting that incremental linguistic processing of the first feature adjective and then the second feature adjective may facilitate something approximating a parallel extraction of objects during search for the target. Here, we extend these results to a variety of experimental designs. First, we replicate the result with a mixed-trials design (ruling out potential strategies associated with the blocked design of the original study). Second, in a mixed-trials experiment, the order of adjective types in the spoken query varies randomly across conditions. In a third experiment, we extend the effect to a triple-conjunction search task. A fourth (control) experiment demonstrates that these effects are not due to an efficient odd-one-out search that ignores the linguistic input. This series of experiments, along with attractor-network simulations of the phenomena, provide further evidence toward understanding linguistically mediated influences in real-time visual search processing.

Elman topology with sigma-pi units: an application to the modeling of verbal hallucinations in schizophrenia.

The development of neural network models has greatly enhanced the comprehension of cognitive phenomena. Here, we show that models using multiplicative processing of inputs are both powerful and simple to train and understand. We believe they are valuable tools for cognitive explorations. Our model can be viewed as a subclass of networks built on sigma-pi units and we show how to derive the Kronecker product representation from the classical sigma-pi unit. We also show how the connectivity requirements of the Kronecker product can be relaxed considering statistical arguments. We use the multiplicative network to implement what we call an Elman topology, that is, a simple recurrent network (SRN) that supports aspects of language processing. As an application, we model the appearance of hallucinated voices after network damage, and show that we can reproduce results previously obtained with SRNs concerning the pathology of schizophrenia.

Uncovering the richness of the stimulus: structure dependence and indirect statistical evidence.

The poverty of stimulus argument is one of the most controversial arguments in the study of language acquisition. Here we follow previous approaches challenging the assumption of impoverished primary linguistic data, focusing on the specific problem of auxiliary (AUX) fronting in complex polar interrogatives. We develop a series of corpus analyses of child-directed speech showing that there is indirect statistical information useful for correct auxiliary fronting in polar interrogatives and that such information is sufficient for distinguishing between grammatical and ungrammatical generalizations, even in the absence of direct evidence. We further show that there are simple learning devices, such as neural networks, capable of exploiting such statistical cues, producing a bias toward correct AUX questions when compared to their ungrammatical counterparts. The results suggest that the basic assumptions of the poverty of stimulus argument may need to be reappraised.