The organization and dissolution of semantic-conceptual knowledge: Is the ‘amodal hub’ the only plausible model?

In recent years, the anatomical and functional bases of conceptual activity have attracted a growing interest. In particular, Patterson and Lambon-Ralph have proposed the existence, in the anterior parts of the temporal lobes, of a mechanism (the 'amodal semantic hub') supporting the interactive activation of semantic representations in all modalities and for all semantic categories. The aim of then present paper is to discuss this model, arguing against the notion of an 'amodal' semantic hub, because we maintain, in agreement with the Damasio's construct of 'higher-order convergence zone', that a continuum exists between perceptual information and conceptual representations, whereas the 'amodal' account views perceptual informations only as a channel through which abstract semantic knowledge can be activated. According to our model, semantic organization can be better explained by two orthogonal higher-order convergence systems, concerning, on one hand, the right vs. left hemisphere and, on the other hand, the ventral vs. dorsal processing pathways. This model posits that conceptual representations may be mainly based upon perceptual activities in the right hemisphere and upon verbal mediation in the left side of the brain. It also assumes that conceptual knowledge based on the convergence of highly processed visual information with other perceptual data (and mainly concerning living categories) may be bilaterally represented in the anterior parts of the temporal lobes, whereas knowledge based on the integration of visual data with action schemata (namely knowledge of actions, body parts and artefacts) may be more represented in the left fronto-temporo-parietal areas.     

Processing of Numerical and Proportional Quantifiers

Quantifier expressions like “many” and “at least” are part of a rich repository of words in language representing magnitude information. The role of numerical processing in comprehending quantifiers was studied in a semantic truth value judgment task, asking adults to quickly verify sentences about visual displays using numerical (at least seven, at least thirteen, at most seven, at most thirteen) or proportional (many, few) quantifiers. The visual displays were composed of systematically varied proportions of yellow and blue circles. The results demonstrated that numerical estimation and numerical reference information are fundamental in encoding the meaning of quantifiers in terms of response times and acceptability judgments. However, a difference emerges in the comparison strategies when a fixed external reference numerosity (seven or thirteen) is used for numerical quantifiers, whereas an internal numerical criterion is invoked for proportional quantifiers. Moreover, for both quantifier types, quantifier semantics and its polarity (positive vs. negative) biased the response direction (accept/reject). Overall, our results indicate that quantifier comprehension involves core numerical and lexical semantic properties, demonstrating integrated processing of language and numbers.     

How useful are corpus-based methods for extrapolating psycholinguistic variables?

Subjective ratings for age of acquisition, concreteness, affective valence, and many other variables are an important element of psycholinguistic research. However, even for well-studied languages, ratings usually cover just a small part of the vocabulary. A possible solution involves using corpora to build a semantic similarity space and to apply machine learning techniques to extrapolate existing ratings to previously unrated words. We conduct a systematic comparison of two extrapolation techniques: k-nearest neighbours, and random forest, in combination with semantic spaces built using latent semantic analysis, topic model, a hyperspace analogue to language (HAL)-like model, and a skip-gram model. A variant of the k-nearest neighbours method used with skip-gram word vectors gives the most accurate predictions but the random forest method has an advantage of being able to easily incorporate additional predictors. We evaluate the usefulness of the methods by exploring how much of the human performance in a lexical decision task can be explained by extrapolated ratings for age of acquisition and how precisely we can assign words to discrete categories based on extrapolated ratings. We find that at least some of the extrapolation methods may introduce artefacts to the data and produce results that could lead to different conclusions that would be reached based on the human ratings. From a practical point of view, the usefulness of ratings extrapolated with the described methods may be limited.     

Simple Co‐Occurrence Statistics Reproducibly Predict Association Ratings

What determines human ratings of association? We planned this paper as a test for association strength (AS) that is derived from the log likelihood that two words co‐occur significantly more often together in sentences than is expected from their single word frequencies. We also investigated the moderately correlated interactions of word frequency, emotional valence, arousal, and imageability of both words (r's ≤ .3). In three studies, linear mixed effects models revealed that AS and valence reproducibly account for variance in the human ratings. To understand further correlated predictors, we conducted a hierarchical cluster analysis and examined the predictors of four clusters in competitive analyses: Only AS and word2vec skip‐gram cosine distances reproducibly accounted for variance in all three studies. The other predictors of the first cluster (number of common associates, (positive) point‐wise mutual information, and word2vec CBOW cosine) did not reproducibly explain further variance. The same was true for the second cluster (word frequency and arousal); the third cluster (emotional valence and imageability); and the fourth cluster (consisting of joint frequency only). Finally, we discuss emotional valence as an important dimension of semantic space. Our results suggest that a simple definition of syntagmatic word contiguity (AS) and a paradigmatic measure of semantic similarity (skip‐gram cosine) provide the most general performance‐independent explanation of association ratings.     

平衡蒙汉双语者词汇与物理位置空间信息的语义表征

采用空间词不对称判断与Simon任务混合范式考察平衡蒙汉双语者词汇与物理位置空间信息的语义表征特点。实验一以平衡蒙汉双语者为被试,发现Simon效应所受影响在蒙汉语言间无差异。实验二以蒙-汉-英三语者为被试,发现Simon效应所受影响在汉语英语间、蒙语英语间有差异。本研究表明,平衡双语者词汇空间信息与物理位置空间信息存在共享语义表征,语言熟练程度影响一语和二语与共享表征的联结强度,验证了修正层级模型。     

Two theories of consciousness: Semantic pointer competition vs. information integration

Consciousness results from three mechanisms: representation by firing patterns in neural populations, binding of representations into more complex representations called semantic pointers, and competition among semantic pointers to capture the most important aspects of an organism’s current state. We contrast the semantic pointer competition (SPC) theory of consciousness with the hypothesis that consciousness is the capacity of a system to integrate information (IIT). We describe computer simulations to show that SPC surpasses IIT in providing better explanations of key aspects of consciousness: qualitative features, onset and cessation, shifts in experiences, differences in kinds across different organisms, unity and diversity, and storage and retrieval.     

A review of literature on the link between action observation and action language: advancing a shared semantic theory

Understanding each other is a core concept of social cohesion and, consequently, has immense value in human society. Importantly, shared information leading to cohesion can come from two main sources: observed action and/or language (word) processing. In this paper, we propose a theoretical framework for the link between action observation and action verb processing. Based on the activation of common semantic representations of actions through semantic resonance, this model can account for the neurophysiological, behavioral and neuropsychological domains in the link between action observation and language. Semantic resonance is hypothesized to play a role beyond that of the mere observation of others and can benefit future studies trying to connect action production and language.     

Characterizing the Dynamics of Learning in Repeated Reference Games

The language we use over the course of conversation changes as we establish common ground and learn what our partner finds meaningful. Here we draw upon recent advances in natural language processing to provide a finer-grained characterization of the dynamics of this learning process. We release an open corpus (>15,000 utterances) of extended dyadic interactions in a classic repeated reference game task where pairs of participants had to coordinate on how to refer to initially difficult-to-describe tangram stimuli. We find that different pairs discover a wide variety of idiosyncratic but efficient and stable solutions to the problem of reference. Furthermore, these conventions are shaped by the communicative context: words that are more discriminative in the initial context (i.e., that are used for one target more than others) are more likely to persist through the final repetition. Finally, we find systematic structure in how a speaker's referring expressions become more efficient over time: Syntactic units drop out in clusters following positive feedback from the listener, eventually leaving short labels containing open-class parts of speech. These findings provide a higher resolution look at the quantitative dynamics of ad hoc convention formation and support further development of computational models of learning in communication.     

Acquisition of the Meaning of the Word Orange Requires Understanding of the Meanings of Red,Pink, and Purple: Constructing a Lexicon as a Connected System

This research investigated how children build up the language-specific system of the color lexicon, examining factors that play important roles for the construction of an adult-like color lexicon. We had 3-, 4-, and 5-year-old Japanese-speaking children and adults (n = 20, 18, 19, and 19, respectively) produce names for 93 color swatches. The results showed that children of all ages were able to apply most of the chromatic words to the colors close to the center of each category, but even 5-year-olds struggle to delineate the boundaries between the words. Furthermore, the model analyses revealed that broad-covering and high-frequency words are mapped to the center of the lexical category earlier. However, cross-individual consistency in adults' use contributed most strongly for the adult-like boundary delineation. The results suggest that the process of system construction consists of at least two steps (i.e., mapping words to their category center and finding appropriate boundaries between neighboring words), with the quantity and the quality of the input contributing differently to the steps.