The Growth of Children's Semantic and Phonological Networks: Insight From 10 Languages

Children tend to produce words earlier when they are connected to a variety of other words along the phonological and semantic dimensions. Though these semantic and phonological connectivity effects have been extensively documented, little is known about their underlying developmental mechanism. One possibility is that learning is driven by lexical network growth where highly connected words in the child's early lexicon enable learning of similar words. Another possibility is that learning is driven by highly connected words in the external learning environment, instead of highly connected words in the early internal lexicon. The present study tests both scenarios systematically in both the phonological and semantic domains across 10 languages. We show that phonological and semantic connectivity in the learning environment drives growth in both production- and comprehension-based vocabularies, even controlling for word frequency and length. This pattern of findings suggests a word learning process where children harness their statistical learning abilities to detect and learn highly connected words in the learning environment.     

The Role of Co-Occurrence Statistics in Developing Semantic Knowledge

The organization of our knowledge about the world into an interconnected network of concepts linked by relations profoundly impacts many facets of cognition, including attention, memory retrieval, reasoning, and learning. It is therefore crucial to understand how organized semantic representations are acquired. The present experiment investigated the contributions of readily observable environmental statistical regularities to semantic organization in childhood. Specifically, we investigated whether co-occurrence regularities with which entities or their labels more reliably occur together than with others (a) contribute to relations between concepts independently and (b) contribute to relations between concepts belonging to the same taxonomic category. Using child-directed speech corpora to estimate reliable co-occurrences between labels for familiar items, we constructed triads consisting of a target, a related distractor, and an unrelated distractor in which targets and related distractors consistently co-occurred (e.g., sock-foot), belonged to the same taxonomic category (e.g., sock-coat), or both (e.g., sock-shoe). We used an implicit, eye-gaze measure of relations between concepts based on the degree to which children (N = 72, age 4–7 years) looked at related versus unrelated distractors when asked to look for a target. The results indicated that co-occurrence both independently contributes to relations between concepts and contributes to relations between concepts belonging to the same taxonomic category. These findings suggest that sensitivity to the regularity with which different entities co-occur in children's environments shapes the organization of semantic knowledge during development. Implications for theoretical accounts and empirical investigations of semantic organization are discussed.     

Faster might not be better: Pictures may not elicit a stronger unconscious priming effect than words when modulated by semantic similarity

It has been suggested that unconscious semantic processing is stimulus-dependent, and that pictures might have privileged access to semantic content. Those findings led to the hypothesis that unconscious semantic priming effect for pictorial stimuli would be stronger as compared to verbal stimuli. This effect was tested on pictures and words by manipulating the semantic similarity between the prime and target stimuli. Participants performed a masked priming categorization task for either words or pictures with three semantic similarity conditions: strongly similar, weakly similar, and non-similar. Significant differences in reaction times were only found between strongly similar and non-similar and between weakly similar and non-similar, for both pictures and words, with faster overall responses for pictures as compared to words. Nevertheless, pictures showed no superior priming effect over words. This could suggest the hypothesis that even though semantic processing is faster for pictures, this does not imply a stronger unconscious priming effect.     

Empirical and modeling study of emotional state dynamics in social videogame paradigms

The objective of this work was to study the dynamics of human emotional states in the process of social interaction in a virtual environment. The previously developed for this purpose prototypes of the virtual actor (NPC) and its virtual environment simulator “Teleport” underwent significant re-design and modification. The experimental platform was re-implemented and used in experiments with college student participants, combining electromyography, emotion recognition in facial recordings and model-based game log analysis in a social videogame paradigm. Participants interacted with two virtual actors implemented based on the eBICA cognitive architecture (Samsonovich, 2013, 2018). Positive correlations were found between eBICA model predictions and participant affects extracted from their facial expressions and facial muscle activity. Affective dynamics of social phenomena, such as the establishment of partnership or an act of betrayal, were characterized and found consistent with the model predictions. Other findings include a gradually developing emotional reaction, possibly due to the integration of appraisals of game events. Overall, obtained results confirm the eBICA model, suggesting its further extension and refinement.     

汉语句子理解中语义分析与句法分析的关系

两个实验研究了中文句子理解中句法分析与语义分析的关系。实验1采用被试者自控阅读速度的方法,要求被试者对每个句子(合理句或不合理句)进行语法判断。结果表明,在歧义词(AW)和解歧词(DAW)上,合理句与不合理句的错误率存在显著差异,而反应时差异不显著。实验2研究了语境对句子理解的作用。结果表明,在有语境和无语境条件下,两类句子在歧义词和解歧词上的反应时,均有明显的差异。这些结果支持了句子理解中句法与语义加工的弱相互作用模型。     

Composition in distributional models of semantics

Vector-based models of word meaning have become increasingly popular in cognitive science. The appeal of these models lies in their ability to represent meaning simply by using distributional information under the assumption that words occurring within similar contexts are semantically similar. Despite their widespread use, vector-based models are typically directed at representing words in isolation, and methods for constructing representations for phrases or sentences have received little attention in the literature. This is in marked contrast to experimental evidence (e.g., in sentential priming) suggesting that semantic similarity is more complex than simply a relation between isolated words. This article proposes a framework for representing the meaning of word combinations in vector space. Central to our approach is vector composition, which we operationalize in terms of additive and multiplicative functions. Under this framework, we introduce a wide range of composition models that we evaluate empirically on a phrase similarity task.     

Comparison Types in the Semantic Extension of Diidxazá Body Part Terms

Body part terms (BPTs) are used extensively in Mesoamerican languages to name object parts. The process through which BPTs might be extended to refer to a part of an object and further serve as a relator in describing the relation between objects in space has often been attributed to metaphorical processes. This study proposes an alternative analysis following a Structure–Mapping Theory approach (Gentner, 1983, inter alia), based on data from Diidxazá (Isthmus Zapotec, Otomanguean) obtained through elicitation and experimental tasks. The data show that structure mapping does not depend on a 1:1 match of attributes; frequency of use shed light on principles that constrain the semantic extension of most BPTs; a core set of six BPTs are extended by abstraction of the set of intersecting axes of the body. The detailed nature of this study enables an analysis of the mental representations underlying the semantic extension of BPTs. This in turn elucidates on aspects of the relation between spatial language and spatial cognition. In addition, this study allows us to address questions about the categorial status of BPTs in Diidxazá and their lexicographic representation.     

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.     

Ontology relativized: Reply to Moulines

Ontology is taken by Moulines as supervenient on science: what kinds of things there are is determined by our well-confirmed theories. But the fact is that today, science provides us with a multiplicity of well-confirmed theories, each having its own ontological commitments. The modest, ontological form of reduction advocated by Moulines (this volume) restores hope of putting some ontological order in the “huge chaotic supermarket of science”. In this paper I show that any claim on the amount of order obtained by reduction does not only always remain “temporally qualified” but, worse for the reductionist with a taste for ontological order, that the very notion of orderliness must be relativized to the capacities and interests of knowers.     

启动测量方法在内隐社会认知研究中的应用

内隐社会认知是指在社会认知过程中虽然个体不能回忆某一过去经验,但这一经验潜在地对个体的行为和判断产生影响,其中启动测量方法是进行内隐社会认知研究最常用的一种方法。本文介绍了语义启动任务与评价启动任务这两种启动测量的方法及其内在机制,并从发展性、融合性、有效性、应用性四个方面总结与展望了在内隐社会认知领域中启动测量方法的发展趋势。