Russian-language neurosemantics: Clustering of word meaning and sense from oral narratives

This article is a part of a large-scale brain mapping project aimed at finding the relations among semantic categories in oral Russian-language texts and brain activity as measured using functional magnetic resonance imaging (fMRI). The goal of present study in particular is to examine the nature of lexical semantic relations and find an appropriate lexical space, homeomorphic to the activation patterns in the brain. Participants were presented with oral narratives, which described significant social issues from the first-person perspective. Stimuli were annotated using a dictionary and a vector approach. Results show that fMRI signal and clusters of related words have similar patterns of brain activation across participants. Results also show that annotation by a list of features more strongly contributes to prediction of the observed activation patterns. Findings confirm the hypothesis of situational semantic representation in the brain.     

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.     

The missing link between faces and names: Evidence from Alzheimer's disease patients

Retrieval of proper names is a cause of concern and complaint among elderly adults and it is an early symptom of patients suffering from neurodegenerative diseases such as Alzheimer's disease (AD). While it is well established that AD patients have deficits of proper name retrieval, the nature of such impairment is not yet fully understood. Specifically, it is unknown whether this deficit is due to a degradation of the links between faces and proper names, or due to deficits in intentionally accessing and retrieving proper names from faces. Here, we aim to investigate the integrity of the links between famous faces and proper names in AD while minimizing the impact of the explicit retrieval. We compare the performances of AD patients and elderly controls in a face-name priming task. We assess the integrity of the link between faces and names at two different levels: identity level - the name and face belong to the same person; and semantic level - the name and face belong to the same category (e.g., politicians). Our results reveal that AD patients compared with controls show intact semantic priming but reduced priming for person identity. This suggests that the deficits in intentionally retrieving proper names in AD are the result of a partial disruption of the network at the identity level, i.e., the links between known faces and proper names.     

Monotone Quantifiers Emerge via Iterated Learning

Natural languages exhibit many semantic universals, that is, properties of meaning shared across all languages. In this paper, we develop an explanation of one very prominent semantic universal, the monotonicity universal. While the existing work has shown that quantifiers satisfying the monotonicity universal are easier to learn, we provide a more complete explanation by considering the emergence of quantifiers from the perspective of cultural evolution. In particular, we show that quantifiers satisfy the monotonicity universal evolve reliably in an iterated learning paradigm with neural networks as agents.