Most words in natural languages are polysemous; that is, they have related but different meanings in different contexts. This one‐to‐many mapping of form to meaning presents a challenge to understanding how word meanings are learned, represented, and processed. Previous work has focused on solutions in which multiple static semantic representations are linked to a single word form, which fails to capture important generalizations about how polysemous words are used; in particular, the graded nature of polysemous senses, and the flexibility and (...) regularity of polysemy use. We provide a novel view of how polysemous words are represented and processed, focusing on how meaning is modulated by context. Our theory is implemented within a recurrent neural network that learns distributional information through exposure to a large and representative corpus of English. Clusters of meaning emerge from how the model processes individual word forms. In keeping with distributional theories of semantics, we suggest word meanings are generalized from contexts of different word tokens, with polysemy emerging as multiple clusters of contextually modulated meanings. We validate our results against a human‐annotated corpus of polysemy focusing on the gradedness, flexibility, and regularity of polysemous sense individuation, as well as behavioral findings of offline sense relatedness ratings and online sentence processing. The results provide novel insights into how polysemy emerges from contextual processing of word meaning from both a theoretical and computational point of view. (shrink)

Recent theories on abstract concepts and words (ACs), such as Words As social Tools (WAT) (Borghi et al., 2019b) and Language is an Embodied Neuroenhancement and Scaffold (LENS) (Dove, 2019) have underlined the crucial role of both sensorimotor experience and language for ACs representation and use [see Dove et al. (2020), for a comparison]. Here we focus on the WAT view. WAT highlights the role of language, sociality, and inner grounding (interoception, metacognition) for ACs. Furthermore, WAT seeks to integrate a (...) developmental perspective with approaches focusing on conceptual use and brain representation. We briefly illustrate evidence coming from both clinical and non-clinical populations and identify areas where additional evidence that ACs evoke linguistic, social, and interoceptive experience is still needed. (shrink)

La tesis aborda uno de los temas centrales en la filosofía de la mente y las ciencias cognitivas: los conceptos como unidades básicas de la cognición humana. La tesis central que se defiende es que el contenido de los conceptos es determinado parcialmente por las comunidades a las que pertenecen los sujetos cognitivos, en la medida en la que dichas comunidades guían y constriñen las interacciones entre el sistema cognitivo conceptual y el entorno del que forma conceptos. La novedad de (...) la tesis es doble. Por una parte, cuestiona las teorías dominantes sobre el contenido de los conceptos —las teorías descriptivistas y las teorías naturalistas—, no solamente a partir de desafíos filosóficos que muestran sus limitaciones, sino también a partir de evidencia empírica sobre el efecto de las interacciones sociales en el contenido de los conceptos y, por tanto, en la cognición. Por otra parte, proporciona evidencia empírica sobre infantes ferales (i.e. niños salvajes), cuyo sistema cognitivo conceptual no ha recibido la guía de ninguna comunidad humana en sus interacciones con el entorno. Dicha evidencia permite sugerir que una explicación puramente naturalizada del contenido, sin la presencia de las comunidades, no puede explicar el desarrollo cognitivo conceptual de dichos infantes. Así, la tesis logra proponer un papel no trivial de las comunidades en el debate sobre la determinación del contenido semántico de los conceptos. (shrink)

In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at different developmental stages (five and four developmental stages for English and Spanish, respectively) using (...) the Word Maturity methodology to align different vector spaces. Second, we analyzed the amodal development of words through mixed-effects models with crossed random effects for words and variables using a continuous time metric. Third, the emotional norms were included as covariates in the statistical models. We evaluated more than 23,000 words, whose emotional norms were available for more than 10,000 words, in each language separately. Results showed a curve of amodal development with an increasing linear effect and a small quadratic deceleration. A relevant influence on the amodal development of words was found only for emotional valence (not for arousal), suggesting that positive words have an earlier amodal development and a less pronounced semantic change across early lifespan. (shrink)

A view that has been gaining prevalence over the past decade is that the human conceptual system is malleable, dynamic, context‐dependent, and task‐dependent, that is, flexible. Within the flexible conceptual representation framework, conceptual representations are constructed ad hoc, forming a different, idiosyncratic instantiation upon each occurrence. In this review, we scrutinize the neurocognitive literature to better understand the nature of this flexibility. First, we identify some key characteristics of these representations. Next, we consider how these flexible representations are constructed by (...) addressing some of the open questions in this framework: We review the age‐old question of how to reconcile flexibility with the apparent need for shareable stable definitions to anchor meaning and come to mutual understanding, as well as some newer questions we find critical, namely, the nature of relations among flexible representations, the role of feature saliency in activation, and the viability of all‐or‐none feature activations. We suggest replacing the debate about the existence of a definitional stable core that is obligatorily activated with a question of the degree and probability of activation of the information constituting a conceptual representation. We rely on published works to suggest that (1) prior featural salience matters, (2) feature activation may be graded, and (3) Bayesian updating of prior information according to current demands offers a viable account of how flexible representations are constructed. This proposal provides a theoretical mechanism for incorporating a changing momentary context into a constructed representation, while still preserving some of the concept's constituent meaning. (shrink)

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9‐year‐old children. The neural network was trained and validated in the child semantic space. (...) Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed‐effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed. (shrink)

According to a recent proposal, natural concepts are represented in an optimally designed similarity space, adhering to principles a skilled engineer would use for creatures with our perceptual and cognitive capacities. One key principle is that natural concepts should be easily learnable. While evidence exists for parts of this optimal design proposal, there has been no direct evidence linking naturalness to learning until now. This article presents results from a computational study on perceptual color space, demonstrating that naturalness indeed facilitates (...) learning. (shrink)