Recent studies of naturalistic face‐to‐face communication have demonstrated coordination patterns such as the temporal matching of verbal and non‐verbal behavior, which provides evidence for the proposal that verbal and non‐verbal communicative control derives from one system. In this study, we argue that the observed relationship between verbal and non‐verbal behaviors depends on the level of analysis. In a reanalysis of a corpus of naturalistic multimodal communication (Louwerse, Dale, Bard, & Jeuniaux, ), we focus on measuring the temporal patterns of specific (...) communicative behaviors in terms of their burstiness. We examined burstiness estimates across different roles of the speaker and different communicative modalities. We observed more burstiness for verbal versus non‐verbal channels, and for more versus less informative language subchannels. Using this new method for analyzing temporal patterns in communicative behaviors, we show that there is a complex relationship between verbal and non‐verbal channels. We propose a “temporal heterogeneity” hypothesis to explain how the language system adapts to the demands of dialog. (shrink)

Machery proposes that the construct of detracts from research progress. However, ignoring development also detracts from research progress. Developmental research has advanced our understanding of how concepts are acquired and thus is essential to a complete theory. We propose a framework that both accounts for development and holds great promise as a new direction for thinking about concepts.

Cognitive Science, Volume 46, Issue 8, August 2022.

Given that there is referential uncertainty (noise) when learning words, to what extent can forgetting filter some of that noise out, and be an aid to learning? Using a Cross Situational Learning model we find a U-shaped function of errors indicative of a “Goldilocks” zone of forgetting: an optimum store-loss ratio that is neither too aggressive or too weak, but just the right amount to produce better learning outcomes. Forgetting acts as a high-pass filter that actively deletes (part of) the (...) referential ambiguity noise, retains intended referents, and effectively amplifies the signal. The model achieves this performance without incorporating any specific cognitive biases of the type proposed in the constraints and principles account, and without any prescribed developmental changes in the underlying learning mechanism. Instead we interpret the model performance as more of a by-product of exposure to input, where the associative strengths in the lexicon grow as a function of linguistic experience in combination with memory limitations. The result adds a mechanistic explanation for the experimental evidence on spaced learning and, more generally, advocates integrating domain-general aspects of cognition, such as memory, in to the language acquisition process. (shrink)