Frequency and Chunking in Derived Words: A Parametric fMRI Study.

In usage-based linguistic theories, the assumption that high-frequency language strings are mentally represented as unitary chunks has been invoked to account for a wide range of phenomena. However, neurocognitive evidence in support of this assumption is still lacking. In line with Gestalt psychological assumptions, we propose that a language string qualifies as a chunk if the following two conditions are simultaneously satisfied: The perception of the whole string does not involve strong activation of its individual component parts, but the component parts in isolation strongly evoke the whole. Against this background, we explore the relationship between different frequency metrics and the chunk status of derived words (e.g., "government," "worthless") in a masked visual priming experiment with two conditions of interest. One condition investigates "whole-to-part" priming (worthless-WORTH), whereas the other one analyzes "part-to-whole" priming (tear-TEARLESS). Both conditions combine mixed-effects regression analyses of lexical decision RTs with a parametric fMRI design. Relative frequency (the frequency of the whole word relative to that of its onset-embedded part) emerges as the only frequency metric to correlate with chunk status in behavioral terms. The fMRI results show that relative frequency modulates activity in regions that have been related to morphological (de)composition or general task performance difficulty (notably left inferior frontal areas) and in regions associated with competition between whole, undecomposed words (right inferior frontal areas). We conclude that relative frequency affects early stages of processing, thereby supporting the usage-based concept of frequency-induced chunks.

Shared neural and cognitive mechanisms in action and language: The multiscale information transfer framework.

This review compares how humans process action and language sequences produced by other humans. On the one hand, we identify commonalities between action and language processing in terms of cognitive mechanisms (e.g., perceptual segmentation, predictive processing, integration across multiple temporal scales), neural resources (e.g., the left inferior frontal cortex), and processing algorithms (e.g., comprehension based on changes in signal entropy). On the other hand, drawing on sign language with its particularly strong motor component, we also highlight what differentiates (both oral and signed) linguistic communication from nonlinguistic action sequences. We propose the multiscale information transfer framework (MSIT) as a way of integrating these insights and highlight directions into which future empirical research inspired by the MSIT framework might fruitfully evolve. This article is categorized under: Psychology > Language Linguistics > Language in Mind and Brain Psychology > Motor Skill and Performance Psychology > Prediction.