Manual actions are a hallmark of humanness. Their underlying neural circuitry gives rise to species-specific skills and interacts with language processes. In particular, multiple studies show that hand-related expressions - verbal units evoking manual activity - variously affect concurrent manual actions, yielding apparently controversial results (interference, facilitation, or null effects) in varied time windows. Through a systematic review of 108 experiments, we show that such effects are driven by several factors, such as the level of verbal processing, action complexity, and the time-lag between linguistic and motor processes. We reconcile key empirical patterns by introducing the Hand-Action-Network Dynamic Language Embodiment (HANDLE) model, an integrative framework based on neural coupling dynamics and predictive-coding principles. To conclude, we assess HANDLE against the backdrop of other action-cognition theories, illustrate its potential applications to understand high-level deficits in motor disorders, and discuss key challenges for further development. In sum, our work aligns with the 'pragmatic turn', moving away from passive and static representationalist perspectives to a more dynamic, enactive, and embodied conceptualization of cognitive processes.
Keywords: Enactive cognition; Hand-related language; Language embodiment; Manual-action networks; Predictive coding.
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