Two of the main theoretical approaches to the evolution of language are biolinguistics and usage-based approaches. Both are often conceptualized as belonging to seemingly irreconcilable “camps.” Biolinguistic approaches assume that the ability to acquire language is based on a language-specific genetic foundation. Usage-based approaches, on the other hand, stress the importance of domain-general cognitive capacities, social cognition, and interaction. However, there have been a number of recent developments in both paradigms which suggest that biolinguistic and usage-based approaches are actually moving (...) closer together. For example, theoretical advancements such as evo-devo and complex adaptive system theory have gained traction in the language sciences, leading to changed conceptions of issues like the relative influence of “nature” and “nurture.” In this paper, we outline points of convergence between current minimalist biolinguistic and usage-based approaches regarding four contentious issues: (1) modularity and domain specificity; (2) innateness and development; (3) cultural and biological evolution; and (4) knowledge of language and its description. We show that across both paradigms, researchers have come to increasingly embrace more complex views of these issues. They also have come to appreciate the view that biological and cultural evolution are closely intertwined, which lead to an increased amount of common ground between minimalist biolinguistics and usage-based approaches. (shrink)

Several philosophers have expressed concerns with some recent uses of the term ‘cognition’. Underlying a number of these concerns are claims that cognition is only located in the brain and that no compelling case has been made to use ‘cognition’ in any way other than as a cause of behavior that is representational in nature. These concerns center on two primary misapprehensions: First, that some adherents of dynamical cognitive science think DCS implies the thesis of extended cognition and the rejection (...) of representation, and second, that cognition is mistakenly equated with behavior. We make three points in response to these claims: First, there is no thoroughly entrenched conception of cognition as distinct from behavior that is being illegitimately disregarded. Second, we present Shapiro’s exposition of dynamical systems theory as revealing a misunderstanding of the way that dynamical models are used in explanations of cognition and related phenomena. Accordingly, a proper conception of DCS’s methods facilitates an appreciation of extended cognition as a legitimate phenomenon of scientific investigation. Finally, we demonstrate that practicing cognitive scientists and psychologists are far more pluralistic in the phenomena they apply ‘cognition’ to than is suggested by some. At the heart of our disagreement with these concerned folks is that although we think it likely that some cognitive phenomena are representational, non-extended, and only in-between the ears, we also think there are good conceptual and empirical reasons to believe that many cognitive phenomena are non-representational, extended, and not confined to the brain. (shrink)

Learning in intelligent systems is a result of direct or indirect interaction with the environment. Humans can learn by way of different states of (inter-)action such as the execution or the imagery of an action, but their unique potential to induce brain-related as well as mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., execution and imagery in terms of physical and mental practice) and their contribution to the learning (...) of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to the motor action system. These findings provide valuable insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process, and to jointly contribute to developing intelligent cognitive systems and their application in robotics, rehabilitation, or sports. (shrink)