Cognitive science is experiencing a pragmatic turn away from the traditional representation-centered framework toward a view that focuses on understanding cognition as "enactive." This enactive view holds that cognition does not produce models of the world but rather subserves action as it is grounded in sensorimotor skills. In this volume, experts from cognitive science, neuroscience, psychology, robotics, and philosophy of mind assess the foundations and implications of a novel action-oriented view of cognition. Their contributions and supporting experimental evidence show that (...) an enactive approach to cognitive science enables strong conceptual advances, and the chapters explore key concepts for this new model of cognition. The contributors discuss the implications of an enactive approach for cognitive development; action-oriented models of cognitive processing; action-oriented understandings of consciousness and experience; and the accompanying paradigm shifts in the fields of philosophy, brain science, robotics, and psychology. ContributorsMoshe Bar, Lawrence W. Barsalov, Olaf Blanke, Jeannette Bohg, Martin V. Butz, Peter F. Dominey, Andreas K. Engel, Judith M. Ford, Karl J. Friston, Chris D. Frith, Shaun Gallagher, Antonia Hamilton, Tobias Heed, Cecilia Heyes, Elisabeth Hill, Matej Hoffmann, Jakob Hohwy, Bernhard Hommel, Atsushi Iriki, Pierre Jacob, Henrik Jörntell, Jürgen Jost, James Kilner, Günther Knoblich, Peter König, Danica Kragic, Miriam Kyselo, Alexander Maye, Marek McGann, Richard Menary, Thomas Metzinger, Ezequiel Morsella, Saskia Nagel, Kevin J. O'Regan, Pierre-Yves Oudeyer, Giovanni Pezzulo, Tony J. Prescott, Wolfgang Prinz, Friedemann Pulvermüller, Robert Rupert, Marti Sanchez-Fibla, Andrew Schwartz, Anil K. Seth, Vicky Southgate, Antonella Tramacere, John K. Tsotsos, Paul F. M. J. Verschure, Gabriella Vigliocco, Gottfried Vosgerau. (shrink)

An action-oriented perspective changes the role of an individual from a passive observer to an actively engaged agent interacting in a closed loop with the world as well as with others. Cognition exists to serve action within a landscape that contains both. This chapter surveys this landscape and addresses the status of the pragmatic turn. Its potential influence on science and the study of cognition are considered (including perception, social cognition, social interaction, sensorimotor entrainment, and language acquisition) and its impact (...) on how neuroscience is studied is also investigated (with the notion that brains do not passively build models, but instead support the guidance of action). A review of its implications in robotics and engineering includes a discussion of the application of enactive control principles to couple action and perception in robotics as well as the conceptualization of system design in a more holistic, less modular manner. Practical applications that can impact the human condition are reviewed (e.g., educational applications, treatment possibilities for developmental and psychopathological disorders, the development of neural prostheses). All of this foreshadows the potential societal implications of the pragmatic turn. The chapter concludes that an action-oriented approach emphasizes a continuum of interaction between technical aspects of cognitive systems and robotics, biology, psychology, the social sciences, and the humanities, where the individual is part of a grounded cultural system. (shrink)

Our ability to acknowledge and recognise our own identity - our 'self' - is a characteristic doubtless unique to humans. Where does this feeling come from? How does the combination of neurophysiological processes coupled with our interaction with the outside world construct this coherent identity? We know that our social interactions contribute via the eyes, ears etc. However, our self is not only influenced by our senses. It is also influenced by the actions we perform and those we see others (...) perform. Our brain anticipates the effects of our own actions and simulates the actions of others. In this way, we become able to understand ourselves and to understand the actions and emotions of others. -/- This book is the first to describe the new field of 'Motor Cognition' - one to which the author's contribution has been seminal. Though motor actions have long been studied by neuroscientists and physiologists, it is only recently that scientists have considered the role of actions in building the self. How consciousness of action is part of self-consciousness, how one's own actions determine the sense of being an agent, how actions performed by others impact on ourselves for understanding others, differentiating ourselves from them and learning from them: these questions are raised and discussed throughout the book, drawing on experimental, clinical, and theoretical bases. -/- The advent of new neuroscience techniques, like neuroimaging and direct electrical brain stimulation, together with a renewal of behavioral methods in cognitive psychology, provide new insights into this area. Mental imagery of action, self-recognition, consciousness of actions, imitation can be objectively studied using these new tools. The results of these investigations shed light on clinical disorders in neurology, psychiatry and in neuro-development. -/- This is a major new work that will lay down the foundations for the field of motor cognition. (shrink)

This paper offers a conceptual framework which (re)integrates goal-directed control, motivational processes, and executive functions, and suggests a developmentalpathway from situated action to higher level cognition. We first illustrate a basic computational (control-theoretic) model of goal-directed action that makes use of internalmodeling. We then show that by adding the problem of selection among multiple actionalternatives motivation enters the scene, and that the basic mechanisms of executivefunctions such as inhibition, the monitoring of progresses, and working memory, arerequired for this system to (...) work. Further, we elaborate on the idea that the off-line re-enactment of anticipatory mechanisms used for action control gives rise to (embodied)mental simulations, and propose that thinking consists essentially in controlling mental simulations rather than directly controlling behavior and perceptions. We concludeby sketching an evolutionary perspective of this process, proposing that anticipationleveraged cognition, and by highlighting specific predictions of our model. (shrink)

Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...) the ‘symbol grounding problem'. When behaviour is viewed as a control process, it is natural to explain how internal representations, even symbols, can have meaning for an organism, and how actions can be motivated by organic needs. (shrink)

In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first (...) positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference. (shrink)

The goal of this short chapter, aimed at philosophers, is to provide an overview and brief explanation of some central concepts involved in predictive processing (PP). Even those who consider themselves experts on the topic may find it helpful to see how the central terms are used in this collection. To keep things simple, we will first informally define a set of features important to predictive processing, supplemented by some short explanations and an alphabetic glossary. -/- The features described here (...) are not shared in all PP accounts. Some may not be necessary for an individual model; others may be contested. Indeed, not even all authors of this collection will accept all of them. To make this transparent, we have encouraged contributors to indicate briefly which of the features are necessary to support the arguments they provide, and which (if any) are incompatible with their account. For the sake of clarity, we provide the complete list here, very roughly ordered by how central we take them to be for “Vanilla PP” (i.e., a formulation of predictive processing that will probably be accepted by most researchers working on this topic). More detailed explanations will be given below. Note that these features do not specify individually necessary and jointly sufficient conditions for the application of the concept of “predictive processing”. All we currently have is a semantic cluster, with perhaps some overlapping sets of jointly sufficient criteria. The framework is still developing, and it is difficult, maybe impossible, to provide theory-neutral explanations of all PP ideas without already introducing strong background assumptions. (shrink)

The neural bases of behavior are often discussed in terms of perceptual, cognitive, and motor stages, defined within an information processing framework that was originally inspired by models of human abstract problem solving. Here, we review a growing body of neurophysiological data that is difficult to reconcile with this influential theoretical perspective. As an alternative foundation for interpreting neural data, we consider frameworks borrowed from ethology, which emphasize the kinds of real-time interactive behaviors that animals have engaged in for millions (...) of years. In particular, we discuss an ethologically-inspired view of interactive behavior as simultaneous processes that specify potential motor actions and select between them. We review how recent neurophysiological data from diverse cortical and subcortical regions appear more compatible with this parallel view than with the classical view of serial information processing stages. (shrink)