This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

Imitation, deliberation, and mindreading are characteristically human sociocognitive skills. Research on imitation and its role in social cognition is flourishing across various disciplines; it is here surveyed under headings of behavior, subpersonal mechanisms, and functions of imitation. A model is then advanced within which many of the developments surveyed can be located and explained. The shared circuits model explains how imitation, deliberation, and mindreading can be enabled by subpersonal mechanisms of control, mirroring and simulation. It is cast at a middle, (...) functional level of description, between the level of neural implementation and the level of conscious perceptions and intentional actions. The shared circuits model connects shared informational dynamics for perception and action with shared informational dynamics for self and other, while also showing how the action/perception, self/other and actual/possible distinctions can be overlaid on these shared informational dynamics. It avoids the common conception of perception and action as separate and peripheral to central cognition. Rather, it contributes to the situated cognition movement by showing how mechanisms for perceiving action can be built on those for active perception. (shrink)

A SLOW revolution in cognitive science is banishing this century's technological conception of mind as disembodied pure thought, namely a material symbol manipulation, and replacing it with next century's conception: mind as the organisation of bodily interaction, intelligent robotics. Here is Clark: Intelligence and understanding are rooted not in the presence and manipulation of explicit, language-like data structures, but in something more earthy: the tuning of basic responses to a real world that enables an embodied organism to sense, act and (...) survive . . . it is now increasingly clear that the alternative to the ``disembodied explicit data manipulation'' vision of AI is not to retreat from hard science; it is to pursue some even harder science. It is to put intelligence where it belongs: in the coupling of organisms and the world that is at the root of daily, fluent action. (p. 4) # AAHPSSS, 1998. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, and 350 Main Street, Malden MA 02148, USA.. (shrink)

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in (...) parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery. (shrink)

An attempt is made to defend a general approach to the spatial content of perception, an approach according to which perception is imbued with spatial content in virtue of certain kinds of connections between perceiving organism's sensory input and its behavioral output. The most important aspect of the defense involves clearly distinguishing two kinds of perceptuo-behavioral skills—the formation of dispositions, and a capacity for emulation. The former, the formation of dispositions, is argued to by the central pivot of spatial content. (...) I provide a neural information processing interpretation of what these dispositions amount to, and describe how dispositions, so understood, are an obvious implementation of Gareth Evans' proposal on the topic. Furthermore, I describe what sorts of contribution are made by emulation mechanisms, and I also describe exactly how the emulation framework differs from similar but distinct notions with which it is often unhelpfully confused, such as sensorimotor contingencies and forward models. (shrink)

b>: In this article I outline, apply, and defend a theory of natural representation. The main consequences of this theory are: i) representational status is a matter of how physical entities are used, and specifically is not a matter of causation, nomic relations with the intentional object, or information; ii) there are genuine (brain-)internal representations; iii) such representations are really representations, and not just farcical pseudo-representations, such as attractors, principal components, state-space partitions, or what-have-you;and iv) the theory allows us to (...) sharply distinguish those complex behaviors which are genuinely cognitive from those which are merely complex and adaptive. (shrink)

I argue against a growing radical trend in current theoretical cognitive science that moves from the premises of embedded cognition, embodied cognition, dynamical systems theory and/or situated robotics to conclusions either to the effect that the mind is not in the brain or that cognition does not require representation, or both. I unearth the considerations at the foundation of this view: Haugeland's bandwidth-component argument to the effect that the brain is not a component in cognitive activity, and arguments inspired by (...) dynamical systems theory and situated robotics to the effect that cognitive activity does not involve representations. Both of these strands depend not only on a shift of emphasis from higher cognitive functions to things like sensorimotor processes, but also depend on a certain understanding of how sensorimotor processes are implemented - as closed-loop control systems. I describe a much more sophisticated model of sensorimotor processing that is not only more powerful and robust than simple closed-loop control, but for which there is great evidence that it is implemented in the nervous system. The is the emulation theory of representation, according to which the brain constructs inner dynamical models, or emulators, of the body and environment which are used in parallel with the body and environment to enhance motor control and perception and to provide faster feedback during motor processes, and can be run off-line to produce imagery and evaluate sensorimotor counterfactuals. I then show that the emulation framework is immune to the radical arguments, and makes apparent why the brain is a component in the cognitive activity, and exactly what the representations are in sensorimotor control. (shrink)

This chapter contains sections titled: Introduction Historical Background: Behaviorism and the Cognitive Revolution Current Topics Future Directions.

Consciousness and experience, William G. Lycan. Cambridge, MA: MIT Press, 1996. ISBN 0–262–12197–2 (hc)Mind as motion: explorations in the dynamics of cognition, Robert Port & Timothy Van Gelder (Eds). Cambridge, MA: MIT/Bradford, 1995. ISBN 0–262–16150–8Perception, Kathleen Akins (Ed.). New York: Oxford University Press, 1996. ISBN 0–19–508461 (hbk); 0–19–508462–4 (pbk)Context and consciousness, B. Nardi (Ed.). Cambridge, MA: MIT Press, 1996. ISBN: 0–262–14058–6Catching ourselves in the act, Horst Hendriks‐Jansen. Cambridge, MA: MIT Press, 1996. ISBN 0–262–08246–2The search for mind. A new foundation for (...) cognitive science, Sean O'Nuallain. Norwood, NJ: Ablex, 1995Mindblindness: an essay on autism and theory of mind, Simon Baron‐Cohen. Cambridge, MA: MIT Press, 1995. ISBN 0–262–02384–9. (shrink)

Susan Hurley's shared circuits model (SCM) rightly begins in action and progresses through a series of layers; but it fails to reach action understanding because it relies on mirroring as a driving force, draws on heavily criticized theories, and neglects the need for shared experience in our grasp of social understanding.

The paper defends the structural concept of representation, defined by homomorphisms, against the main objections that have been raised against it: Logical objections, the objection from misrepresentation, the objection from failing necessity, and the copy theory objection. Homomorphic representations are not necessarily ‘copies’ of their representanda, and thus can convey scientific insight.

The aim of this paper is to defend the structural concept of representation, as defined by homomorphisms, against its main objections, namely: logical objections, the objection from misrepresentation, theobjection from failing necessity, and the copy theory objection. The logical objections can be met by reserving the relation.

A slow revolution in cognitive science is banishing this century's technological conception of mind as disembodied pure thought, namely a material symbol manipulation, and replacing it with next century's conception: mind as the organisation of bodily interaction, intelligent robotics.

In this article we will argue that given certain conditions for the evolution of bi- ological controllers, these will necessarily evolve in the direction of incorporating consciousness capabilities. We will also see what are the necessary mechanics for the provision of these capabilities and extrapolate this vision to the world of artifi- cial systems postulating seven design principles for conscious systems. This article was published in the journal Neural Networks special issue on brain and conscious- ness.