Reflexive monism is, in essence, an ancient view of how consciousness relates to the material world that has, in recent decades, been resurrected in modern form. In this paper I discuss how some of its basic features differ from both dualism and variants of physicalist and functionalist reductionism, focusing on those aspects of the theory that challenge deeply rooted presuppositions in current Western thought. I pay particular attention to the ontological status and seeming “outthereness” of the phenomenal world and to how the “phenomenal world” relates to the “physical world”, the “world itself”, and processing in the brain. In order to place the theory within the context of current thought and debate, I address questions that have been raised about reflexive monism in recent commentaries and also evaluate competing accounts of the same issues offered by “transparency theory ” and by “biological naturalism”. I argue that, of the competing views on offer, reflexive monism most closely follows the contours of ordinary experience, the findings of science, and common sense.

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Attractor networks, which map an input space to a discrete output space, are useful for pattern completion---cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins. These difficulties occur because each connection in the network participates in the encoding of multiple attractors. We describe an alternative formulation of attractor networks in which the encoding of knowledge is local, not distributed. Although localist attractor networks have similar dynamics to their distributed counterparts, they are much easier to work with and interpret. We propose a statistical formulation of localist attractor net dynamics, which yields a convergence proof and a mathematical interpretation of model parameters. We present simulation experiments that explore the behavior of localist attractor networks, show...

Past studies have shown that nonwords homophonic to words can produce phonological priming (klip -- CLIP), even when the primes are presented in a masked fashion (Ferrand & Grainger, 1992). This suggests that phonological codes are automatically activated and used in written word recognition. Here, we raise the possibility that in these experiments, subjects might have occasionally been aware of the primes, and that prime awareness is a necessary condition for phonological priming to arise. Across a large range of prime duration (43ms to 100ms), and a total of 238 subjects, we found phonological priming to be restricted to subjects who were consciously aware of the prime, whatever the prime duration. In contrast, we uncovered a small but statistically reliable nonword repetition priming effect, which was not dependant on prime awareness, and increased as a function of prime duration. We discuss these findings in terms of current models of written word recognition and general issues regarding the distinction between automatic and strategic processes.

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Abstract. This chapter describes Conversational Agents (CAs) in the context of

Abstract — Creativity is an important attribute of the human mind, and shows itself in all aspects of its function. However, its neural basis remains poorly understood. In this paper, we explore two issues with regard to creativity in the semantic domain: 1) What neural mechanism enable the brain to construct context-specific semantic spaces to facilitate the generation of relevant ideas? and 2) Can these mechanisms support greater creativity simply by exploring unusual semantic spaces? We use a variant of our previously developed neural model of ideation to show that a dynamical modular neural system can, indeed, learn to configure context-appropriate semantic domains based on experience, and that exploratory dynamics within this system can lead to the unmasking of novel emergent ideas. I.

Abstract — This paper reviews the different methods that have been employed recently to study consciousness. At least two of those methods, the neuropsychological approach and the cognitive approach, have converged on a set of characteristics that separate conscious processes from unconscious ones. These characteristics: durable, explicit representations; novel combinations of operations; and intentional behaviors intersect with the necessary requirements for the development of expertise using deliberate practice. This intersection is described in detail and its potential implications for cross-species comparisons, understanding the evolution of human consciousness, and consciousness in machines is discussed. Copyright c ○ 2003-2005 Yang’s Scientific

Introduction While the study of implicit learning is nothing new, the field as a whole has come to embody --- over the last decade or so --- ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. To begin in a way that reflects

We examined whether a pictorial depth illusion influences the manual pursuit of a moving dot to the same extent that it influences the dot's apparent displacement. Fourteen subjects performed two tasks. In one case, they used their unseen hand to track a dot that moved on an elliptical path. In the other, they first watched the dot move on the same path, and then set an ellipse to match the shape of the dot's path. The illusion influenced the two tasks to the same extent, suggesting that the visual information processing is the same for the two tasks.