This is a unique book. It is excellently written, crammed with information, wise and a pleasure to read.' ---Daniel C. Dennett, Tufts University.

Through the ability to preview the future , people can anticipate how best to think, feel and act in just about any setting. But exactly what factors determine the contents of prospection? Extending research on action identification and temporal construal, here we explored how action goals and temporal distance modulate the characteristics of future previews. Participants were required to imagine travelling to Egypt to climb or photograph a pyramid. Afterwards, to probe the contents of prospection, participants provided a sketch of (...) their imaginary experience. Results elucidated the impact of goal type and temporal distance on mental imagery. While a climbing goal prompted participants to draw a larger pyramid in the near than distant future, a photographic goal influenced only the compositional complexity of the sketches. These findings reveal how action goals and temporal distance shape the contents of future simulations. (shrink)

In a remarkable exchange between neuroscientist Jean-Pierre Changeux and philosopher Paul Ricoeur, this book explores the vexed territory between these...

The easy problems of consciousness are those that seem directly susceptible to the standard methods of cognitive science, whereby a phenomenon is explained in terms of computational or neural mechanisms. The hard problems are those that seem to resist those methods. The easy problems are easy precisely because they concern the explanation of cognitive abilities and functions. Once we have specified the neural or computational mechanism that performs the function of verbal report, for example, the bulk of our work in (...) explaining reportability is over. Baars theory of cognitive accessibility addresses many aspects of human cognition and shows promise as a theory of awareness, the functional correlate of conscious experience, but an explanation of experience itself is not on offer. The key is the conceptual point that the explanation of functions does not suffice for the explanation of experience. (shrink)

We critically review themushrooming literature addressing the neuralmechanisms of moral cognition (NMMC), reachingthe following broad conclusions: (1) researchmainly focuses on three inter-relatedcategories: the moral emotions, moral socialcognition, and abstract moral reasoning. (2)Research varies in terms of whether it deploysecologically valid or experimentallysimplified conceptions of moral cognition. Themore ecologically valid the experimentalregime, the broader the brain areas involved.(3) Much of the research depends on simplifyingassumptions about the domain of moral reasoningthat are motivated by the need to makeexperimental progress. This is a (...) valuablebeginning, but as more is understood about theneural mechanisms of decision-making, morerealistic conceptions will need to replace thesimplified conceptions. (4) The neuralcorrelates of real-life moral cognition areunlikely to consist in anything remotely like a``moral module'' or a ``morality center.'' Moralrepresentations, deliberations and decisionsare probably highly distributed and notconfined to any particular brainsub-system. Discovering the basic neuralprinciples governing planning, judgment anddecision-making will require vastly more basicresearch in neuroscience, but correlatingactivity in certain brain regions withwell-defined psychological conditions helpsguide neural level research. Progress on socialphenomena will also require theoreticalinnovation in understanding the brain'sdistinctly biological form of computationthat is anchored by emotions, needs, drives,and the instinct for survival. (shrink)

After establishing its roots in basic forms of sensorimotor coupling between an organism and its environment, the new wave in cognitive science known as “enactivism” has turned to higher-level cognition, in an attempt to prove that even socioculturally mediated meaning-making processes can be accounted for in enactivist terms. My article tries to bolster this case by focusing on how the production and interpretation of stories can shape the value landscape of those who engage with them. First, it builds on the (...) idea that narrative plays a key role in expressing the values held by a society, in order to argue that the interpretation of stories cannot be understood in abstraction from the background of storytelling in which we are always already involved. Second, it presents interpretation as an example of what Di Paolo et al. ( 2010 ) have called in their recent enactivist manifesto a “joint process of sensemaking”: just like in face-to-face interaction, the recipient of the story collaborates with the authorial point of view, generating meaning. Third, it traces the meaning brought into the world by interpretation to the activation and, potentially, the restructuring of the background of the recipients of the story. (shrink)

From our deep interest in the neuroconstructivist framework, we would like to comment on two fundamental aspects of Mareschal et al.'s work: the role of neuroconstructivism for clinical work with people suffering from developmental disorders; and the relation between the process of progressive specialization and the increasing abstraction of representations in development.

To explain social learning without invoking the cognitively complex concept of imitation, many learning mechanisms have been proposed. Borrowing an idea used routinely in cognitive psychology, we argue that most of these alternatives can be subsumed under a single process, priming, in which input increases the activation of stored internal representations. Imitation itself has generally been seen as a This has diverted much research towards the all-or-none question of whether an animal can imitate, with disappointingly inconclusive results. In the great (...) apes, however, voluntary, learned behaviour is organized hierarchically. This means that imitation can occur at various levels, of which we single out two clearly distinct ones: the a rather detailed and linear specification of sequential acts, and the a broader description of subroutine structure and the hierarchical layout of a behavioural Program level imitation is a high-level, constructive mechanism, adapted for the efficient learning of complex skills and thus not evident in the simple manipulations used to test for imitation in the laboratory. As examples, we describe the food-preparation techniques of wild mountain gorillas and the imitative behaviour of orangutans undergoing to the wild. Representing and manipulating relations between objects seems to be one basic building block in their hierarchical programs. There is evidence that great apes suffer from a stricter capacity limit than humans in the hierarchical depth of planning. We re-interpret some chimpanzee behaviour previously described as and suggest that all great apes may be able to imitate at the program level. Action level imitation is seldom observed in great ape skill learning, and may have a largely social role, even in humans. (shrink)

Evolutionary psychologists claim that the mind contains “hundreds or thousands” of “genetically specified” modules, which are evolutionary adaptations for their cognitive functions. We argue that, while the adult human mind/brain typically contains a degree of modularization, its “modules” are neither genetically specified nor evolutionary adaptations. Rather, they result from the brain’s developmental plasticity, which allows environmental task demands a large role in shaping the brain’s information-processing structures. The brain’s developmental plasticity is our fundamental psychological adaptation, and the “modules” that result (...) from it are adaptive responses to local conditions, not past evolutionary environments. If different individuals share common environ- ments, however, they may develop similar “modules,” and this process can mimic the development of genetically specified modules in the evolutionary psychologist’s sense. (shrink)

Surely since the Enlightenment, if not before, the study of mind has centered principally on how man achieves a “true” knowledge of the world. Emphasis in this pursuit has varied, of course: empiricists have concentrated on the mind’s interplay with an external world of nature, hoping to find the key in the association of sensations and ideas, while rationalists have looked inward to the powers of mind itself for the principles of right reason. The objective, in either case, has been (...) to discover how we achieve “reality,” that is to say, how we get a reliable fix on the world, a world that is, as it were, assumed to be immutable and, as it were, “there to be observed.”This quest has, of course, had a profound effect on the development of psychology, and the empiricist and rationalist traditions have dominated our conceptions of how the mind grows and how it gets its grasp on the “real world.” Indeed, at midcentury Gestalt theory represented the rationalist wing of this enterprise and American learning theory the empiricist. Both gave accounts of mental development as proceeding in some more or less linear and uniform fashion from an initial incompetence in grasping reality to a final competence, in one case attributing it to the work out of internal processes or mental organization, and in the other to some unspecified principle of reflection by which—whether through reinforcement, association, or conditioning—we came to respond to the world “as it is.” There have always been dissidents who challenged these views, but conjectures about human mental development have been influenced far more by majoritarian rationalism and empiricism than by these dissident voices. Jerome Bruner is research professor of psychology at New York University, where he is also serving as Meyer Visiting Professor of Law. His most recent book, Acts of Meaning, appeared in 1990. In 1987 he received the Balzan Prize for “a lifetime contribution to the study of human psychology.”. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

I sketch my general model of the roles of intentions in the planning of agents like us-agents with substantial resource limitations and with important needs for coordination. I then focus on the stability of prior intentions: their rational resistance to reconsideration. I emphasize the importance of cases in which one's nonreconsideration of a prior intention is nondeliberative and is grounded in relevant habits of reconsideration. Concerning such cases I argue for a limited form of two-tier consequentialism, one that is restricted (...) in ways that aim at blocking an analogue of Smart's concerns about rule-worship. I contrast this with the unrestricted two-tier consequentialism suggested by McClennen. I argue that my restricted approach is superior for a theory of the practical rationality of reflective, planning agents like us. But I also conjecture that an unrestricted two-tier consequentialism may be more appropriate for the AI project of specifying a high level architecture for a resource-bounded planner. (shrink)

In autonomous action the agent herself directs and governs the action. But what is it for the agent herself to direct and to govern? One theme in a series of articles by Harry G. Frankfurt is that we can make progress in answering this question by appeal to higher-order conative attitudes. Frankfurt's original version of this idea is that in acting of one's own free will, one is not acting simply because one desires so to act. Rather, it is also (...) true that this desire motivates one's action because one desires that this desire motivate one's action. This latter desire about the motivational role of one's desire is a second-order desire. It is, in particular, what Frankfurt calls a second-order “volition.” And, according to Frankfurt's original proposal, acting of one's own free will involves in this way such second-order, and sometimes yet higher order, volitions. (shrink)

Current cognitive science models of perception and action assume that the objects that we move toward and perceive are represented as determinate in our experience of them. A proper phenomenology of perception and action, however, shows that we experience objects indeterminately when we are perceiving them or moving toward them. This indeterminacy, as it relates to simple movement and perception, is captured in the proposed phenomenologically based recurrent network models of brain function. These models provide a possible foundation from which (...) predicative structures may arise as an emergent phenomenon without the positing of a representing subject. These models go some way in addressing the dual constraints of phenomenological accuracy and neurophysiological plausibility that ought to guide all projects devoted to discovering the physical basis of human experience. (shrink)

Expert chess players, specialized in different openings, recalled positions and solved problems within and outside their area of specialization. While their general expertise was at a similar level, players performed better with stimuli from their area of specialization. The effect of specialization on both recall and problem solving was strong enough to override general expertise—players remembering positions and solving problems from their area of specialization performed at around the level of players 1 standard deviation (SD) above them in general skill. (...) Their problem‐solving strategy also changed depending on whether the problem was within their area of specialization. When it was, they searched more in depth and less in breadth; with problems outside their area of specialization, the reverse. The knowledge that comes from familiarity with a problem area is more important than general purpose strategies in determining how an expert will tackle it. These results demonstrate the link in experts between problem solving and memory of specific experiences and indicate that the search for context‐independent general purpose problem‐solving strategies to teach to future experts is unlikely to be successful. (shrink)

Three studies using the Dreyfus model of skill acquisition were conducted over a period of 21 years. Nurses with a range of experience and reported skill-fulness were interviewed. Each study used nurses’ narrative accounts of actual clinical situations. A subsample of participants were observed and interviewed at work. These studies extend the understanding of the Dreyfus model to complex, underdetermined, and fast-paced practices. The skill of involvement and the development of moral agency are linked with the development of expertise, and (...) change as the practitioner becomes more skillful. Nurses who had some difficulty with understanding the ends of practice and difficulty with their skills of interpersonal and problem engagement did not progress to the level of expertise. Taken together, these studies demonstrate the usefulness of the Dreyfus model for understanding the learning needs and styles of learning at different levels of skill acquisition. (shrink)

The current study collected orally-delivered autobiographical narratives from a sample of 44 undergraduate students. Participants were asked to produce both deceptive and non-deceptive versions of their narrative to two specific autobiographical question prompts while standing in front of a video camera. Narratives were then analyzed with Coh-Metrix software on 33 indices of linguistic cohesion. Following a Bonferroni correction for the large number of linguistic variables , results indicated that the deceptive narratives contained more explicit action verbs, less linguistic complexity, and (...) less referential coherence . The results support a theory that, in deceptive narratives, there is greater narrative distance between the self that narrates and the self that is narrated about. This suggests that narrative selves are constituted not as autonomous selves, but are subject to processes that are likely operating on a subconscious level. (shrink)

Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, and an (...) analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing. (shrink)

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...) they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations. (shrink)

The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of processes at (...) the level at which cognitive theories attempt to function: One is drawn from too low a level, the other from too high a level. If there is a distinctly cognitive level, then we still need to determine what are the basic organizational principles at that level. (shrink)

Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...) find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up —situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. (shrink)

The claim of the multiple realizability of mental states by brain states has been a major feature of the dominant philosophy of mind of the late 20th century. The claim is usually motivated by evidence that mental states are multiply realized, both within humans and between humans and other species. We challenge this contention by focusing on how neuroscientists differentiate brain areas. The fact that they rely centrally on psychological measures in mapping the brain and do so in a comparative (...) fashion undercuts the likelihood that, at least within organic life forms, we are likely to find cases of multiply realized psychological functions. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

This paper defends cognitive neuroscience’s project of developing mechanistic explan- ations of cognitive processes through decomposition and localization against objections raised by William Uttal in The New Phrenology. The key issue between Uttal and researchers pursuing cognitive neuroscience is that Uttal bets against the possibility of decomposing mental operations into component elementary operations which are localized in distinct brain regions. The paper argues that it is through advancing and revising what are likely to be overly simplistic and incorrect decompositions that (...) the goals of cognitive neuroscience are likely to be achieved. (shrink)

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their (...) styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

"Theoretical pluralism" obtains when there are good evidential reasons for accommodating multiple theories of the same domain. Issues of "relative significance" often arise in connection with the investigation of such domains. In this paper, I describe and give examples of theoretical pluralism and relative significance issues. Then I explain why theoretical pluralism so often obtains in biology--and why issues of relative significance arise--in terms of evolutionary contingencies and the paucity or lack of laws of biology. Finally, I turn from explanation (...) to justification, and raise questions about the purpose and value of concerns and disagreements about relative significance. (shrink)

An attractive feature of Neuroconstructivism, Vol. I: How the Brain Constructs Cognition is its emphasis on the active role of the individual in neural and behavioural development and the importance of the interplay with the environment. Certain aspects of development are omitted, however, such as specializations for the distinctive ecologies of infancy and childhood and the scaffolding-like features of behaviour seen during development. It was also a pity that so little credit was given to many scientists who have contributed to (...) just those aspects of development on which the authors focus. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.

Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that purport to undermine modularity, with particular attention on cognitive architecture, development, genetics, and evolution. The authors propose that modularity, cleanly defined, provides a useful framework for directing (...) research and resolving debates about individual cognitive systems and the nature of human evolved cognition. Modularity is a fundamental property of living things at every level of organization; it might prove indispensable for understanding the structure of the mind as well. (shrink)

Organisms engage in various activities that are directed at objects, whether real or imagined. Such activities may be termed “intentional relations.” We present a four-level framework of social understanding that organizes the ways in which social organisms represent the intentional relations of themselves and other agents. We presuppose that the information available to an organism about its own intentional relations (or first person information) is qualitatively different from the information available to that organism about other agents’ intentional relations (or third (...) person information). However, through the integration of these two sources of information, it is possible to generate representations of intentional relations that are uniformly applicable to the activities of both self and other. The four levels of the framework differ in the extent to which such integration occurs and in the degree to which imagination is involved in generating these representations. Most animals exist at the lowest level, at which integration of first and third person sources of information does not occur. Of nonhuman species, only great apes exhibit social understanding at intermediate levels, at which integration of these sources of information provides uniform representations of intentional relations. Only humans attain the highest level, at which it is possible to represent intentional relations with mental objects. We propose that with the development of the imagination, children progress through three stages, equivalent to the later three levels of the framework. The abnormalities in social understanding of autistic individuals are hypothesized to result from a failure to develop integrated representations of intentional relations. (shrink)

Grounded cognition offers a natural approach for integrating Bayesian accounts of optimality with mechanistic accounts of cognition, the brain, the body, the physical environment, and the social environment. The constructs of simulator and situated conceptualization illustrate how Bayesian priors and likelihoods arise naturally in grounded mechanisms to predict and control situated action.

Thirty years ago, grounded cognition had roots in philosophy, perception, cognitive linguistics, psycholinguistics, cognitive psychology, and cognitive neuropsychology. During the next 20 years, grounded cognition continued developing in these areas, and it also took new forms in robotics, cognitive ecology, cognitive neuroscience, and developmental psychology. In the past 10 years, research on grounded cognition has grown rapidly, especially in cognitive neuroscience, social neuroscience, cognitive psychology, social psychology, and developmental psychology. Currently, grounded cognition appears to be achieving increased acceptance throughout cognitive (...) science, shifting from relatively minor status to increasing importance. Nevertheless, researchers wonder whether grounded mechanisms lie at the heart of the cognitive system or are peripheral to classic symbolic mechanisms. Although grounded cognition is currently dominated by demonstration experiments in the absence of well-developed theories, the area is likely to become increasingly theory driven over the next 30 years. Another likely development is the increased incorporation of grounding mechanisms into cognitive architectures and into accounts of classic cognitive phenomena. As this incorporation occurs, much functionality of these architectures and phenomena is likely to remain, along with many original mechanisms. Future theories of grounded cognition are likely to be heavily influenced by both cognitive neuroscience and social neuroscience, and also by developmental science and robotics. Aspects from the three major perspectives in cognitive science—classic symbolic architectures, statistical/dynamical systems, and grounded cognition—will probably be integrated increasingly in future theories, each capturing indispensable aspects of intelligence. (shrink)

Increasing evidence suggests that mundane knowledge about objects, people, and events is grounded in the brain's modality-specific systems. The modality-specific representations that become active to represent these entities in actual experience are later used to simulate them in their absence. In particular, simulations of perception, action, and mental states often appear to underlie the representation of knowledge, making it embodied and situated. Findings that support this conclusion are briefly reviewed from cognitive psychology, social psychology, and cognitive neuroscience. A similar representational (...) process may underlie religious knowledge. In support of this conjecture, embodied knowledge appears central to three aspects of religious experience: religious visions, religious beliefs, and religious rituals. In religious visions, the process of simulation offers a natural account of how these experiences are produced. In religious beliefs, knowledge about the body and the environment are typically central in religious frameworks, and are likely to affect the perception of daily experience. In religious rituals, embodiments appear central to conveying religious ideas metaphorically and to establishing them in memory. To the extent that religious knowledge is like non-religious knowledge, embodiment is likely to play central roles. (shrink)

What makes us conscious? Many theories that attempt to answer this question have appeared recently in the context of widespread interest about consciousness in the cognitive neurosciences. Most of these proposals are formulated in terms of the information processing conducted by the brain. In this overview, we survey and contrast these models. We first delineate several notions of consciousness, addressing what it is that the various models are attempting to explain. Next, we describe a conceptual landscape that addresses how the (...) theories attempt to explain consciousness. We then situate each of several representative models in this landscape and indicate which aspect of consciousness they try to explain. We conclude that the search for the neural correlates of consciousness should be usefully complemented by a search for the computational correlates of consciousness. (shrink)