2. Daugman, J. G. Brain metaphor and brain theory 3. Mundale, J. Neuroanatomical Foundations of Cognition: Connecting the Neuronal Level with the Study of Higher Brain Areas.

New research tools such as PET can produce dramatic results. But they can also produce dramatic artifacts. Why is PET to be trusted? We examine both the rationale that justifies interpreting PET as measuring brain activity and the strategies for interpreting PET results functionally. We show that functional ascriptions with PET make important assumptions and depend critically on relating PET results to those secured through other research techniques.

New research tools such as PET can produce dramatic results. But they can also produce dramatic artifacts. Why is PET to be trusted? We examine both the rationale that justifies interpreting PET as measuring brain activity and the strategies for interpreting PET results functionally. We show that functional ascriptions with PET make important assumptions and depend critically on relating PET results to those secured through other research techniques.

Most cognitive scientists believe that cognitive processing (e.g., thought, speech, perception, and sensori‐motor processing) is the hallmark of intelligent systems. Aside from modeling such processes, cognitive science is in the business of mechanistically explaining how minds and other intelligent systems work. As one might expect, mechanistic explanations appeal to the causal‐functional interactions among a system's component structures. Good explanations are the ones that get the causal story right. But getting the causal story right requires positing structures that are really in (...) the system. After all, within the context of a mechanistic explanation, to posit X is to claim not only that X exists but that X is doing some causal labor. Because most cognitive scientists believe that cognitive processing requires the use, manipulation, and storage of internal representations, they characteristically posit internal representations to explain how intelligent systems work. (shrink)

Aron Gurwitsch (1900-73) was one of the most important figures in the phenomenological movement between the 1920s and the 1970s. Through his introduction of Gestalt theoretical concepts into phenomenology, he exerted a powerful influence on Maurice Merleau-Ponty and others. The contributions to this memorial volume, most written by friends and students of Gurwitsch, contain critical studies of the work of Aron Gurwitsch and attempts to extend his philosophical analyses to new problems and fields. Ranging from formal ontology through the philosophy (...) of the social sciences to the interpretation of Kant, the essays assembled here are both a tribute to and a continuation of the philosophical legacy of Aron Gurwitsch. The contributions will be of interest to advanced undergraduates and graduate students, and to specialists in a wide range of areas. (shrink)

C. I. Lewis' action-oriented notion of cognition is consistent with a minimally representational picture of mind. I aim to show why. Toward this end, I explore some of the tensions between Lewis' theory of knowledge and his theory of mind. At face value, the former renders the latter implausible. Among other problems, no agent could act if she were required to entertain the myriad beliefs that Lewis claims figures in the guidance of action. But rather than abandon Lewis' story, I (...) attempt to rehabilitate it. Rehabilitation is possible, I argue, because Lewis isn't claiming that his epistemology describes actual justificatory practices, but rather what an agent could do; the social character of concepts [and meaning] considerably reduces the need for appealing to internal concepts when explaining why an agent does what she does; and among his paradigm cases of cognitive behavior are paradigm cases of nonreflective action. Here's the rub: not only do such actions account for most of our behavior [as Lewis himself notes], nonreflective actions, though cognitive, don't require conceptualization. (shrink)

Although Clark & Thornton's “trading spaces” hypothesis is supposed to require trading internal representation for computation, it is not used consistently in that fashion. Not only do some of the offered computation-saving strategies turn out to be nonrepresentational, others (e.g., cultural artifacts) are external representations. Hence, C&T's hypothesis is consistent with antirepresentationalism.

Turing's analysis of the concept of computation is indisputably the foundation of computationalism, which is, in turn, the foundation of cognitive science. What is disputed is whether computationalism is explanatorily bankrupt. For Turing, all computers are digital computers and something becomes a computer just in case its 'behavior' is interpreted as implementing, executing, or satisfying some function 'f'. As 'computer' names a nonnatural kind, almost everyone agrees that a computational interpretation of this sort is necessary for something to be a (...) computer. But because everything in the universe satisfies at least one function, it is the sufficiency of such interpretations that is the problem. If, as anticomputationalists are fond of pointing out, computationalists are wedded to the view that a computational interpretation is sufficient for something to be a computer, then everything becomes a digital computer. This not only renders computer-talk vacuous, it strips computationalism of any empirical or explanatory import. My aim is to defend computationalism against charges that it is explanatorily bankrupt. I reexamine several fundamental questions about computers. One effect of this computation-related soul-searching will be a framework within which 'Is the brain a computer?' will be meaningful. Another effect will be a fracture in the supposed link between computationalism and symbolic-digital processing. (shrink)