The paper is an examination of the ways and extent to which neuroscience places constraints on cognitive science. In Part I, I clarify the issue, as well as the notion of levels in cognitive inquiry. I then present and address, in Part II, two arguments designed to show that facts from neuroscience are at a level too low to constrain cognitive theory in any important sense. I argue, to the contrary, that there are several respects in which facts from neurophysiology (...) will constrain cognitive theory. Part III then turns to an examination of Connectionism and Classical Cognitivism to determine which, if either, is in a better position to accomodate neural constraints in the ways suggested in Part II. (shrink)

This paper discusses the relation between cognitive and implementational levels of analysis. Chalmers (1990, 1993) argues that a connectionist implementation of a classical cognitive architecture possesses a compositional semantics, and therefore undercuts Fodor and Pylyshyn's (1988) argument that connectionist networks cannot possess a compositional semantics. I argue that Chalmers argument misconstrues the relation between cognitive and implementational levels of analysis. This paper clarifies the distinction, and shows that while Fodor and Pylyshyn's argument survives Chalmers' critique, it cannot be used to (...) establish the irrelevance of neurophysiological implementation to cognitive modeling; some aspects of Chater and Oaksford's (1990) response to Fodor and Pylyshyn, though not all, are therefore cogent. (shrink)

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that (...) none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures. (shrink)

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that (...) none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures. (shrink)

It is widely assumed that the explanatory states of scientific psychology are type-individuated by their semantic or intentional properties. First, I argue that this assumption is implausible for theories like David Marr's [1982] that seek to provide computational or syntactic explanations of psychological processes. Second, I examine the implications of this conclusion for the debate over psychological individualism. While most philosophers suppose that syntactic states supervene on the intrinsic physical states of information-processing systems, I contend they may not. Syntatic descriptions (...) must be adequately constrained, and the most plausible such constraints appeal to a system's teleological function or design and hence to its history. As a result, physical twins may not realize the same syntactic states. (shrink)

This paper defends a cognitive theory of those emotional reactions which motivate and constrain moral judgment. On this theory, moral emotions result from mental faculties specialized for automatically producing feelings of approval or disapproval in response to mental representations of various social situations and actions. These faculties are modules in Fodor's sense, since they are informationally encapsulated, specialized, and contain innate information about social situations. The paper also tries to shed light on which moral modules there are, which of these (...) modules we share with non-human primates, and on the (pre-)history and development of this modular system from pre-humans through gatherer-hunters and on to modern (i.e. arablist) humans. The theory is not, however, meant to explain all moral reasoning. It is plausible that a non-modular intelligence at least sometimes play a role in conscious moral thought. However, even non-modular moral reasoning is initiated and constrained by moral emotions having modular sources. (shrink)

The view that moral cognition is subserved by a two-tieredarchitecture is defended: Moral reasoning is the result both ofspecialized, informationally encapsulated modules which automaticallyand effortlessly generate intuitions; and of general-purpose,cognitively penetrable mechanisms which enable moral judgment in thelight of the agent's general fund of knowledge. This view is contrastedwith rival architectures of social/moral cognition, such as Cosmidesand Tooby's view that the mind is wholly modular, and it is argued thata two-tiered architecture is more plausible.

If the Trade Descriptions Act were applied to academic labels, cognitive scientists would be in trouble. For what they do is much wider than the name suggests—and wider, too, than most philosophers assume. They give you more for your money than you may have expected.

Interpreting the Miyashita et al. experiments in terms of a cellassembly representation does not adequately explain the performance of Miyashita's monkeys on novel stimuli. We will argue that the latter observations point to acompositionalrepresentation and suggest a dynamics involving rapid and reversible binding of distinct activity patterns.

While some philosophers have assumed that there are only two options for characterizing the ontological status of mental models in cognitive information processing psychology--treating them as nearly autonomous from theories of brain activity (Putnam 1975 and Fodor 1974) or eliminating them in favor of neuroscience accounts (Churchland 1979)-- cognitive scientists have often tacitly assumed a third option. This involves treating the mental models as systems of rules and representations that are instantiated in the nervous system much in the way computer (...) programs are instantiated in computers. While this seems to be the position of those endorsing the autonomy of psychology, it, in fact is consistent with a much weaker interpretation if one recognizes that the vehicle in which mental processes or computer programs are instantiated may limit and constrain what kinds of mental processes or computer programs can be instantiated. (shrink)

One way in which philosophy of science can perform a valuable normative function for science is by showing characteristic errors made in scientific research programs and proposing ways in which such errors can be avoided or corrected. This paper examines two errors that have commonly plagued research in biology and psychology: 1) functional localization errors that arise when parts of a complex system are assigned functions which these parts are not themselves able to perform, and 2) vacuous functional explanations in (...) which one provides an analysis that does account for the inputs and outputs of a system but does not employ the same set of functions to produce this output as does the natural system. These two kinds of error usually arise when researchers limit their investigation to one type of evidence. Historically, correction of these errors has awaited researchers who have employed the opposite type of evidence. This paper explores the tendency to commit these errors by examining examples from historical and contemporary science and proposes a dialectical process through which researchers can avoid or correct such errors in the future. (shrink)