Online research in philosophy

Tye argues that visual mental images have their contents encoded in topographically organized regions of the visual cortex, which support depictive representations; therefore, visual mental images rely at least in part on depictive representations. This argument, I contend, does not support its conclusion. I propose that we divide the problem about the depictive nature of mental imagery into two parts: one concerns the format of image representation and the other the conditions by virtue of which a representation becomes a depictive representation. Regarding the first part of the question, I argue that there exists a topographic format in the brain but that does not imply that there exists a depictive format of image representation. My answer to the second part of the question is that one needs a content analysis of a certain sort of topographic representations i n order to make sense of depictive mental representations, and a topographic representation becomes a depictive representation by virtue of its content rather than its form.

The main task of Cognitive Science is to construct concepts and models that would be superordinate to knowledge in the various particular cognitive sciences. In particular, one major objective is to formulate a hypergeneral description of representations that could encompass all descriptions given in subordinate domains.A first basic distinction is between natural and rational representations, i.e. given mental entities and representations that are governed by prescriptive rules coming from logical or scientific thought. In addition, representations must be described in respect to several sources of variability, which are tentatively listed here.Description of natural representations is based on a distinction between taken representations, which are mental events, and type representations, which are lasting structures registered in memory. The connection between them can be modelled through the concept of activation.One advantage of activation models is their large compatibilty, not only with experimental evidence in cognitive psychology, but also with facts and hypotheses in neurosciences, and programming modes or requirements in artificial intelligence. Comprehension of natural language is a highly representative domain in this respect, which exemplifies the power of these concepts.

Abstract A survey of different senses of the term ?representation? is presented. The presentation is guided by the appraisal that this key term is employed in the cognitive literature in different senses and that the distinction between these is not always explicitly stated or appreciated. Furthermore, the different senses seem to be associated with different rationales for the postulation of representation. Given that there may be a lack of convergence between the various senses of the construct in question and the rationales for its postulation, a clear differentiation of these may be crucial for any evaluation of the role of representations in cognition and in cognitive theory.

William Ramsey’s Representation Reconsidered is a superb, insightful analysis of the notion of mental representation in cognitive science. The book presents an original argument for a bold conclusion: partial eliminativism about mental representation in scientific psychology. According to Ramsey, once we examine the conditions that need to be satisfied for something to qualify as a representation, we can see those conditions are not fulfilled by the ‘representations’ posited by much of modern psychology. Cognitive science—or at least large swathes of it—has no warrant for positing representations. The structure of Ramsey’s argument repeats a familiar eliminativist strategy (c.f. Churchland (1981); Stich (1983)).1 First step: argue that in order for something to be an X, it must satisfy a certain description D (say, beliefs must satisfy the description given in folk psychology). Second step: argue that to the best of our knowledge, nothing satisfies description D (e.g. folk psychology is false). Third step: conclude that since nothing satisfies description D, there are no Xs (no beliefs). Here is how the strategy is played out in the book. First, Ramsey argues for certain minimal conditions that a representation must satisfy (what he calls the ‘job description’). Second (this takes the bulk of the book), he considers the ways in which our best psychological theories use the notion of representation. Ramsey argues that none of these uses satisfy the job description associated with a genuine representation. (A wrinkle is that some representations—those posited by the classical computational theory of cognition—do qualify as true representations. But, Ramsey claims, classical theories are in a minority in cognitive science, and their hold on the field is shrinking.) Therefore, Ramsey concludes, in most of cognitive science, there are no mental representations.

This paper investigates how "representation" is actually used in some areas in cognitive neuroscience. It is argued that recent philosophy has largely ignored an important kind of representation that differs in interesting ways from the representations that are standardly recognized in philosophy of mind. This overlooked kind of representation does not represent by having intentional contents; rather members of the kind represent by displaying or instantiating features. The investigation is not simply an ethnographic study of the discourse of neuroscientists. If there are indeed two different kinds of representations, and the non-standard ones are the ones referred to in some areas of cognitive neuroscience, then we will have to give up the idea that appealing to inner representations with intentional contents is the defining distinction between cognitive neuroscience and behaviorist psychology (Montgomery, 1995). Further, if the conclusions of this paper are correct, many general accounts of how neural states represent are either false or theoretically ill-motivated.

The sense of embodiment is vital for self recognition. An examination of anosognosia for hemiplegia—the inability to recognise that one is paralysed down one side of one’s body—suggests the existence of ‘online’ and ‘offline’ representations of the body. Online representations of the body are representations of the body as it is currently, are newly constructed moment by moment and are directly “plugged into” current perception of the body. In contrast, offline representations of the body are representations of what the body is usually like, are relatively stable and are constructed from online representations. This distinction is supported by an analysis of phantom limb—the feeling that an amputated limb is still present—phenomena. Initially it seems that the sense of embodiment may arise from either of these types of representation; however, an integrated representation of the body seems to be required. It is suggested information from vision and emotions is involved in generating these representations. A lack of access to online representations of the body does not necessarily lead to a loss in the sense of embodiment. An integrated offline representation of the body could account for the sense of embodiment and perform the functions attributed to this sense.

Mental representations are more than emulations. Different types of representations, including external representations, various mental models (distorted and abstract), and emulative models, can all play important roles in human cognition. To explain cognitive performance in a specific task, a systematic analysis of the underlying representational structures and their interactions is needed.

Thelen et al. present a convincing explanation of the A-not-B error, but contrary to their own claims, their explanation essentially involves mental representations. As is too common among cognitive scientists, they equate mental representations with representations of external physical objects. They clearly show, however, that representations of bodily actions on physical objects are central to the dynamical system producing the error.

Positing representations and operations on them as a way of explaining behavior was one of the major innovations of the cognitive revolution. Neuroscience and biology more generally also employ representations in explaining how organisms function and coordinate their behavior with the world around them. In discussions of the nature of representation, theorists commonly differentiate between the vehicles of representation and their content—what they denote. Many contentious debates in cognitive science, such as those pitting neural network models against symbol processing accounts, have focused on the types of vehicles proposed for mental representation and whether they have the appropriate structure to succeed in bearing their contents. Philosophers, in contrast, have focused their debates on content and the particular way in which vehicles might bear content—that is, the process of representing rather than the format of representations. I will offer a novel answer to the question of how it is that a representation has content by focusing on the architecture of representation. My proposal is that representations occur in a particular type of mechanism—one in which a control system regulates a plant—and that we can gain traction on cognitive systems of representation by considering how this works in physical systems more generally.

Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete representations are more influenced by conceptual role than continuous representations. We end by arguing that the presence of discrete representations in cognitive systems entails that computationalism (i.e., the view that the mind is a computational device) is true, and that cognitive science should embrace representational pluralism.