Online research in philosophy

The neural basis of the Chorus model has been cast in terms of the visual alphabet theory, but the neural evidence can also be interpreted as supporting a theory of higher level representation in which neurons are responsive to complex 3D stimuli. These neurons, functioning as a population, could also form the basis of a representation such as envisaged by the Chorus model.

Is mental imagery pictorial? In Pylyshyn's view no empirical data provides convincing support to the “pictorial” hypothesis of mental imagery. Phenomenology, Pylyshyn says, is deeply deceiving and offers no explanation of why and how mental imagery occurs. We suggest that Pylyshyn mistakes phenomenology for what it never pretended to be. Phenomenological evidence, if properly considered, shows that mental imagery may indeed be pictorial, though not in the way that mimics visual perception. Moreover, Pylyshyn claims that the “pictorial hypothesis” is flawed because the interpretation of “picture-like” objects in mental imagery takes a homunculus. However, the same point can be objected to Pylyshyn's own conclusion: if imagistic reasoning involves the same mechanisms and the same forms of representation as those that are involved in general reasoning, if they operate on symbol-based representations of the kind recommended by Pylyshyn (1984) and Fodor (1975), don't we need a phenomenological homunculus to tell an imagined bear from the real one?

Pictorial representation is a subject of interest to both cognitive science and aesthetics. Standard theories of depiction often draw on vision science, and vision science must give an account of picture perception. I offer a critical overview of standard theories of depiction and argue that none of them is adequate. I then describe ways in which new theories of perception blend elements of representationalism with an emphasis on attention and motor control. Such theories, in effect, limit the reliance on mental representation in perceptual tasks. This work provides the basis for a theory of depiction in which pictorial representation is explained in terms of both mental representations and perceptual strategies. I argue that, in the case, the mental representations are most plausibly individuated by the functional and conceptual roles, rather than by causal links to the external world.

O'Regan & Noë (O&N) are pessimistic about the prospects for discovering the neural correlates of consciousness. They argue that there can be no one-to-one correspondence between awareness and patterns of neural activity in the brain, so a project attempting to identify the neural correlates of consciousness is doomed to failure. We believe that this degree of pessimism may be overstated; recent empirical data show some convergence in describing consistent patterns of neural activity associated with visual consciousness.

Positing the importance of sensorimotor contingencies for perception is by no means denying the presence and importance of representations. Using the evidence of mirror neurons we will show the intrinsic relationship between action control and representation within the logic of forward models.

This paper is an argument to the effect that a certain view about mental representing, together with some very liberal constraints on the brain as a dynamic system, entails that the organism will tend to form adaptive mental representations of its environment. To show this, it will first be argued that although mental representing is a common thing indeed, representationalism, in the most important sense of that term (indirect representationalism), is false. Three different views about pictorial thinking (mental imagery, intuitive representing) are then contrasted, two of which are tied to this brand of representationalism and one of which is not. The latter view, versions of which have sometimes been presented as ”simulation” theories of imagery, is here generalised to cover all kinds of mental representation. Two models of the brain are then presented in which learning of adaptive representations follows from this theory together with certain biologically plausible constraints.

The emulation theory of representation articulated in the target article is further explained and explored in this response to commentaries. Major topics include: the irrelevance of equilibrium-point and related models of motor control to the theory; clarification of the particular sense of “representation” which the emulation theory of representation is an account of; the relation between the emulation framework and Kalman filtering; and addressing the empirical data considered to be in conflict with the emulation theory. In addition, I discuss the further empirical support for the emulation theory provided by some commentators, as well as a number of suggested theoretical applications.

The notion of representation has become ubiquitous throughout cognitive psychology, cognitive neuroscience and the cognitive sciences generally. This paper addresses the status of mental representations as entities that have been posited to explain cognition. I do so by examining similarities between mental representations and sense-data in both their characteristics and key arguments offered for each. I hope to show that more caution in the adoption and use of representations in explaining cognition is warranted. Moreover, by paying attention to problematic notions of representations, a less problematic sense of representation might emerge.

Almost all representations have both distributed and localist aspects, depending upon what properties of the data are being considered. With noisy data, features represented in a localist way can be detected very efficiently, and in binary representations they can be counted more efficiently than those represented in a distributed way. Brains operate in noisy environments, so the localist representation of behaviourally important events is advantageous, and fits what has been found experimentally. Distributed representations require more neurons to perform as efficiently, but they do have greater versatility.

There are two distinct interpretations of the role that Feynman diagrams play in physics: (i) they are calculational devices, a type of notation designed to keep track of complicated mathematical expressions; and (ii) they are representational devices, a type of picture. I argue that Feynman diagrams not only have a calculational function but also represent: they are in some sense pictures. I defend my view through addressing two objections and in so doing I offer an account of representation that explains why Feynman diagrams represent. The account that I advocate is a version of that defended by Kendall Walton, which provides us with a basic characterization of the way that representations in general work and is particularly useful for understanding distinctively pictorial representations - in Walton's terms, depictions. The question of the epistemic function of Feynman diagrams as pictorial representations is left for another time.