Jonathan Opie

Although connectionism is advocated by its proponents as an alternative to the classical computational theory of mind, doubts persist about its _computational_ credentials. Our aim is to dispel these doubts by explaining how connectionist networks compute. We first develop a generic account of computation—no easy task, because computation, like almost every other foundational concept in cognitive science, has resisted canonical definition. We opt for a characterisation that does justice to the explanatory role of computation in cognitive science. Next we examine what might be regarded as the “conventional” account of connectionist computation. We show why this account is inadequate and hence fosters the suspicion that connectionist networks aren’t genuinely computational. Lastly, we turn to the principal task of the paper: the development of a more robust portrait of connectionist computation. The basis of this portrait is an explanation of the representational capacities of connection weights, supported by an analysis of the weight configurations of a series of simulated neural networks

One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or the philosophy of mind. Our response is quite different. We believe that, once properly formulated, Cartesian materialism is no straw man. Rather, it is an attractive hypothesis about the relationship between the computational architecture of the brain and phenomenal consciousness, and hence one that is worthy of further exploration. Consequently, our primary aim in this paper is to defend Cartesian materialism from Dennett’s assault. We do this by showing that Dennett’s argument against this position is founded on an implicit assumption (about the relationship between phenomenal experience and information coding in the brain), which while valid in the context of classical cognitive science, is not forced on connectionism

When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between a counter-intuitive theory or no theory at all. We offer a way out of this dilemma. We argue that the computational theory of mind doesn't force cognitive scientists to explain consciousness in terms of computational processes, as there is an alternative strategy available: one that focuses on the representational vehicles that encode information in the brain. This alternative approach to consciousness allows us to do justice to the standard intuitions about phenomenal experience, yet remain within the confines of cognitive science

We think the best prospect for a naturalistic explanation of phenomenal consciousness is to be found at the confluence of two influential ideas about the mind. The first is the _computational _ _theory of mind_: the theory that treats human cognitive processes as disciplined operations over neurally realised representing vehicles.1 The second is the _representationalist theory of _ _consciousness_: the theory that takes the phenomenal character of conscious experiences (the “what-it-is-likeness”) to be constituted by their representational content.2 Together these two theories suggest that phenomenal consciousness might be explicable in terms of the representational content of the neurally realised representing vehicles that are generated and manipulated in the course of cognition. The simplest and most elegant hypothesis that one might entertain in this regard is that conscious experiences are identical to (i.e., are one and the same as) the brain’s representing vehicles

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are _dissociable_, and on the other, by the _classical_ computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of _connectionism; _and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: _phenomenal experience consists in the explicit_ _representation of information in neurally realized PDP networks_..

In general, there are two ways to approach cognition. One is to start with the features of the human case and try to generalize to other species. Another is to start with the biological conditions under which natural cognition evolved and currently operates and ask what organisms do such that they might require cognition. A full account of cognition requires both. Cognitive biology, however, requires a biogenic approach. Tight integration with biological knowledge places strong constraints on cognitive explanation. These constraints arise from the fact that cognition evolved in a particular context with very special features. All organisms are complex, self-organizing, dynamical systems that exist far from thermodynamic equilibrium and actively maintain themselves in this statistically improbable state by continuously manufacturing the components of the processes that sustain them. Organisms thus must interact with the world in ways that allow them to actively secure matter and energy. They are also persistence-valuing systems: most organisms have mechanisms for resisting or avoiding perturbations that threaten their integrity. A biogenic approach thus stresses the role of mechanisms that facilitate system persistence, for example, those that integrate information concerning external and internal states of affairs to facilitate adaptive behaviour; differentiate some states of affairs from others; invest different properties of the environment with different degrees of salience; appraise system needs relative to prevailing conditions, the potential for interaction, and whether the current interaction is succeeding ; and reduce the impact of random perturbations on system functioning, of which there are many, potentially lethal sources. These are recognisably cognitive functions. Mounting evidence suggests that even bacteria grapple with problems long familiar to cognitive scientists, including: integrating information from multiple sensory channels to marshal an effective response to fluctuating conditions; making decisions under conditions of uncertainty; communicating with conspecifics and others ; and coordinating collective behaviour to increase the chances of survival. Thus a biogenic approach not only justifies the use of very simple biological models to study cognition, it suggests that this is precisely where we ought to look to ascertain the general logic of the function, as well as the mechanisms that carry it out.