The relations between automatic processing and consciousness are discussed in this paper. It is argued that automatic processing should not be identified with the absence of consciousness. The organism has access to representations resulting from automatic processing, but these representations, in contrast to the representations resulting from nonautomatic processing, are not propositional. Therefore monitoring of the process, the defining feature of nonautomatic processing, is not possible.

Posner & Raichle (1994) is a nice addition to the Scientific American Library and the average reader will both enjoy the book and learn a great deal. As an activeresearcher, however, I find the book disappointing in many respects. My two major disappointments are in the illusion of computation that is created throughout the volume and in the inadequate perspective of the presentation on visual attention.

This paper argues that intelligence can be approximated by the ability to produce accurate predictions. It is further argued that general intelligence can be approximated by context dependent predictive abilities combined with the ability to use working memory to abstract away contextual information. The flexibility associated with general intelligence can be understood as the ability to use selective attention to focus on specific aspects of sensory impressions to identify patterns, which can then be used to predict events in novel situations (...) and environments. The argumentation synthesizes Godfrey-Smith’s environmental complexity theory, adding the notion of niche broadness as well as changes concerning the view of cognition and control, and Hohwy’s predictive mind theory, making explicit the significance of accuracy as a composite of trueness and precision where the nervous system acts as a distributed controller motivating actions that keep the body in homeostasis. (shrink)

This paper argues that intelligence can be approximated by the ability to produce accurate predictions. It is further argued that general intelligence can be approximated by context dependent predictive abilities combined with the ability to use working memory to abstract away contextual information. The flexibility associated with general intelligence can be understood as the ability to use selective attention to focus on specific aspects of sensory impressions to identify patterns, which can then be used to predict events in novel situations (...) and environments. The argumentation synthesizes Godfrey-Smith’s environmental complexity theory, adding the notion of niche broadness as well as changes concerning the view of cognition and control, and Hohwy’s predictive mind theory, making explicit the significance of accuracy as a composite of trueness and precision where the nervous system acts as a distributed controller motivating actions that keep the body in homeostasis. (shrink)

In this response, we clarify several misunderstandings of the understanding/acceptance principle and defend our specific operationalization of that principle. We reiterate the importance of addressing the problem of rational task construal and we elaborate the notion of computational limitations contained in our target article. Our concept of thinking dispositions as variable intentional-level styles of epistemic and behavioral regulation is explained, as is its relation to the rationality debate. Many of the suggestions of the commentators for elaborating two-process models are easily (...) integrated into our generic dual-process account. We further explicate how we view the relation between System 1 and System 2 and evolutionary and normative rationality. We clarify our attempt to fuse the contributions of the cognitive ecologists with the insights of the original heuristics and biases researchers. (shrink)

The authors ofImages of the Mindhave made a significant contribution to our understanding of the brain through imaging technology. The book is well written, timely, beautifully illustrated and conveys a sense of history. It will appeal to alay audience as well as a professional audience.

One necessary condition on any adequate account of perception is clarity regarding whether unconscious perception exists. The issue is complicated, and the debate is growing in both philosophy and science. In this paper we consider the case for unconscious perception, offering three primary achievements. First, we offer a discussion of the underspecified notion of central coordinating agency, a notion that is critical for arguments that purportedly perceptual states are not attributable to the individual, and thus not genuinely perceptual. We develop (...) an explication of what it is for a representational state to be available to central coordinating agency for guidance of behavior. Second, drawing on this explication, we place a more careful understanding of the attributability of a state to the individual in the context of a range of empirical work on vision-for-action, saccades, and skilled typing. The results place pressure on the skeptic about unconscious perception. Third, reflecting upon broader philosophical themes running through debates about unconscious perception, we highlight how our discussion places pressure on the view that perception is a manifest kind, rather than a natural kind. In doing so, we resist the tempting complaint that the debate about unconscious perception is merely verbal. (shrink)

Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large (...) body of systemic knowledge and perform a range of inferences with such speed? We describe a computational model that takes a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables and perform a class of inferences in a few hundred milliseconds. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model (which we refer to as SHRUTI) achieves this by representing (1) dynamic bindings as the synchronous firing of appropriate nodes, (2) rules as interconnection patterns that direct the propagation of rhythmic activity, and (3) long-term facts as temporal pattern-matching subnetworks. The model is consistent with recent neurophysiological evidence that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific psychologically significant predictions about the nature of reflexive reasoning. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization. (shrink)

The results of four experiments provide evidence for controlled processing in the absence of awareness. Participants identified the colour of a neutral distracter word. Each of four words was presented in one of the four colours 75% of the time or 50% of the time . Colour identification was faster when the words appeared in the colour they were most often presented in relative to when they appeared in another colour, even for participants who were subjectively unaware of any contingencies (...) between the words and the colours. An analysis of sequence effects showed that participants who were unaware of the relation between distracter words and colours nonetheless controlled the impact of the word on performance depending on the nature of the previous trial. A block analysis of contingency-unaware participants revealed that contingencies were learned rapidly in the first block of trials. Experiment 3 showed that the contingency effect does not depend on the level of awareness, thus ruling out explicit strategy accounts. Finally, Experiment 4 showed that the contingency effect results from behavioural control and not from semantic association or stimulus familiarity. These results thus provide evidence for implicit control. (shrink)

There are methodological problems with the new techniques reviewed by Posner & Raichle. Some brain mechanisms are not detected by the temporal and spatial resolution. Questions are also raised by the stimulation paradigms.