What is the content of a mental state? This question poses the problem of intentionality: to explain how mental states can be about other things, where being about them is understood as representing them. A framework that integrates predictive coding and signaling systems theories of cognitive processing offers a new perspective on intentionality. On this view, at least some mental states are evaluations, which differ in function, operation, and normativity from representations. A complete naturalistic theory of intentionality must account for (...) both types of intentional state. (shrink)

Natural information refers to the information carried by natural signs such as that smoke is thought to carry natural information about fire. A number of influential philosophers have argued that natural information can also be utilized in a theory of mental content. The most widely discussed account of natural information holds that it results from an extremely strong relation between sign and signified. Critics have responded that it is doubtful that there are many strong relations of this sort in the (...) natural world due to variability between signs and signified. In light of this observation, a promising suggestion is that much of the interesting natural information carried by natural signs is really information with a probabilistic content. However, Dretske’s theory cannot account for this information because it would require implausible second order objective probabilities. Given the most plausible understanding of the probabilities involved here, I argue that it is only sequences of traditional natural signs that carry this probabilistic information. Several implications of this idea will be explored. (shrink)

Commonsense psychology and cognitive science both regularly assume the existence of representational states. I propose a naturalistic theory of representation sufficient to meet the pretheoretical constraints of a "folk theory of representation", constraints including the capacities for accuracy and inaccuracy, selectivity of proper objects of representation, perspective, articulation, and "efficacy" or content-determined functionality. The proposed model states that a representing device is a device which changes state when information is received over multiple information channels originating at a single source. The (...) changed state of a representing device is a representation. The unitary information source which would give rise to the information impinging on the representing device, and hence, give rise to the representation, is the content of the representation. The model meets the pretheoretic constraints, and also conforms to available neurobiological data for two invertebrate species. (shrink)

This article responds to two unresolved and crucial problems of cognitive science: (1) What is actually accomplished by functions of the nervous system that we ordinarily describe in the intentional idiom? and (2) What makes the information processing involved in these functions semantic? It is argued that, contrary to the assumptions of many cognitive theorists, the computational approach does not provide coherent answers to these problems, and that a more promising start would be to fall back on mathematical communication theory (...) and, with the help of evolutionary biology and neurophysiology, to attempt a characterization of the adaptive processes involved in visual perception. Visual representations are explained as patterns of cortical activity that are enabled to focus on objects in the changing visual environment by constantly adjusting to maintain levels of mutual information between pattern and object that are adequate for continuing perceptual control. In these terms, the answer proposed to (1) is that the intentional functions of vision are those involved in the establishment and maintenance of such representations, and to (2) that semantic features are added to the information processes of vision with the focus on objects that these representations accomplish. The article concludes with proposals for extending this account of intentionality to the higher domains of conceptualization and reason, and with speculation about how semantic information-processing might be achieved in mechanical systems. (shrink)

Cohen and Meskin 2006 recently offered a counterfactual theory of information to replace the standard probabilistic theory of information. They claim that the counterfactual theory fares better than the standard account on three grounds: first, it provides a better framework for explaining information flow properties; second, it requires a less expensive ontology; and third, because it does not refer to doxastic states of the information-receiving organism, it provides an objective basis. In this paper, I show that none of these is (...) really an advantage. Moreover, the counterfactual theory fails to satisfy one of the basic properties of information flow, namely the Conjunction principle. Thus, I conclude, there is no reason to give up the standard probabilistic theory for the counterfactual theory of information. (shrink)