Heemskerk, Johan (2025) How Informational Teleosemantics Works: Towards a Realist Theory of Content. UNSPECIFIED, University of Warwick.
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Abstract
Representations appear to play a central role in cognitive science. Capacities such as face recognition are thought to be enabled by internal states or structures representing external items. However, despite the ubiquity of representational terminology in cognitive science, there is no explicit scientific theory outlining what makes an internal state a representation of an external item. Nonetheless, many philosophers hope to uncover an implicit theory in the scientific literature. This is the project of the current thesis. However, all such projects face an obstacle in the form of Frances Egan's argument that content plays no role in scientific theorising. I respond that, in some limited regions of cognitive science, content is crucial for explanation. The unifying idea is that closer attention to the application of information theory in those regions of cognitive neuroscience enables us to uncover an implicit theory of content. I examine the conditions which must be met for the cognitive system to be modelled using information theory, presenting some constraints on how we apply the mathematical framework. For example, information theory requires identifying probability distributions over measurable outcomes, which leads us to focus specifically on neural representation. I then argue that functions are required to make tractable measures of information, since they serve to narrow the range of possible contents to those potentially explanatory of a cognitive capacity. However, unlike many other teleosemanticists, I argue that we need to use a non-etiological form of function. I consider whether non-etiological functions allow for misrepresentation, and conclude that they do. Finally, I introduce what I argue is the implicit theory of content in cognitive neuroscience: maxMI. The content of a representation is that item in the environment with which the representation shares maximal mutual information.
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