It is common to distinguish two great families of representation. Symbolic representations include logical and mathematical symbols, words, and complex linguistic expressions. Iconic representations include dials, diagrams, maps, pictures, 3-dimensional models, and depictive gestures. This essay describes and motivates a new way of distinguishing iconic from symbolic representation. It locates the difference not in the signs themselves, nor in the contents they express, but in the semantic rules by which signs are associated with contents. The two kinds of rule have (...) divergent forms, occupying opposite poles on a spectrum of naturalness. Symbolic rules are composed entirely of primitive juxtapositions of sign types with contents, while iconic rules determine contents entirely by uniform natural relations with sign types. This distinction is marked explicitly in the formal semantics of familiar sign systems, both for atomic first-order representations, like words, pixel colors, and dials, and for complex second-order representations, like sentences, diagrams, and pictures. (shrink)

Cognitive representations are typically analysed in terms of content, vehicle and format. While current work on formats appeals to intuitions about external representations, such as words and maps, in this paper we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, i.e., the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, it makes space for a variety (...) of different formats, and is intimately tied to the computational approach to cognition in cognitive science and artificial intelligence. (shrink)

Episodic memory is memory for past events. It’s characteristically associated with an experience of ‘mentally replaying’ one’s experiences in the mind’s eye. This biological phenomenon has inspired the development of several ‘experience replay’ algorithms in AI. In this chapter, I ask whether experience replay algorithms might shed light on a puzzle about episodic memory’s function: what does episodic memory contribute to the cognitive systems in which it is found? I argue that experience replay algorithms can serve as idealized models of (...) episodic memory for the purposes of addressing this question. Taking the DQN algorithm as a case study, I suggest that these algorithms provide some support for mnemonic accounts, on which episodic memory’s function lies in the storage, encoding and retrieval of information. By extending and adapting experience replay algorithms, we might gain further insight into episodic memory’s operations and contributions to cognition. (shrink)

Analog representations come in different types. One distinction is between those representations that have parts that are themselves representations and those that do not (i.e., those for which the Parts Principle is true and those for which it is not). I offer a unified account of analog representation, showing what all types have in common. This account clarifies when the Parts Principle applies and when it does not, thereby illuminating why the Parts Principle is less interesting than one might have (...) thought. Understanding analog representation instead requires understanding the kinds of magnitudes used in a particular representation, and the kinds of variation possible within a representational scheme. (shrink)

Building on Christopher Peacocke’s account of analog perceptual contentand my own account of analog perceptual vehicles, I defend three claims: that theperception of magnitudes often has analog contents; that the perception of magni-tudes often has analog vehicles; and that the first claim is true in virtue of the second—that is, the analog vehicles help to ground the analog contents.

Peter Godfrey-Smith recently introduced the idea of representational ‘organization’. When a collection of representations form an organized family, similar representational vehicles carry similar contents. For example, where neural firing rate represents numerosity (an analogue magnitude representation), similar firing rates represent similar numbers of items. Organization has been elided with structural representation, but the two are in fact distinct. An under-appreciated merit of representational organization is the way it facilitates computational processing. Representations from different organized families can interact, for example to (...) perform addition. Their being organized allows them to implement a useful computation. Many of the cases where organization has seemed significant, but which fall short of structural representation, are cases where representational organization underpins a computationally useful processing structure. (shrink)

An influential objection to the epistemic power of the imagination holds that it is uninformative. You cannot get more out of the imagination than you put into it, and therefore learning from the imagination is impossible. This paper argues, against this view, that the imagination is robustly informative. Moreover, it defends a novel account of how the imagination informs, according to which the imagination is informative in virtue of its analog representational format. The core idea is that analog representations represent (...) relations ‘for free,’ and this explains how the imagination can contain more information than is put into it. This account makes important contributions to both philosophy of mind, by showing how the imagination can generate new content that is not represented by a subject’s antecedent mental states, and epistemology, by showing how the imagination can generate new justification that is not conferred by a subject’s antecedent evidence. (shrink)

Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal scale of observation. (...) My argument begins by introducing the “cognitive neuroscience revolution” (Sect. 1 ) and sketching a prominent, widely adopted account of structural representations (Sect. 2 ). Then, I will consult various reports that describe our neuronal activity at various spatiotemporal scales, arguing that none of them reports the presence of structural representations (Sect. 3 ). After having deflected certain intuitive objections to my analysis (Sect. 4 ), I will conclude that, in the absence of neural structural representations, representationalism and mechanism can’t go together, and so the “cognitive neuroscience revolution” is forced to abandon one of its commitments (Sect. 5 ). (shrink)

We motivate five constraints on theorizing about sensory experience. We then propose a novel form of naturalistic intentionalism that succeeds where other theories fail by satisfying all of these constraints. On the proposed theory, which we call structure matching tracking intentionalism, brains states track determinables. Internal structural features of those states select determinates of those determinables for presentation in experience. We argue that this theory is distinctively well-positioned to both explain internal-phenomenal structural correlations and accord external features a role in (...) fixing phenomenology. In addition, we use the theory to shed light on how one comes to experience “missing shades”. (shrink)

The imagination is ubiquitous in our cognitive lives. You might imagine rotating a puzzle piece to determine whether it fits in an open space, or imagine what things are like from another person's perspective to figure out how they are feeling, or imagine a new rug in your living room to determine whether it matches the color of your sofa. These examples are mundane, but they point to a deep philosophical puzzle: how could merely imagining something give you any reason (...) to believe that it is true? After all, you can imagine anything you want to, from the fictional to the fantastical. This has led many philosophers to be deeply skeptical of the epistemic value of the imagination. When imagination is accorded a justificatory role, it is typically limited to beliefs about what is metaphysically possible. More recently, some philosophers have begun to push back against this orthodoxy by arguing that the imagination can justify empirical beliefs about the actual world. But even then, most contemporary discussions focus on whether the imagination can justify empirical belief, rather than on how the imagination justifies empirical belief, thereby leaving many central questions about the epistemology of the imagination unanswered. This dissertation attempts to fill this lacuna by canvassing the theoretical landscape of this exciting new literature and developing an account of the epistemic structure of the imagination. The first chapter sets the stage for the rest of the dissertation by reviewing extant arguments for and against the view that the imagination can justify empirical belief before posing a new argument in its favor. The second chapter argues that imaginative justification is mediate but non-inferential; it depends on one’s prior justification without depending on an inference from one’s prior beliefs. The third chapter argues that the imagination is informative—it can represent new content and generate new justification—in virtue of its analog representational format. The fourth and final chapter argues that some imaginings just are beliefs, and that this grounds their justificatory force. Together, the arguments of this dissertation suggest that the imagination is a distinctive kind of ampliative reasoning, and that it plays this cognitive and epistemic role by combining the analog representational format of imagery with the evidence-sensitive function of belief. (shrink)