Nico Orlandi

This chapter offers an account of mental representation that spells out the conditions for representational status. I argue that we should draw a distinction between issues concerning content and issues concerning representational role, and that the challenge of understanding representational role is at least as pressing as the more familiar challenge of giving an account of content. I then argue that we should understand representational role in terms of serving as a stand-in, and use the idea of structural isomorphism, with examples from animal cognition and from the literature on analog representation, to capture standing-in.

This chapter discusses Andy Clark’s recent explorations of Bayesian perceptual models and predictive processing. In the first part, the chapter discusses the predictive processing (PP) framework, explicating its relationship with hierarchical Bayesian models in theories of perception. In the second part, it examines the relationship between perception and action in the PP model. The overarching goal is twofold: first, to get clearer on the picture of mental activity that Clark is presenting, including what exactly is represented at the levels of the perception/action hierarchy, and the nature of the information processing it postulates; second, although the framework presented by Clark certainly has interesting novel features, some of his glosses on it are misleading. In particular, Clark’s interpretation of predictive processing as essentially a top-down, expectation-driven process, on which perception is aptly thought of as “controlled hallucination,” exaggerates the contrast with the traditional picture of perception as bottom-up and stimulus-driven. Additionally, despite the rhetoric, Clark’s PP model substantially preserves the traditional distinction between perception and action.

Standard accounts of concepts in philosophy and in cognitive psychology hold that we learn a target concept by learning the concepts that constitute it. If this is the only model of learning we have, then only concepts that are complex or structured can be learned. I argue for an alternative to this framework by presenting a proposal for how we learn some atomic concepts. I show that we can learn a concept through descriptions without thinking that the concepts employed in the descriptions constitute the target concept. I develop this idea by using the notion of a mental file and by employing a general externalist explanatory strategy. In the view I develop, some concepts are akin to files in that the descriptions associated with a given concept are means of properly individuating the extension of the concept, and they are also means of connecting a concept to others, but they do not constitute the concept and can be revised or abandoned. I show how this discussion connects to issues in conceptual engineering.

It is increasingly common in cognitive science and philosophy of perception to regard perceptual processing as a probabilistic engine, taking into account uncertainty in computing representations of the distal environment. Models of this kind often postulate probabilistic representations, or what we will call probabilistic states,. These are states that in some sense mark or represent information about the probabilities of distal conditions. It has also been argued that perceptual experience itself in some sense represents uncertainty (Morrison _Analytic Philosophy_ 57 (1): 15 48, 2016 ). In this article, we will first consider three models of sensory activity from perceptual neuroscience, namely signal detection theory (SDT), probabilistic population codes (PPC), and sampling. We will then reflect on the sense in which the probabilistic states introduced in these models are probabilistic representations. To sharpen this discussion, we will compare and contrast these probabilistic states to credences as they are understood in epistemology. We will suggest that probabilistic representation, in an appropriately robust sense, can be understood as a form of analog representation. In the last part of the paper, we apply this to the issue of whether conscious experience represents uncertainty—we will interpret this as the claim that there are phenomenal features of experience that serve as analog probabilistic representations.

This paper questions two prima facie plausible claims concerning switching in the presence of ambiguous figures. The first is the claim that reversing is an instantaneous process. The second is the claim that the ability to reverse demonstrates the interpretive, inferential and constructive nature of visual processing. Empirical studies show that optical and cerebral events related to switching protract in time in a way that clashes with its perceived instantaneity. The studies further suggest an alternative theory of reversing: according to such alternative, seeing the same thing in multiple ways is a matter of uncovering what is already present to the senses through visual search

Standard models of visual perception hold that vision is an inferential or interpretative process. Such models are said to be superior to competing, non-inferential views in explanatory power. In particular, they are said to be capable of explaining a number of otherwise mysterious, visual phenomena such as multi-stable perception. Multi-stable perception paradigmatically occurs in the presence of ambiguous figures, single images that can give rise to two or more distinct percepts. Different interpretations are said to produce the different percepts. In this paper, I argue that a non-inferential account of visual perception is just as capable of explaining multi-stable perception. I propose an embedded understanding of vision, and show how the embedded account can, after properly qualifying them, use the explanatory resources of the inferential view to explain just what such a view explains.

Ambiguous figures pose a problem for representationalists, particularly for representationalists who believe that the content of perceptual experience is non-conceptual (MacPherson in Nous 40(1):82–117, 2006). This is because, in viewing ambiguous figures, subjects have perceptual experiences that differ in phenomenal properties without differing in non-conceptual content. In this paper, I argue that ambiguous figures pose no problem for non-conceptual representationalists. I argue that aspect shifts do not presuppose or require the possession of sophisticated conceptual resources and that, although viewing ambiguous figures often causes a change in phenomenal properties, this change is accompanied by a change in non-conceptual content. I illustrate the case by considering specific examples

Philosophers of perception widely agree that sensory properties, like color, are represented in perceptual experience. Arguments are usually needed to establish that something other than sensory properties, for example three-dimensional objects or kind properties, are part of perceptual content. Call the idea that sensory properties are represented in perceptual experience the Sensation View (SV). Given its widespread acceptance, we may expect to find strong reasons for holding SV. In this paper, I argue that we lack such reasons: SV is largely unjustified. We have surprisingly poor justification for thinking that sensory properties are represented in perception. By focusing on the case of vision, I show that an embedded understanding of visual perception, and empirical evidence in cognitive psychology, indicate that SV is far from warranted

Can one see one thing as another without possessing a concept of it? The answer to this question is intuitively negative. This is because seeing x as F is usually taken to consist in the application of the concept F to x . Seeing the duck-rabbit figure as a duck figure, for instance, involves applying the concept DUCK to the figure; thus, one cannot see the figure as the figure of a duck unless one has the concept of a duck and is able to deploy it when looking at the figure. Nearly by definition, then, one cannot see x as F without possessing a concept of F. Contrary to this line of reasoning, this article treats the question of whether we can see x as F without possessing a concept of F as an open and partially empirical question. Seeing x as F involves seeing x in a certain way, namely as F, and whether concepts are required in order to see something in a certain way is an open question. Accordingly, what follows offers a proposal for an alternative way of understanding seeing–as that does not appeal to concept application.

We investigated the possible causes of perceptual switching in ambiguous figures. Ambiguous figures are a special class of visual stimuli that can give rise to at least two alternative interpretations. Because the figures themselves stay the same, these stimuli are particularly suitable to study the dynamic changes in our visual apparatus that enable us to see the world in different ways. Recent studies stress the importance of both low-level and high-level processes in switching. We show that these processes lead to switching independently, and that, when they co-occur, they do not occur at exactly the same time.We take these results to indicate that perceptual switching is a radically multiply realizable process, in that various neurological states can instantiate it in a single individual from time to time. We reflect on the consequences of this conclusion for experiential realism, in particular the notion that embodiment misleads us in identifying psychological types

There is a certain excitement in vision science concerning the idea of applying the tools of bayesian decision theory to explain our perceptual capacities. Bayesian models are thought to be needed to explain how the inverse problem of perception is solved, and to rescue a certain constructivist and Kantian way of understanding the perceptual process. Anticlimactically, I argue both that bayesian outlooks do not constitute good solutions to the inverse problem, and that they are not constructivist in nature. In explaining how visual systems derive a single percept from underdetermined stimulation, orthodox versions of bayesian accounts encounter a problem. The problem shows that such accounts need to be grounded in Natural Scene Statistics (NSS), an approach that takes seriously the Gibsonian insight that studying perception involves studying the statistical regularities of the environment in which we are situated. Additionally, I argue that bayesian frameworks postulate structures that hardly rescue a constructivist way of understanding perception. Except for percepts, the posits of bayesian theory are not representational in nature. bayesian perceptual inferences are not genuine inferences. They are biased processes that operate over nonrepresentational states.