Kevin Connolly

This report highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012: 1. How should we demarcate perceptual learning from perceptual development? 2. What are the origins of multimodal associations? 3. Does our representation of time provide an amodal framework for multi-sensory integration? 4. What counts as cognitive penetration? 5. How can philosophers and psychologists most fruitfully collaborate?

One of the central limitations of sensory substitution devices (SSDs) is their inability to reproduce the non-sensory feelings that are normally associated with visual experiences, especially hedonic and aesthetic responses. This limitation is sometimes reported to cause SSD users frustration. To make matters worse, it is unclear that improvements in acuity, bandwidth, or training will resolve the issue. Yet, if SSDs are to actually reproduce visual experience in its fullness, it seems that the reproduction of non-sensory feelings will be of some importance. We offer a novel solution. Researchers can produce hedonic and aesthetic responses by eliciting these feelings artificially, pairing distal objects that should be pleasurable to pleasurable stimulus outputs from the SSD. We outline two strategies for accomplishing this: first, by means of a prefixed, hardwired, association of pleasant distal objects to pleasant stimulus outputs from the SSD; second, by means of a flexible, feedback-based association which creates associations based on a subject-directed matching of distal objects to patterns of stimuli from the SSD which the subject takes to have the corresponding hedonic properties. We evaluate some problems with both strategies, and we argue that the feedback-based strategy is more promising. Researchers can use this strategy to help the blind, allowing them to take pleasure in the objects they perceive using SSDs.

When a user integrates a sensory substitution device into her life, the process involves perceptual learning, that is, ‘relatively long-lasting changes to an organism’s perceptual system that improve its ability to respond to its environment’ (Goldstone 1998: 585). In this paper, I explore ways in which the extensive literature on perceptual learning can be applied to help improve sensory substitution devices. I then use these findings to answer a philosophical question. Much of the philosophical debate surrounding sensory substitution devices concerns what happens after perceptual learning occurs. In particular, should the resultant perceptual experience be classified in the substituted modality (as vision), in the substituting modality (as auditory or tactile), or in a new sense modality? I propose a novel empirical test to help resolve this philosophical debate.

We seem perfectly able to perceive fine-grained shades of colour even without possessing precise concepts for them. The same might be said of shapes. I argue that this is in fact not the case. A subject can perceive a colour or shape only if she possesses a concept of that type of colour or shape. I provide new justification for this thesis, and do not rely on demonstrative concepts such as THIS SHADE or THAT SHAPE, a move first suggested by John McDowell, but rejected by Christopher Peacocke and Richard Heck among others.1.

Suppose that you are at a live jazz show. The drummer begins a solo. You see the cymbal jolt and you hear the clang. But in addition seeing the cymbal jolt and hearing the clang, you are also aware that the jolt and the clang are part of the same event. Casey O’Callaghan (forthcoming) calls this awareness “intermodal feature binding awareness.” Psychologists have long assumed that multimodal perceptions such as this one are the result of a subpersonal feature binding mechanism (see Vatakis and Spence, 2007, Kubovy and Schutz, 2010, Pourtois et al., 2000, and Navarra et al., 2012). I present new evidence against this. I argue that there is no automatic feature binding mechanism that couples features like the jolt and the clang together. Instead, when you experience the jolt and the clang as part of the same event, this is the result of an associative learning process. The cymbal’s jolt and the clang are best understood as a single learned perceptual unit, rather than as automatically bound. I outline the specific learning process in perception called “unitization,” whereby we come to “chunk” the world into multimodal units. Unitization has never before been applied to multimodal cases. Yet I argue that this learning process can do the same work that intermodal binding would do, and that this issue has important philosophical implications. Specifically, whether we take multimodal cases to involve a binding mechanism or an associative process will have impact on philosophical issues from Molyneux’s question to the question of how active or passive we consider perception to be.

Experts from wine tasters to radiologists to bird watchers have all undergone perceptual learning-long-term changes in perception that result from practice or experience. Philosophers have been discussing such cases for centuries, from the 14th-century Indian philosopher Vedanta Desika to the 18th-century Scottish philosopher Thomas Reid, and into contemporary times. This book uses recent evidence from psychology and neuroscience to show that perceptual learning is genuinely perceptual, rather than post-perceptual. It also offers a taxonomy for classifying cases in the philosophical literature. In some cases, perceptual learning involves changes in how one attends; in other cases, it involves a learned ability to differentiate two properties, or to perceive two properties as unified. Connolly uses this taxonomy to rethink several domains of perception in terms of perceptual learning, including multisensory perception, color perception, and speech perception. As a whole, the book offers a theory of the function of perceptual learning. Perceptual learning embeds into our quick perceptual systems what would be a slower task were it to be done in a controlled, cognitive manner. A novice wine taster drinking a Cabernet Sauvignon might have to think about its features first and then infer the type of wine, while an expert can identify it immediately. This learned ability to immediately identify the wine enables the expert to think about other things like the vineyard or the vintage of the wine. More generally, perceptual learning serves to free up cognitive resources for other tasks. This book offers a comprehensive empirically-informed account, and explores the nature, scope, and theoretical implications of perceptual learning.