Zenon Pylyshyn

This paper argues that a theory of situated vision, suited for the dual purposes of object recognition and the control of action, will have to provide something more than a system that constructs a conceptual representation from visual stimuli: it will also need to provide a special kind of direct (preconceptual, unmediated) connection between elements of a visual representation and certain elements in the world. Like natural language demonstratives (such as `this' or `that') this direct connection allows entities to be referred to without being categorized or conceptualized. Several reasons are given for why we need such a preconcep- tual mechanism which individuates and keeps track of several individual objects in the world. One is that early vision must pick out and compute the relation among several individual objects while ignoring their properties. Another is that incrementally computing and updating representations of a dynamic scene requires keeping track of token individuals despite changes in their properties or locations. It is then noted that a mechanism meeting these requirements has already been proposed in order to account for a number of disparate empiri- cal phenomena, including subitizing, search-subset selection and multiple object tracking (Pylyshyn et al., Canadian Journal of Experimental Psychology 48(2) (1994) 260). This mechanism, called a visual index or FINST, is brie

People have always wondered how thinking takes place and what thoughts are constructed from. We typically experience our thoughts as involving pictorial (or sensory) contents or as being in words. Although this idea has been enshrined in psychology as the “dual code” theory of reasoning and memory, serious questions have been raised concerning this view. It appears that whatever the form of our thoughts it is unlikely that it is anything like our experience of them. But if thought is not in pictures or words, what form does it take? If we do not sometimes think in words, then what actually goes on when we think by engaging in an “inner dialogue”? And if we do not sometimes think in pictures, what goes on when we reason by creating and examining “mental images”?

You might reasonably surmise from the title of this paper that I will be discussing a theory of vision. After all, what is a theory of vision but a theory of how the world is connected to our visual representations? Theories of visual perception universally attempt to give an account of how a proximal stimulus (presumably a pattern impinging on the retina) can lead to a rich representation of a three dimensional world and thence to either the recognition of known objects or to the coordination of actions with visual information. Such theories typically provide an effective (i.e., computable) mapping from a 2D pattern to a representation of a 3D scene, usually in the form of a symbol structure. But such a mapping, though undoubtedly the essential purpose of a theory of vision, leaves at least one serious problem that I intend to discuss here. It is this problem, rather than a theory of vision itself, that is the subject of this talk

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of?

In three experiments, subjects attempted to track multiple items as they moved independently and unpredictably about a display. Performance was not impaired when the items were briefly (but completely) occluded at various times during their motion, suggesting that occlusion is taken into account when computing enduring perceptual objecthood. Unimpaired performance required the presence of accretion and deletion cues along fixed contours at the occluding boundaries. Performance was impaired when items were present on the visual field at the same times and to the same degrees as in the occlusion conditions, but disappeared and reappeared in ways which did not implicate the presence of occluding surfaces (e.g. by imploding and exploding into and out of existence, instead of accreting and deleting along a fixed contour). Unimpaired performance did not require visible occluders (i.e. Michotte’s tunnel effect) or globally consistent occluder positions. We discuss implications of these results for theories of objecthood in visual attention.

In the past decade there has been renewed interest in the study of mental imagery. Emboldened by new findings from neuroscience, many people have revived the idea that mental imagery involves a special format of thought, one that is pictorial in nature. But the evidence and the arguments that exposed deep conceptual and empirical problems in the picture theory over the past 300 years have not gone away. I argue that the new evidence from neural imaging and clinical neuropsychology does little to justify this recidivism because it does not address the format of mental images. I also discuss some reasons why the picture theory is so resistant to counterarguments and suggest ways in which non-pictorial theories might account for the apparent spatial nature of images.

The target article claimed that although visual apprehension involves all of general cognition, a significant component of vision (referred to as early vision) works independently of cognition and yet is able to provide a surprisingly high level interpretation of visual inputs, roughly up to identifying general shape-classes. The commentators were largely sympathetic, but frequently disagreed on how to draw the boundary, on exactly what early vision delivers, on the role that attention plays, and on how to interpret the neurophysiological data showing top-down effects. A significant number simply asserted that they were not willing to accept any distinction between vision and cognition, and a surprising number even felt that we could never tell for sure, so why bother? Among the topics covered was the relation of cognition and consciousness, the relation of early vision to other modules such as face recognition and language, and the role of natural constraints.

Although the study of visual perception has made more progress in the past 40 years than any other area of cognitive science, there remain major disagreements as to how closely vision is tied to general cognition. This paper sets out some of the arguments for both sides and defends the position that an important part of visual perception, which may be called early vision or just vision, is prohibited from accessing relevant expectations, knowledge and utilities - in other words it is cognitively impenetrable. That part of vision is complex and articulated and provides a representation of the 3-D surfaces of objects sufficient to serve as an index into memory, with somewhat different outputs being made available to other systems such as those dealing with motor control. The paper also addresses certain conceptual and methodological issues, including the use of signal detection theory and event-related potentials to assess cognitive penetration of vision. A distinction is made among several stages in visual processing. These include, in addition to the inflexible early-vision stage, a pre-perceptual attention allocation stage and a post-perceptual evaluation, memory-accessing, and inference stage which provide several different highly constrained ways in which cognition can affect the outcome of visual perception. The paper discusses arguments that have been presented in both computer vision and psychology showing that vision is "intelligent" and involves elements of problem solving". It is suggested that these cases do not show cognitive penetration, but rather they show that certain natural constraints on interpretation, concerned primarily with optical and geometrical properties of the world, have been compiled into the visual system. The paper also examines a number of examples where instructions and "hints" are alleged to affect

This commentary argues that the “illusion” to which Wegner refers in The Illusion of Conscious Will is actually the illusion that our conscious experience of mentally causing certain behaviors explains the behavior in question: It is not the subjective experience itself that is illusory, but the implied causal explanation. The experience of “mental effort” is cited as another example of this sort of illusion. Another significant example is the experience that properties of the representation of our mental images are responsible for certain patterns of behavior observed in mental imagery experiments. Examples include the increase in reaction time found when details are reported from smaller images or when attention is switched between different places and features (imagined as further apart than they are) within a single image. These examples illustrate the nature of the “illusion” involved: It is the illusion that certain observed regularities occur because of the content of the experience, as opposed to the converse – that experience has the content it does because of what the person figures out would happen in the imagined situation.

In Multiple Object Tracking (MOT), an observer is able to track 4 – 5 objects in a group of otherwise indistinguishable objects that move independently and unpredictably about a display. According to the Visual Indexing Theory (Pylyshyn, 1989), successful tracking requires that target objects be indexed while they are distinct -- before tracking begins. In the typical MOT task, the target objects are briefly flashed resulting in the automatic assignment of indexes. The question arises whether indexes are only assigned automatically or whether they can be assigned voluntarily in a top-down manner. This study compares several ways of specifying which of 8 items are the targets to be tracked. In the Flash condition the target items were flashed, in the Nonflash condition the targets were the items not flashed, and in the Number condition the targets were specified by number (e.g., items numbered 1-4). The results showed no difference between the three conditions, suggesting that tracking was possible with either voluntary or involuntary indexing. The second experiment tested the hypothesis that voluntary indexing is possible only if the target items are visited serially. The conditions were the same as experiment 1 except that the time available for index assignment was too short to allow targets to be visited serially. In this experiment, targets flashed only once (or, in the Numbers condition, remained visible for about 400 ms). The results showed a decrease in tracking performance for the Number condition, but the Flash and the Nonflash conditions did not differ, suggesting that as long as the designation of targets was done rapidly, the observer did not have to visit each target serially in order to index it. These results suggest that indexing can occur both automatically and voluntarily, and without serially visiting them, so long as the items are successfully specified.

Each of the chapters in this volume devotes considerable attention to defining and elaborating the notion of the frame problem-one of the hard problems of artificial intelligence. Not only do the chapters clarify the problems at hand, they shed light on the different approaches taken by those in artificial intelligence and by certain philosophers who have been concerned with related problems in their field. The book should therefore not be read merely as a discussion of the frame problem narrowly conceived, but also as a general analysis of what could be a major challenge to the design of computer systems exhibiting general intelligence.

We present three studies examining whether multiple-object tracking (MOT) benefits from the active inhibition of nontargets, as proposed in (Pylyshyn, 2004). Using a probedot technique, the first study showed poorer probe detection on nontargets than on either the targets being tracked or in the empty space between objects. The second study used a matching nontracking task to control for possible masking of probes, independent of target tracking. The third study examined how localized the inhibition is to individual nontargets. The result of these three studies led to the conclusion that nontargets are subject to a highly localized object-based inhibition. Implications of this finding for the FINST visual index theory are discussed. We suggest that we need to distinguish between the differentiation (or individuation) of enduring token objects and the process of making the objects accessible through indexes, with only the latter being limited to 4 or 5 objects

The target article proposes that visual experience arises when sensorimotor contingencies are exploited in perception. This novel analysis of visual experience fares no better than the other proposals that the article rightly dismisses, and for the same reasons. Extracting invariants may be needed for recognition, but it is neither necessary nor sufficient for having a visual experience. While the idea that vision involves the active extraction of sensorimotor invariants has merit, it does not replace the need for perceptual representations. Vision is not just for the immediate controlling of action; it is also for finding out about the world, from which inferences may be drawn and beliefs changed.