Zenon Pylyshyn

Assuming that the vehicle of imaginal thought is a spatial model may not be quite as egregious an error as assuming it is a two-dimensional picture, but it represents no less a reification error. Because the model is not a literal physical layout, one is still owed an explanation of why spatial properties hold in the model – whether because of architectural constraints or by stipulation. The difference is like the difference between explaining behavior from a principle and predicting it by looking it up in a list. In the latter case no purpose is being served by calling it a mental model.

A major cognitive framework for individuating, visualizing, and keeping track of different items of knowledge (such as who said what in a conference or what items of data go with what) is the use of real 3D spatial locations. We use space both literally (as in the desktop or office model of data organization) and also figuratively. Examples of the latter includes such techniques as mentally locating different facts and premises in certain imagined spatial loci -- a technique widely used in mnemonic aids, and the use of spatial location in reasoning where so-called "spatial paralogic" provides an important scheme for keeping track of different components of a problem. The use of distinct spatial loci in reasoning and visualizing can be enhanced and its effectiveness in communication increased if distinct spatial locations can be shared. This, of course, happens routinely when people use gestures, pointing, and carving shapes in the air when they converse. Sharing a common workspace and conceptual space is now becoming technologically feasible through the use of interactive multimedia workstations, in which sound and 3D visual locations can be communicated and spatial indicators such as pointing in space can form part of the human-computer interaction.

The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of human functioning that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis. Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the " cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories

We previously reported that in the Multiple Object Tracking (MOT) task, which requires tracking several identical targets moving unpredictably among identical nontargets, the nontargets appear to be inhibited, as measured by a probe-dot detection method. The inhibition appears to be local to nontargets and does not extend to the space between objects – dropping off very rapidly away from targets and nontargets. In the present three experiments we show that (1) nontargets that are identical to targets but remain in a fixed location are not inhibited and (2) moving objects that have a different shape from targets are inhibited as much as same-shape nontargets, and (3) nontargets that are on a different depth plane and so are easily filtered out are not inhibited. This is consistent with a taskdependent view of item inhibition wherein nontargets are inhibited if (and only if) they are likely to be mistaken for targets.

Marr (1982) may have been one of the rst vision researchers to insist that in modeling vision it is important to separate the location of visual features from their type. He argued that in early stages of visual processing there must be “place tokens” that enable subsequent stages of the visual system to treat locations independent of what specic feature type was at that location. Thus, in certain respects a collinear array of diverse features could still be perceived as a line, and under certain conditions could function as such in perceptual phenomena like the Poggendorf illusion

I’m one of those who is awed and impressed by the potential of this field and have devoted some part of my energy to persuading people that it is a positive force. I have done so largely on the grounds of its economic benefits and it potential for making the fruits of computer technology more generally available to the public — for example, to help the overworked physician; to search for oil and minerals and help manage our valuable resources; to explore, mine, and experimentindangerousenvironments;toallowthenon-computingpublicaccesstovast libraries of important information and even advice, and in the process give real meaning to the..

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