According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation (...) and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction. Key Words: concept learning; conceptual development; features; perceptual learning; stimulus encoding. (shrink)

We adapted the Bubbles procedure [Vis. Res. 41 (2001) 2261] to examine the effective use of information during the first 282 ms of face identification. Ten participants each viewed a total of 5100 faces sub-sampled in space–time. We obtained a clear pattern of effective use of information: the eye on the left side of the image became diagnostic between 47 and 94 ms after the onset of the stimulus; after 94 ms, both eyes were used effectively. This preference for the (...) eyes increased with practice, and was not solely due to the informativeness of the eyes for the task at hand. The bias for the eye on the left side of the image is explained in terms of hemispheric specialization. Although there were individual differences, most participants exhibited this pattern of effective use of information. An intriguing finding is that most participants displayed a clear sinusoidal modulation of effective use of attention through time with a frequency of about 10.6 Hz. (shrink)

We adapted the Bubbles procedure [Vis. Res. 41 (2001) 2261] to examine the effective use of information during the first 282 ms of face identification. Ten participants each viewed a total of 5100 faces sub-sampled in space–time. We obtained a clear pattern of effective use of information: the eye on the left side of the image became diagnostic between 47 and 94 ms after the onset of the stimulus; after 94 ms, both eyes were used effectively. This preference for the (...) eyes increased with practice, and was not solely due to the informativeness of the eyes for the task at hand. The bias for the eye on the left side of the image is explained in terms of hemispheric specialization. Although there were individual differences, most participants exhibited this pattern of effective use of information. An intriguing finding is that most participants displayed a clear sinusoidal modulation of effective use of attention through time with a frequency of about 10.6 Hz. (shrink)

Pylyshyn argues against representations with pictorial properties that would be superimposed on a scene. We present evidence against this view, and a new method to depict pictorial properties. We propose a continuum between the top-down generation of internal signals (imagery) and the bottom-up signals from the outside world. Along the continuum, superstitious perceptions provide a method to tackle representational issues.

Pylyshyn acknowledges that cognition intervenes in determining the nature of perception when attention is allocated to locations or properties prior to the operation of early vision. I present evidence that scale perception (one function of early vision) is cognitively penetrable and argue that Pylyshyn's criterion covers not a few, but many situations of recognition. Cognitive penetrability could be their modus operandi.

The origin of features from nonfeatural information is a problem that should concern all theories of object categorization and recognition, not just the flexible feature approach. In contrast to the idea that new features must originate from combinations of simpler fixed features, we argue that holistic features can be created from a direct imprinting on the visual medium. Furthermore, featural descriptions can emerge from processes that by themselves do not operate on feature detectors. Once acquired, features can be decomposed into (...) component features if required by other categorizations. We therefore argue that it is not necessary to separate holistic and componential approaches to representations, because the latter is a development of the former. The requirements for representational flexibility outstrip the performance of any existing computational models, but specific mechanisms of feature creation are discussed and evaluated. Challenges for feature creation mechanisms are discussed together with the constraints (perceptual, statistical, functional, and task) they will need to satisfy. (shrink)