Knowledge that Transforms

The history of psychology is full of disputes among various “-isms”: behaviorism, cognitivism, functionalism, and many others. Nevertheless, all are unanimous in their opposition to one other -ism: reductionism. From Skinner to Simon, there is tacit agreement that behavior (or mind) is a subject matter in its own right that need not, perhaps cannot, be “reduced to” neurophysiology. This consensus has begun to crack in recent decades, with advances in neurobiology and the growth of understanding of the properties of brainlike theoretical systems. What, then, is the status of the study of behavior in its own right? This paper proposes a framework in which realtime theoretical models provide the link between behavioral research and the structure and function of the nervous system. We argue that such models arise most naturally from studies at the behavioral level, especially when the behavior under study depends on context and remote past history, as in learning and memory. We conclude that Skinner was probably right to argue that behavior must be understood in its own right before we can expect to understand brain—behavior relations. But he was wrong in limiting behavioral science to descriptive laws and catalogs of input-output relationships.

Wasserman (1990a) has reported an experiment that shows that people's attributions of causality in circumstances where they have to make inferences from brief verbal descriptions correspond to the attributions they make in situations where they actually experience causal sequences, and on the basis of that result he has suggested that psychologists should search for general laws of learning that might account for correspondences such as this one. I briefly describe some further similarities that can be obtained between causal judgments in experienced and described situations. However, the suggestion that a common mechanism may be involved in the two cases is questioned. Instead, I suggest that the correspondence is little more than a coincidence: It does not arise from the operation of a common mechanism. Instead, I argue that people, along with other organisms, possess an associative learning mechanism that operates in experienced situations, but we also possess domain-specific causal beliefs and metabeliefs about causation. These latter two types of beliefs play little role in experienced causal situations, but can readily be applied in making causal attributions from descriptions.

Event related brain potentials (ERP) were recorded from 12 normal right-handed subjects from 13 midline and lateral scalp sites during a task that involved learning a list of 20 words in the auditory modality, followed by recognition memory testing in first the auditory and then the visual modality. Subjects were instructed to keypress to repeated words, which were randomly mixed with an equal number of novel distractor words. A decrement in the amplitude of the N4 component of ERPs and an increase in the P3 component was found following repeated words in the auditory condition, and this difference persisted across modalities to the visual condition, although the anterior-posterior distribution of the N4 difference changed between conditions. The cross-modal transfer of the repetition-induced N4 attenuation suggests that the N4 change may be modulated by a semantic (i.e., non-modality specific) memory trace, while the difference in its distribution between the auditory and visual conditions provides evidence for a modality-specific contribution to the N4 generator.

The most important problem confronting color science is the construction of a uniform color space, i.e., a geometrical model of color discrimination in which Euclidean distances between the points representing colors are proportional to perceived color differences. The traditional approach to the construction of a metric color space is based on the integration of just-noticeable color differences (Wyszecki & Stiles, 1982). Experimental data show, however, that the integral of just-noticeable differences between colors does not coincide with direct estimations of the subjective differences between the colors (Judd, 1967; Izmailov, 1980). We suggest another way to construct a uniform color space, namely, to analyze large color differences by multidimensional scaling. This paper reports three groups of experimental data of the measurement of large color differences. Based on these data, we suggest a new color space model taking into account nontraditional relations between threshold and suprathreshold differences. The first group of data includes the results of research on color discrimination for a set of equibright monochromatic lights. The second group includes data on the discrimination of achromatic light stimuli resulting from different relations between test and background luminances. The third group consists of results of color-naming classification of lights varying in chromaticity and brightness. Chromatic differences between spectral stimuli of equal brightness, varying in hue and saturation, and differences in brightness between achromatic lights varying in luminance were analyzed separately. The results are compared with a general color space of colors of different hue, saturation, and brightness. The color spaces were constructed by the same multidimensional scaling technique. An important advantage of multidimensional scaling is that it offers the possibility of finding the dimensionality of a color space directly from experimental data, as we demonstrate for the analysis of color discrimination data for equibright stimuli.

An exponential-decay relationship between the probability of generalization and psychological distance has received considerable support from studies of stimulus generalization ( Shepard, 1958 ) and categorization ( Nosofsky, 1984 ). It is shown here how an approximate exponential generalization gradient emerges from stimulus representation assumptions isomorphic to a special case of Shepard's (1987) theory of stimulus generalization in a “configuralcue” network model of human learning that represents stimulus patterns in terms of elementary features and pairwise conjunctions of features ( Gluck & Bower, 1988b ; Gluck, Bower, & Hee, 1989 ). The network model can be viewed as a combination of Shepard's theory and an associative learning rule derived from Rescorla and Wagner's (1972) theory of classical conditioning.

The following two articles offer a glimpse at current experimental psychology in the Soviet Union, normally screened from the English-speaking world by all but impenetrable language barriers. The accompanying Commentary by Tarow Indow helps place these contributions in the framework of contemporary work on the psychophysics of color perception. Fifteen normal trichromatic subjects, two protanopes, and two deuteranopes judged pairs of successively presented foveal color stimuli. Multidimensional scaling of the data yielded estimates of a three-dimensional space with axes interpreted as red–green, blue–yellow, and white–black. For color-deficient subjects, the average radius of the space differed from that of normals, being smaller for the protanopes and larger for the deuteranopes. For both types of color deficiency, the blue–yellow axis was stretched relative to the red–green, more strongly in the protanopes. The findings are taken to support the generality of a “spherical” model.

Changes in technology after the ability of people to express competence, to interact with others, to be active rather than passive, and to exercise influence. For the most part, these changes in psychological processes are accidental by-products of technology's attempts to solve the practical problems of society. Because of the close relation between technology and social behavior, we argue that technology should be included as an explanatory variable in social psychology's construction of behavior. Several benefits should result from developing a social psychology of technology. For one, social psychology will be better able to account for the variance of critical social behaviors such as competence, autonomy, social influence, and social isolation. Second, the study of technology will provide a historical perspective for examining changes in social behavior. Finally, the application of social psychological constructs and methods to the study of technology will provide insights that are not available from studies of this topic by economics, philosophy, and political science.

A formal proof is provided that Anderson's (1990) rational model of categorization generalizes the Medin and Schaffer (1978) context model. According to the context model, people represent categories by storing individual exemplars in memory. According to the rational model, people represent categories in terms of multiple exemplar-clusters or prototypes. In both models, a multiplicative rule is used to compute the similarity of an item to the underlying category representations. In certain special cases, each multiple prototype in the rational model corresponds to an individual exemplar, and in these cases the rational model reduces to the context model. Preliminary quantitative comparisons between the models are illustrated to test whether the multiple-prototype view adds significant explanatory power over the pure exemplar view.

Animal rights activism is increasing rapidly, yet no empirical research has sought to determine who the animal rights activists are, what they believe, and what they hold as their agenda. An attitude survey was therefore conducted of 402 animal rights activists who attended a recent rally in Washington. Results indicated that nearly half of these activists felt that animal research should not be the primary focus of the animal rights movement. There was also considerable disagreement surrounding the issue of laboratory break-ins. These and other findings from the survey suggest that animal rights activists hold diverse objectives and viewpoints.