Thelen, E., & Smith, L.B. (1993). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT Press.

Shiffrin, R.M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127-190.

Richard Shiffrin’s two-process theory of human attention (with Walter Schneider) has been cited in many thousands of articles and remains a dominant model for our current understanding of the psychology of attention. The authors proposed a theoretical framework for the difference between controlled attention (when you’re trying to focus on a task) and automaticity (when a task is performed without the need for focused attention), and presented a series of experiments in support of this functional dissociation. These experiments have become the basis for most current operationalizations of automaticity: When performing one task fails to interfere with performance on another task, then we’d say the first task is automatic.

Nosofsky, R.M. (1986). Attention, Similarity, and the Identification-Categorization Relationship. Journal of Experimental Psychology: General, 115(1), 39-57.

In this article, Professor Rob Nosofsky first proposed his “generalized context model” (GCM) of categorization, which has since become one of the most influential formal models in all of cognitive psychology. The model formalizes the idea that people represent categories by storing vast collections of individual exemplars of the categories in memory.

Building upon classic theories in the areas of choice and similarity, the model explains relations between categorization and other fundamental cognitive processes, including object identification, old-new recognition memory, and the development of automaticity in tasks of skilled performance.

Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review, 99(1), 22-44.

Imagine being shown apples of various colors and sizes and being told “this one’s a Fuji,” “this one’s a McIntosh,” and so on. You would soon learn that the color of an apple is important for correct categorization, but its size is not as important. People naturally learn to allocate attention to relevant features, even though there is no direct instruction about what features are relevant.

Professor John Kruschke invented a mathematical model of how people learn to allocate attention. The model synthesized a line of neurally-inspired learning models with a line of behaviorally-inspired categorization models (created by another I.U. Professor, Rob Nosofsky; see above). The article has been cited more than a thousand times by researchers in diverse fields from artificial intelligence to neuroscience to social psychology.

Holtzworth-Munroe, A. & Stuart, G.L. (1994). Typologies of male batterers: Three subtypes and the differences among them. Psychological Bulletin, 116(3), 476-497.

Intimate partner violence is a major health problem in the United States. Early studies compared violent to nonviolent men on a variety of variables, (e.g., psychological problems, lack of social skills, attitudes toward violence and women), trying to understand why some men use violence against their partners. But as the field progressed, it became clear that not all violent men are alike.

In theory, considering differences and identifying subtypes of violent men could improve our understanding of violence (e.g., there may be different causes of different types of violence) and our intervention options (e.g., offering different programs targeted to each type of man). Professor Holtzworth-Munroe’s paper (with Gregory Stuart) reviewed the existing batterer typologies, integrating that information to propose a new typology and a model for the development of each subtype of violent man. It changed the research field as it made evident the fact that we cannot consider all violent men to be the same.