Emotions are viewed as having evolved through their adaptive value in dealing with fundamental life-tasks. Each emotion has unique features: signal, physiology, and antecedent events. Each emotion also has characteristics in common with other emotions: rapid onset, short duration, unbidden occurrence, automatic appraisal, and coherence among responses. These shared and unique characteristics are the product of our evolution, and distinguish emotions from other affective phenomena.

Proper linear models are those in which predictor variables are given weights such that the resulting linear composite optimally predicts some criterion of interest; examples of proper linear models are standard regression analysis, discriminant function analysis, and ridge regression analysis. Research summarized in P. Meehl's book on clinical vs statistical prediction and research stimulated in part by that book indicate that when a numerical criterion variable is to be predicted from numerical predictor variables, proper linear models outperform clinical intuition. Improper (...) linear models are those in which the weights of the predictor variables are obtained by some nonoptimal method. The present article presents evidence that even such improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors. In fact, unit weighting is quite robust for making such predictions. The application of unit weights to decide what bullet the Denver Police Department should use is described; some technical, psychological, and ethical resistances to using linear models in making social decisions are considered; and arguments that could weaken these resistances are presented. (shrink)

This article presents a model of the structure of emotion developed primarily from a consideration of neuropsychological evidence and behavioural data which have bearing on neuropsychological theories. Valence is first considered and highlighted as a defining characteristic of emotion. Next, the use of facial behaviour and autonomic nervous system patterns as defining characteristics of discrete emotions is questioned on empirical and conceptual grounds. The regulation of emotion is considered and proposed to affect the very structure of emotion itself. If there (...) is an invariant pattern of biological activity across different instantiations of the same emotion, it is likely to be found in higher-order associative networks of central nervous system activity, the very same networks that subserve goal-directed behaviour and other cognitive functions. Drawing upon evolutionary considerations, it is argued that what is basic about emotion are the dimensions of approach and withdrawal. The nature of the linkage between such action tendencies and emotion is discussed. (shrink)