Aaron Sell: UCSB Department of Psychology

Anger can be understood as a cognitive mechanism designed by natural selection to negotiate conflicts of interest in ways similar to, but distinct from, non-human animal conflict. The Recalibrational Theory of anger uses an evolutionary biological framework to predict the major features of anger and explain their computational structure by reference to this function. Datasets collected from five distinct cultures address the major features of anger including under what conditions anger is evoked, when aggression is used by the anger system, which individuals set lower thresholds for anger and aggression, why and how anger triggers modifications of the face and voice, and how one predicts and explains the computational structure of anger-based arguments. The data demonstrate that anger is a well-designed system for recalibrating targets in ways that minimize immediate and future costs resulting from conflicts of interest.
http://www.bec.ucla.edu/SellTalk.pdf