The Computations of hostile biases (CHB) model: Grounding hostility biases in a unified cognitive framework

Abstract

Our behavior is partly a product of our perception of the world, and aggressive individuals have been found to have 'hostility biases' in their perception and interpretation of social information. Four types of hostility biases can be distinguished: the hostile attribution, interpretation, expectation, and perception bias. Such low-level biases are believed to have a profound influence on decision-making, and possibly also increase the likelihood of engaging in aggressive acts. The current review systematically examined extant research on the four types of hostility bias, with a particular focus on the associations between each type of hostility bias and aggressive behavior. The results confirmed the robust association between hostility biases and aggressive behavior. However, it is still unknown how exactly hostility biases are acquired. This is also caused by a tendency to study hostility biases separately, as if they are non-interacting phenomena. Another issue is that current approaches cannot directly quantify the latent cognitive processes pertaining to the hostility biases, thus creating an explanatory gap. To fill this gap, we embedded the results of the systematic review in a state-of-the-art computational framework, which provides a novel mechanistic account with testable predictions.

Keywords: Aggressive behavior; Computational modelling; Hostility biases.