Computational Perspectives on Behaviour in Anorexia Nervosa: A Systematic Review

Anorexia Nervosa (AN) is a severe eating disorder, marked by persistent changes in behaviour, cognition and neural activity that result in insufficient body weight. Recently, there has been a growing interest in applying computational methods, grounded in formal mathematical models, to understand cognitive mechanisms that underlie AN symptoms. Our aim was to systematically review progress in this new and emerging field. Based on articles selected using systematic and reproducible criteria, we identified four current themes in the computational study of AN: 1) learning from feedback; 2) decision-making; 3) goal-directed and habitual control over behaviour; and 4) cognitive flexibility. In addition to detailing and appraising the insights from each of these areas, we highlight methodological considerations for the field and outline promising future directions to establish the clinical relevance of (neuro)computational changes in AN.