Beyond Description and Deficits: How Computational Psychiatry Can Enhance an Understanding of Decision-Making in Anorexia Nervosa

Abstract

Despite decades of research, anorexia nervosa (AN) remains poorly understood and clearly effective treatments continue to be elusive. Thus, novel theoretical frameworks are needed to advance mechanistic and treatment research for this disorder. Progress in research on AN may have been slowed by systematic biases historically affecting psychiatric research. In this manuscript, we describe the influence of two such biases: 1) Descriptive bias: the tendency to define mechanisms on the basis of surface or face-valid characteristics; and 2) Deficit bias: the tendency to search for mechanisms associated with under-functioning of decision-making abilities and related circuity, and to neglect problems of over-functioning, in psychiatric disorders. The theories and methods of computational psychiatry are well-suited to overcome these biases by emphasizing the role of computational misalignments (rather than absolute deficits or excesses) between decision-making strategies and environmental demands as the key factors promoting psychiatric illnesses. Informed by this approach, we present an account of AN as a disorder of excess goal pursuit, maintained by over-engagement of executive functioning strategies and circuits conventionally considered to be positive for supporting mental health. We provide evidence that this same computational imbalance may constitute neglected phenotype presenting transdiagnostically across psychiatric disorders. We highlight how traditional psychiatric treatments could be ineffective, or even iatrogenic, for this clinical group and suggest future directions for computational models that may be well suited for identifying more precise mechanistic targets for disorders of excess goal pursuit.

The explore/exploit trade‐off: An ecologically valid and translational framework that can advance mechanistic understanding of eating disorders

“…Similarly, adults with BED and obesity showed greater exploration than adults with obesity only on a clock task, wherein participants selected when to stop the clock to obtain an unknown reward (Morris et al, 2016), and more switching (exploratory) behavior than non‐ED controls on a reward‐based decision‐making task (Reiter et al, 2017). In contrast, preliminary evidence suggested that adults with AN are more exploitative than non‐ED controls in a cross‐species foraging task (Haynos, 2021).…”