Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches.
Neurosci Biobehav Rev
; 147: 105103, 2023 04.
Article
em En
| MEDLINE
| ID: mdl-36804398
ABSTRACT
Making effective decisions during approach-avoidance conflict is critical in daily life. Aberrant decision-making during approach-avoidance conflict is evident in a range of psychological disorders, including anxiety, depression, trauma-related disorders, substance use disorders, and alcohol use disorders. To help clarify etiological pathways and reveal novel intervention targets, clinical research into decision-making is increasingly adopting a computational psychopathology approach. This approach uses mathematical models that can identify specific decision-making related processes that are altered in mental health disorders. In our review, we highlight foundational approach-avoidance conflict research, followed by more in-depth discussion of computational approaches that have been used to model behavior in these tasks. Specifically, we describe the computational models that have been applied to approach-avoidance conflict (e.g., drift-diffusion, active inference, and reinforcement learning models), and provide resources to guide clinical researchers who may be interested in applying computational modeling. Finally, we identify notable gaps in the current literature and potential future directions for computational approaches aimed at identifying mechanisms of approach-avoidance conflict in psychopathology.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Tomada de Decisões
/
Alcoolismo
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article