Modeling Avoidance in Mood and Anxiety Disorders Using Reinforcement Learning

Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior—avoiding social situations for fear of embarrassment, for instance—is a core feature of such...

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Podrobná bibliografia
Vydané v:	Biological psychiatry (1969) Ročník 82; číslo 7; s. 532 - 539
Hlavní autori:	Mkrtchian, Anahit, Aylward, Jessica, Dayan, Peter, Roiser, Jonathan P., Robinson, Oliver J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 01.10.2017 Elsevier
Predmet:	Adolescent Adult Anxiety Anxiety - psychology Archival Report Avoidance Avoidance Learning - physiology Bayes Theorem Decision Making - physiology Diathesis–stress Female Humans Male Middle Aged Models, Psychological Mood Disorders - psychology Mood Disorders - rehabilitation Pavlovian bias Psychiatric Status Rating Scales Psychiatric/Mental Health Reinforcement learning Reinforcement, Psychology Threat of shock Young Adult Pavlovian bias Anxiety Diathesis–stress Threat of shock Avoidance Reinforcement learning
ISSN:	0006-3223, 1873-2402, 1873-2402
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Popis
Shrnutí:	Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior—avoiding social situations for fear of embarrassment, for instance—is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear. Reinforcement learning models provide formal and testable characterizations of the mechanisms of decision making; here, we examine avoidance in these terms. A total of 101 healthy participants and individuals with mood and anxiety disorders completed an approach-avoidance go/no-go task under stress induced by threat of unpredictable shock. We show an increased reliance in the mood and anxiety group on a parameter of our reinforcement learning model that characterizes a prepotent (pavlovian) bias to withhold responding in the face of negative outcomes. This was particularly the case when the mood and anxiety group was under stress. This formal description of avoidance within the reinforcement learning framework provides a new means of linking clinical symptoms with biophysically plausible models of neural circuitry and, as such, takes us closer to a mechanistic understanding of mood and anxiety disorders.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0006-3223 1873-2402 1873-2402
DOI:	10.1016/j.biopsych.2017.01.017