Development of a classifier for gambling disorder based on functional connections between brain regions.

Aim: Recently, a machine-learning (ML) technique has been used to create generalizable classifiers for psychiatric disorders based on information of functional connections (FCs) between brain regions at resting state. These classifiers predict diagnostic labels by a weighted linear sum (WLS) of the correlation values of a small number of selected FCs. We aimed to develop a generalizable classifier for gambling disorder (GD) from the information of FCs using the ML technique and examine relationships between WLS and clinical data.

Framing effects on financial and health problems in gambling disorder.

Gambling disorder (GD) patients show excessively risky decision-making in the financial domain. We aimed to clarify whether GD patients show risky decision-making in domain-general or in domain-specific. Furthermore, we also investigated the effect of the well-known cognitive bias, the framing effect on GD's decision-making under risk.

An fMRI study of decision-making under sunk costs in gambling disorder.

The sunk cost effect is the tendency to continue an investment, or take an action, even though it has higher future costs than benefits, if costs of time, money, or effort were previously incurred. This type of decision bias is pervasive in real life and has been studied in various disciplines. Previous studies and clinical observations suggest that decision-making under sunk costs is altered in gambling disorder (GD).

Amygdala volume is associated with risky probability cognition in gambling disorder.

Gambling disorder (GD) is characterized by continual gambling despite negative consequences. Risky decision-making is a hallmark of the disorder. We applied a tool from behavioral economics for assessing probability cognition in both gain and loss domains to GD.

Heterogeneity of Loss Aversion in Pathological Gambling.

Pathological gambling (PG) is characterized by continual repeated gambling behavior despite negative consequences. PG is considered to be a disorder of altered decision-making under risk, and behavioral economics tools were utilized by studies on decision-making under risk. At the same time, PG was suggested to be a heterogeneous disorder in terms of personality traits as well as risk attitude.