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Dissociable neural processes during risky decision-making in individuals with Internet-gaming disorder ☆

View Article: PubMed Central - PubMed

ABSTRACT

Risk-taking is purported to be central to addictive behaviors. However, for Internet gaming disorder (IGD), a condition conceptualized as a behavioral addiction, the neural processes underlying impaired decision-making (risk evaluation and outcome processing) related to gains and losses have not been systematically investigated. Forty-one males with IGD and 27 healthy comparison (HC) male participants were recruited, and the cups task was used to identify neural processes associated with gain- and loss-related risk- and outcome-processing in IGD. During risk evaluation, the IGD group, compared to the HC participants, showed weaker modulation for experienced risk within the bilateral dorsolateral prefrontal cortex (DLPFC) (t = − 4.07; t = − 3.94; PFWE < 0.05) and inferior parietal lobule (IPL) (t = − 4.08; t = − 4.08; PFWE < 0.05) for potential losses. The modulation of the left DLPFC and bilateral IPL activation were negatively related to addiction severity within the IGD group (r = − 0.55; r = − 0.61; r = − 0.51; PFWE < 0.05). During outcome processing, the IGD group presented greater responses for the experienced reward within the ventral striatum, ventromedial prefrontal cortex, and orbitofrontal cortex (OFC) (t = 5.04, PFWE < 0.05) for potential gains, as compared to HC participants. Within the IGD group, the increased reward-related activity in the right OFC was positively associated with severity of IGD (r = 0.51, PFWE < 0.05). These results provide a neurobiological foundation for decision-making deficits in individuals with IGD and suggest an imbalance between hypersensitivity for reward and weaker risk experience and self-control for loss. The findings suggest a biological mechanism for why individuals with IGD may persist in game-seeking behavior despite negative consequences, and treatment development strategies may focus on targeting these neural pathways in this population.

No MeSH data available.


Related in: MedlinePlus

The cups task and behavioral performance among IGD and HC participants. The cups includes a gain domain (A) and a loss domain (B). Each trial consists of a safe option with $1 in one cup, and a risky option with a probability of 1/2–1/5 (as determined by the number of cups) of larger gain or loss (±$2 to ±$5). In some trials, the EV of the safe option is equal to that of the risky choice (i.e., EQEV), whereas other combinations could be RA or RD (see Methods section). Mean percentage of risky choices made in the gain domain (C) and loss domain (D), as a function of EV level and group, are displayed. Mean response times (RTs) during decision-making in the gain domain (E) and loss domain (F) are also displayed. IGD = Internet gaming disorder; HC = healthy comparison; EV = expected value; RA = risk advantageous; EQEV = equal expected value; RD = risk disadvantageous.
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f0005: The cups task and behavioral performance among IGD and HC participants. The cups includes a gain domain (A) and a loss domain (B). Each trial consists of a safe option with $1 in one cup, and a risky option with a probability of 1/2–1/5 (as determined by the number of cups) of larger gain or loss (±$2 to ±$5). In some trials, the EV of the safe option is equal to that of the risky choice (i.e., EQEV), whereas other combinations could be RA or RD (see Methods section). Mean percentage of risky choices made in the gain domain (C) and loss domain (D), as a function of EV level and group, are displayed. Mean response times (RTs) during decision-making in the gain domain (E) and loss domain (F) are also displayed. IGD = Internet gaming disorder; HC = healthy comparison; EV = expected value; RA = risk advantageous; EQEV = equal expected value; RD = risk disadvantageous.

Mentions: To assess the neural mechanisms of risky decision-making in gain and loss domains, we used a computerized version of the cups task (Xue et al., 2009). The cups task includes a gain domain and a loss domain. Subjects were instructed to win as much money as possible in the gain domain and to lose as little money as possible in the loss domain. For both gain-domain trials and loss-domain trials, subjects were required to choose between a risky option and a safe option. The safe option is to win or lose $1 for sure, whereas the risky option could lead to a probability (0.20, 0.33, or 0.50) of a larger win ($2, $3, or $5) or winning nothing otherwise in the gain domain, and to a possibility of losing more ($2, $3, or $5) or losing nothing otherwise in the loss domain (Fig. 1). Within each domain, probability and outcome magnitude of the risky option were manipulated such that some combinations of probability and outcome magnitude create equal expected value (EQEV) for the risky and safe options: 0.20 × 5, 0.33 × 3, and 0.50 × 2 on both gain and loss trials. This approach provides a measure of participants' risk preference. Some combinations are slightly risk advantageous (RA), meaning that the expected value (EV) is more favorable for the risky option than for the safe option: 0.33 × 5, 0.50 × 3 in the gain domain; 0.20 × 3, 0.33 × 2 in the loss domain. Some combinations are slightly risk-disadvantageous (RD), meaning that the EV is more favorable for the safe option: 0.20 × 3, 0.33 × 2 in the gain domain; 0.33 × 5, 0.50 × 3 in the loss domain. The 2 combinations with the biggest differences in EV between risk and safe options (i.e., 0.20 × 2 and 0.50 × 5) were excluded in the current study because of their insensitivity to individuals' attitude toward risk, evident from healthy young adults (Xue et al., 2009) (see the Methods section of Supplementary Materials for further details on task and experimental methods).


Dissociable neural processes during risky decision-making in individuals with Internet-gaming disorder ☆
The cups task and behavioral performance among IGD and HC participants. The cups includes a gain domain (A) and a loss domain (B). Each trial consists of a safe option with $1 in one cup, and a risky option with a probability of 1/2–1/5 (as determined by the number of cups) of larger gain or loss (±$2 to ±$5). In some trials, the EV of the safe option is equal to that of the risky choice (i.e., EQEV), whereas other combinations could be RA or RD (see Methods section). Mean percentage of risky choices made in the gain domain (C) and loss domain (D), as a function of EV level and group, are displayed. Mean response times (RTs) during decision-making in the gain domain (E) and loss domain (F) are also displayed. IGD = Internet gaming disorder; HC = healthy comparison; EV = expected value; RA = risk advantageous; EQEV = equal expected value; RD = risk disadvantageous.
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f0005: The cups task and behavioral performance among IGD and HC participants. The cups includes a gain domain (A) and a loss domain (B). Each trial consists of a safe option with $1 in one cup, and a risky option with a probability of 1/2–1/5 (as determined by the number of cups) of larger gain or loss (±$2 to ±$5). In some trials, the EV of the safe option is equal to that of the risky choice (i.e., EQEV), whereas other combinations could be RA or RD (see Methods section). Mean percentage of risky choices made in the gain domain (C) and loss domain (D), as a function of EV level and group, are displayed. Mean response times (RTs) during decision-making in the gain domain (E) and loss domain (F) are also displayed. IGD = Internet gaming disorder; HC = healthy comparison; EV = expected value; RA = risk advantageous; EQEV = equal expected value; RD = risk disadvantageous.
Mentions: To assess the neural mechanisms of risky decision-making in gain and loss domains, we used a computerized version of the cups task (Xue et al., 2009). The cups task includes a gain domain and a loss domain. Subjects were instructed to win as much money as possible in the gain domain and to lose as little money as possible in the loss domain. For both gain-domain trials and loss-domain trials, subjects were required to choose between a risky option and a safe option. The safe option is to win or lose $1 for sure, whereas the risky option could lead to a probability (0.20, 0.33, or 0.50) of a larger win ($2, $3, or $5) or winning nothing otherwise in the gain domain, and to a possibility of losing more ($2, $3, or $5) or losing nothing otherwise in the loss domain (Fig. 1). Within each domain, probability and outcome magnitude of the risky option were manipulated such that some combinations of probability and outcome magnitude create equal expected value (EQEV) for the risky and safe options: 0.20 × 5, 0.33 × 3, and 0.50 × 2 on both gain and loss trials. This approach provides a measure of participants' risk preference. Some combinations are slightly risk advantageous (RA), meaning that the expected value (EV) is more favorable for the risky option than for the safe option: 0.33 × 5, 0.50 × 3 in the gain domain; 0.20 × 3, 0.33 × 2 in the loss domain. Some combinations are slightly risk-disadvantageous (RD), meaning that the EV is more favorable for the safe option: 0.20 × 3, 0.33 × 2 in the gain domain; 0.33 × 5, 0.50 × 3 in the loss domain. The 2 combinations with the biggest differences in EV between risk and safe options (i.e., 0.20 × 2 and 0.50 × 5) were excluded in the current study because of their insensitivity to individuals' attitude toward risk, evident from healthy young adults (Xue et al., 2009) (see the Methods section of Supplementary Materials for further details on task and experimental methods).

View Article: PubMed Central - PubMed

ABSTRACT

Risk-taking is purported to be central to addictive behaviors. However, for Internet gaming disorder (IGD), a condition conceptualized as a behavioral addiction, the neural processes underlying impaired decision-making (risk evaluation and outcome processing) related to gains and losses have not been systematically investigated. Forty-one males with IGD and 27 healthy comparison (HC) male participants were recruited, and the cups task was used to identify neural processes associated with gain- and loss-related risk- and outcome-processing in IGD. During risk evaluation, the IGD group, compared to the HC participants, showed weaker modulation for experienced risk within the bilateral dorsolateral prefrontal cortex (DLPFC) (t = − 4.07; t = − 3.94; PFWE < 0.05) and inferior parietal lobule (IPL) (t = − 4.08; t = − 4.08; PFWE < 0.05) for potential losses. The modulation of the left DLPFC and bilateral IPL activation were negatively related to addiction severity within the IGD group (r = − 0.55; r = − 0.61; r = − 0.51; PFWE < 0.05). During outcome processing, the IGD group presented greater responses for the experienced reward within the ventral striatum, ventromedial prefrontal cortex, and orbitofrontal cortex (OFC) (t = 5.04, PFWE < 0.05) for potential gains, as compared to HC participants. Within the IGD group, the increased reward-related activity in the right OFC was positively associated with severity of IGD (r = 0.51, PFWE < 0.05). These results provide a neurobiological foundation for decision-making deficits in individuals with IGD and suggest an imbalance between hypersensitivity for reward and weaker risk experience and self-control for loss. The findings suggest a biological mechanism for why individuals with IGD may persist in game-seeking behavior despite negative consequences, and treatment development strategies may focus on targeting these neural pathways in this population.

No MeSH data available.


Related in: MedlinePlus