Resting-state functional connectivity within orbitofrontal cortex and inferior frontal gyrus modulates the relationship between reflection level and risk-taking behavior in internet gaming disorder

Liu, Sijia; Lu, Yang; Li, Shuang; Huang, Pujiang; Li, Lin; Liu, Siyi; Zhang, Wensheng; Liu, Zhiyuan; Guo, Xin-Heng

doi:10.1016/j.brainresbull.2021.10.019

Cited by 7 publications

(2 citation statements)

References 67 publications

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“…Previous studies have shown that resting state functional connectivity between OFC and inferior frontal gyrus is associated with risk-taking, and that individuals with internet gaming disorder have increased functional connectivity between these regions. 73 Another fMRI study found that OFC activity and functional connectivity to ACC and ventromedial prefrontal cortices were associated with greater overall risk-taking tendency. 30 Animal studies have suggested an important role for dopaminergic signalling in OFC in risk taking, with blockade of D1 OFC dopamine receptors decreasing risky decisions while blockade of D2 OFC dopamine receptors increases subsequent risky decisions.…”

Section: Discussionmentioning

confidence: 99%

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Hughes,

Qian,

Zargari

et al. 2024

Preprint

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Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking.Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient.Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex (p=0.0022), high-gamma in the anterior cingulate (p=0.0004), and high-gamma in the insula (p=0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power (p=2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex (p=2.0E-4), broad frequencies in amygdala (p=2.0E-4), and theta to low-gamma in insula (p=4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal (p=0.0048) and with patient impulsivity (p=0.00478).Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.

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Section: Discussionmentioning

confidence: 99%

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Hughes,

Qian,

Zargari

et al. 2024

Preprint

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“…Buckert [23] and Kirchler et al [19] analyzed the relationship between subjects' risk preferences and risk decision-making with lottery tasks. Some scholars also studied the impact of time pressure on risk preference using the unpacking task of risk decision-making [28][29][30]. At present, there have been many studies about the impact of time pressure on decision-making, and most of them verified that time pressure reduced the quality of decision-making.…”

Section: Hypothesis 2 (H2) (1)mentioning

confidence: 99%

Experimental Study on the Risk Preference Characteristics of Members in Supply Chain Emergencies

Chen

Liu

2023

Applied Sciences

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Since risk preference affects the behavior of decision makers, the study of its characteristics and impact on decision-making contributes to good planning for emergency coordination. The consistency of a member’s risk preferences in the conventional risk field and emergencies of a supply chain was analyzed by applying the prospect theory and adapting the domain-specific risk-taking (DOSPERT) scale. The influence of time pressure on the risk preferences and decision-making behaviors of members was studied in the emergency field and its sub-emergencies of a supply chain. The conclusions were drawn based on the empirical study. First, the risk preference could be measured in terms of conventional risk and emergencies. Second, the members tended to be risk averse with no time pressure, and the degree of risk aversion was weakened with time pressure, which had the greatest effect in the natural disaster event. Third, even though the change in risk preference had a consistency regarding the four types of sub-events of supply chain emergencies, it was inconsistent regarding the conventional risks and emergencies. With the evolution trend of risk preference demonstrated and the relationship between preference and time pressure revealed, this study may provide a decision-making reference for the formulation of a supply chain emergency coordination scheme.

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The neural mechanisms underlying the modulation of attentional deployment on emotional stability

Liu

Che

et al. 2022

Exp Brain Res

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Resting-state functional connectivity within orbitofrontal cortex and inferior frontal gyrus modulates the relationship between reflection level and risk-taking behavior in internet gaming disorder

Cited by 7 publications

References 67 publications

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Experimental Study on the Risk Preference Characteristics of Members in Supply Chain Emergencies

The neural mechanisms underlying the modulation of attentional deployment on emotional stability

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