scholarly journals Reliability of the fMRI-based assessment of self-evaluation in individuals with internet gaming disorder

2021 ◽  
Author(s):  
Patrick Bach ◽  
Holger Hill ◽  
Iris Reinhard ◽  
Theresa Gädeke ◽  
Falk Kiefer ◽  
...  
Keyword(s):  
Internet Gaming Disorder ◽  
Brain Activation ◽  
Brain Regions ◽  
The Self ◽  
Self Concept ◽  
Gaming Disorder ◽  
Retest Reliability ◽  
Self Evaluation ◽  
Internet Gaming ◽  
Test Retest Reliability

AbstractThe self-concept—defined as the cognitive representation of beliefs about oneself—determines how individuals view themselves, others, and their actions. A negative self-concept can drive gaming use and internet gaming disorder (IGD). The assessment of the neural correlates of self-evaluation gained popularity to assess the self-concept in individuals with IGD. This attempt, however, seems to critically depend on the reliability of the investigated task-fMRI brain activation. As first study to date, we assessed test–retest reliability of an fMRI self-evaluation task. Test–retest reliability of neural brain activation between two separate fMRI sessions (approximately 12 months apart) was investigated in N = 29 healthy participants and N = 11 individuals with pathological internet gaming. We computed reliability estimates for the different task contrasts (self, a familiar, and an unknown person) and the contrast (self > familiar and unknown person). Data indicated good test–retest reliability of brain activation, captured by the “self”, “familiar person”, and “unknown person” contrasts, in a large network of brain regions in the whole sample (N = 40) and when considering both experimental groups separately. In contrast to that, only a small set of brain regions showed moderate to good reliability, when investigating the contrasts (“self > familiar and unknown person”). The lower reliability of the contrast can be attributed to the fact that the constituting contrast conditions were highly correlated. Future research on self-evaluation should be cautioned by the findings of substantial local reliability differences across the brain and employ methods to overcome these limitations.

Disrupted prefrontal regulation of striatum-related craving in Internet gaming disorder revealed by dynamic causal modeling: results from a cue-reactivity task

2020 ◽  
pp. 1-13 ◽  
Author(s):  
Guang-Heng Dong ◽  
Min Wang ◽  
Hui Zheng ◽  
Ziliang Wang ◽  
Xiaoxia Du ◽  
...  
Keyword(s):  
Internet Gaming Disorder ◽  
Cingulate Cortex ◽  
Brain Regions ◽  
Reward Processing ◽  
Causal Modeling ◽  
Anterior Cingulate ◽  
Separate Analysis ◽  
Gaming Disorder ◽  
Lentiform Nucleus ◽  
Internet Gaming

Abstract Background Studies of Internet gaming disorder (IGD) suggest an imbalanced relationship between cognitive control and reward processing in people with IGD. However, it remains unclear how these two systems interact with each other, and whether they could serve as neurobiological markers for IGD. Methods Fifty IGD subjects and matched individuals with recreational game use (RGU) were selected and compared when they were performing a cue-craving task. Regions of interests [anterior cingulate cortex (ACC), lentiform nucleus] were selected based on the comparison between brain responses to gaming-related cues and neutral cues. Directional connectivities among these brain regions were determined using Bayesian estimation. We additionally examined the posterior cingulate cortex (PCC) in a separate analysis based on data implicating the PCC in craving in addiction. Results During fixed-connectivity analyses, IGD subjects showed blunted ACC-to-lentiform and lentiform-to-ACC connectivity relative to RGU subjects, especially in the left hemisphere. When facing gaming cues, IGD subjects trended toward lower left-hemispheric modulatory effects in ACC-to-lentiform connectivity than RGU subjects. Self-reported cue-related craving prior to scanning correlated inversely with left-hemispheric modulatory effects in ACC-to-lentiform connectivity. Conclusions The results suggesting that prefrontal-to-lentiform connectivity is impaired in IGD provides a possible neurobiological mechanism for difficulties in controlling gaming-cue-elicited cravings. Reduced connectivity ACC-lentiform connectivity may be a useful neurobiological marker for IGD.

scholarly journals Neurobiological mechanisms underlying internet and gaming disorder (IGD)

2020 ◽  
Vol 22 (2) ◽  
pp. 113-126
Keyword(s):  
Computer Games ◽  
Structural Changes ◽  
Gray Matter Volume ◽  
Internet Gaming Disorder ◽  
Brain Regions ◽  
Sensory Function ◽  
Gaming Disorder ◽  
Control Networks ◽  
Internet Gaming ◽  
The Impact

This review summarizes studies on the neurobiological correlates of internet gaming disorder (IGD), presently the most direct approach to analyzing the impact of digital technology and the internet on brain mechanisms. Brain imaging studies have shown that IGD shares, to a large extent, neurobiological alterations that are typical for other addictions, such as: (i) activation in brain regions associated with reward, as evident from cue exposure and craving studies and neurotransmitter systems studies that indicate an involvement of dopamine-mediated reward mechanisms; (ii) reduced activity in impulse control areas and impaired decision making; and (iii) reduced functional connectivity in brain networks that are involved in cognitive control, executive function, motivation, and reward. Moreover, there are structural changes, mainly reduction in gray-matter volume and white-matter density. Comorbidity studies indicate that executive control networks in attention deficit-hyperactivity disorder (ADHD) may increase the susceptibility to develop IGD. Most importantly, this review also outlines findings that show the effects of excessive use of screens, here referring to the playing of computer games, which activate many brain regions associated with cognitive, motor, and sensory function and not directly involved in other forms of addiction. This review describes and summarizes comprehensively the neurobiological correlates of addictive internet use in adolescents and young adults.

scholarly journals Enhanced neural responses in specific phases of reward processing in individuals with Internet gaming disorder

2021 ◽  
Vol 10 (1) ◽  
pp. 99-111
Author(s):  
Lingxiao Wang ◽  
Guochun Yang ◽  
Ya Zheng ◽  
Zhenghan Li ◽  
Yue Qi ◽  
...  
Keyword(s):  
Self Regulation ◽  
Internet Gaming Disorder ◽  
Reward System ◽  
Reward Processing ◽  
The Self ◽  
Gaming Disorder ◽  
Internet Gaming ◽  
Reward Anticipation ◽  
Outcome Monitoring ◽  
Regulation Model

AbstractBackground and aimsInternet gaming disorder (IGD) has become a global health problem. The self-regulation model noted that a shift to reward system, whether due to overwhelming reward-seeking or impaired control, can lead to self-regulation failures, e.g., addiction. The present study focused on the reward processing of IGD, aiming to provide insights into the etiology of IGD. Reward processing includes three phases: reward anticipation, outcome monitoring and choice evaluation. However, it is not clear which phases of reward processing are different between individuals with IGD and healthy controls (HC).MethodsTo address this issue, the present study asked 27 individuals with IGD and 26 HC to complete a roulette task during a functional MRI scan.ResultsCompared with HC, individuals with IGD preferred to take risks in pursuit of high rewards behaviorally and showed exaggerated brain activity in the striatum (nucleus accumbens and caudate) during the reward anticipation and outcome monitoring but not during the choice evaluation.DiscussionThese results reveal that the oversensitivity of the reward system to potential and positive rewards in college students with IGD drives them to approach risky options more frequently although they are able to assess the risk values of options and the correctness of decisions properly as HC do.ConclusionsThese findings provide partial support for the application of the self-regulation model to the IGD population. Moreover, this study enriches this model from the perspective of three phases of reward processing and provides specific targets for future research regarding effective treatment of IGD.

scholarly journals Neural Correlates of Distorted Self-concept in Individuals With Internet Gaming Disorder: A Functional MRI Study

2018 ◽  
Vol 9 ◽  
Author(s):  
Min-Kyeong Kim ◽  
Young Hoon Jung ◽  
Sunghyon Kyeong ◽  
Yu-Bin Shin ◽  
Eunjoo Kim ◽  
...  
Keyword(s):  
Functional Mri ◽  
Internet Gaming Disorder ◽  
Neural Correlates ◽  
Self Concept ◽  
Gaming Disorder ◽  
Internet Gaming ◽  
Mri Study

scholarly journals Brain activation for response inhibition under gaming cue distraction in internet gaming disorder

2014 ◽  
Vol 30 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Gin-Chung Liu ◽  
Ju-Yu Yen ◽  
Chiao-Yun Chen ◽  
Cheng-Fang Yen ◽  
Cheng-Sheng Chen ◽  
...  
Keyword(s):  
Response Inhibition ◽  
Internet Gaming Disorder ◽  
Brain Activation ◽  
Gaming Disorder ◽  
Internet Gaming

scholarly journals The neural features in the precentral gyrus predict the severity of internet game disorder: results from the multi-voxel pattern analyses

2020 ◽  
Author(s):  
Shuer Ye ◽  
Min Wang ◽  
Qun Yang ◽  
Haohao Dong ◽  
Guang-Heng Dong
Keyword(s):  
Machine Learning ◽  
Predictive Models ◽  
Resting State ◽  
Internet Gaming Disorder ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Diagnostic Study ◽  
Precentral Gyrus ◽  
Gaming Disorder ◽  
Internet Gaming

AbstractImportanceFinding the neural features that could predict internet gaming disorder severity is important in finding the targets for potential interventions using brain modulation methods.ObjectiveTo determine whether resting-state neural patterns can predict individual variations of internet gaming disorder by applying machine learning method and further investigate brain regions strongly related to IGD severity.DesignThe diagnostic study lasted from December 1, 2013, to November 20, 2019. The data were analyzed from December 31, 2019, to July 10, 2020.SettingThe resting-state fMRI data were collected at East China Normal University, Shanghai.ParticipantsA convenience sample consisting of 402 college students with diverse IGD severityMain Outcomes and MeasuresThe neural patterns were represented by regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF). Predictive model performance was assessed by Pearson correlation coefficient and standard mean squared error between the predicted and true IGD severity. The correlations between IGD severity and topological features (i.e., degree centrality (DC), betweenness centrality (BC), and nodal efficiency (NE)) of consensus highly weighted regions in predictive models were examined.ResultsThe final dataset consists of 402 college students (mean [SD] age, 21.43 [2.44] years; 239 [59.5%] male). The predictive models could significantly predict IGD severity (model based on ReHo: r = 0.11, p(r) = 0.030, SMSE = 3.73, p(SMSE) = 0.033; model based on ALFF: r=0.19, p(r) = 0.002, SMSE = 3.58, p(SMSE) = 0.002). The highly weighted brain regions that contributed to both predictive models were the right precentral gyrus and the left postcentral gyrus. Moreover, the topological properties of the right precentral gyrus were significantly correlated with IGD severity (DC: r = 0.16, p = 0.001; BC: r = 0.14, p = 0.005; NE: r = 0.15, p = 0.003) whereas no significant result was found for the left postcentral gyrus (DC: r = 0.02, p = 0.673; BC: r = 0.04, p = 0.432; NE: r = 0.02, p = 0.664).Conclusions and RelevanceThe machine learning models could significantly predict IGD severity from resting-state neural patterns at the individual level. The predictions of IGD severity deepen our understanding of the neural mechanism of IGD and have implications for clinical diagnosis of IGD. In addition, we propose precentral gyrus as a potential target for physiological treatment interventions for IGD.Key PointsQuestionCan machine learning algorithms predict internet gaming disorder (IGD) from resting-state neural patterns?FindingsThis diagnostic study collected resting-state fMRI data from 402 subjects with diverse IGD severity. We found that machine learning models based on resting-state neural patterns yielded significant predictions of IGD severity. In addition, the topological neural features of precentral gyrus, which is a consensus highly weighted region, is significantly correlated with IGD severity.MeaningThe study found that IGD is a distinctive disorder and its dependence severity could be predicted by brain features. The precentral gyrus and its connection with other brain regions could be view as targets for potential IGD intervention, especially using brain modulation methods.

scholarly journals RISK FACTORS OF INTERNET GAMING AMONG FILIPINO STUDENTS

2020 ◽  
Vol 8 (4) ◽  
pp. 230-237
Author(s):  
Marris R. Reyes
Keyword(s):  
Risk Factors ◽  
Internet Gaming Disorder ◽  
Significant Risk ◽  
The Self ◽  
Self Control ◽  
Personality Factors ◽  
The Internet ◽  
Gaming Disorder ◽  
Internet Gaming ◽  
Filipino Students

Purpose of the study: The main objective of this study is to examine the risk factors for internet gaming disorder (IGD). Specifically, it aims to: measure the severity of internet gaming among Filipino students; describe their internet gaming characteristic; and, identify which among the risk factors predict IGD. Methodology: Students who displayed five or more symptoms in the Internet Gaming Disorder Scale – Short Form (IGD9-SF) were identified. The internet gaming characteristics, Brief Self Control Scale (BSCS) to identify self-control levels, and Mini-IPIP for the personality of the participants were also collected. Data were analyzed using descriptive statistics and linear regression analysis to identify the significant risk factors for IGD using SPSS 17.0. Main Findings: Internet gaming characteristics such as time spent, money spent, and devices used were significant risk factors to IGD. Psychological factors such as self-control and personality traits (agreeableness and openness) were established and were also significant risk factors. The lower the self-control the higher the risk of developing IGD, as well as the more agreeable and open the gamers are the higher the risk to IGD. Applications of this study: Researchers and therapists should focus on developing intervention methods focusing on minimizing the device's exposure to lessen time and money spent in gaming as well as strengthening the self-control of the gamers.  Novelty/Originality of this study: This psychological inquiry contributed to the emerging psychological disorder IGD shedding light on its current debates and controversies. This established risk factors to IGD among Filipino students who are time spent, money spent, devices used, self-control, and personality factors such as agreeableness and openness.

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