Past Research #1

Investigating the effect of actual real-time internet gaming in internet gaming disorder scale
high scorers using functional near-infrared spectroscopy (fNIRS)

    ▶Please click here for the full manuscript on the study, including detailed information on methods and thorough discussions.

   Millions of people play internet games around the world, and playing internet games is gradually becoming a part of people’s everyday lives. Such a phenomenon can be noticed first-hand when one sees people playing games on their smartphones commuting to work or going to school. While enjoying these games may provide players with excitement or pleasure, previous studies suggest that they may also impair mental health and everyday functioning when it becomes an addiction (Ko, 2014; Kuss, 2013; van den Eijnden, Koning, Doornwaard, van Gurp, & ter Bogt, 2018). Recognizing such negative impacts, the Diagnostic and Statistical Manual of Mental Disorders fifth Edition (DSM-5) included Internet Gaming Disorder (IGD) in section three as a condition for further study with suggested diagnostic criteria. However, debate is yet ongoing on whether IGD should become an official diagnosis.

   Keeping in mind such controversies, our team aimed to observe whether there existed neural activation differences between individuals who scored high on the Korean version of the Internet Gaming Disorder Scale (K-IGDS; Cho & Kwon, 2017; Lemmens, Valkenburg, & Gentile, 2015) and a control group (IGD group vs CTRL group) when they were actually playing internet games. In order to capture neuroimages while actively playing the game, we could not rely on the fMRI due to its inherent restrictions. Thus, we used the functional near-infrared spectroscopy (fNIRS) which fit our purpose well.

   Similar to the fMRI, the fNIRS measures blood oxygenated level dependent signals and holds advantages including superior temporal resolution, tolerance to motion artifacts, unnecessariness of constraint, low cost, and portability (Pinti et al., 2020).

   A total of 30 males participated in the study, including 15 in the IGD group and 15 in the CTRL group. Individuals who scored higher than 48 (which is suggested to be the ideal cutoff score for the diagnosis of IGD) or more were assigned to the IGD group, and those who scored 25 or less were assigned to the CTRL group. The final mean K-IGDS score was 67.93 (SD = 21.17) in the IGD group and 12.20 (SD = 6.64) in the CTRL group.

   The game used in the research was League of Legends, one of the most popular internet games played around the world with approximately 27 million players (Gray, 2021; Mishra, 2021). Through a frame-by-frame review of the gameplay videos of participants, we marked the time points of positive and negative events that took place inside the game and clipped the fNIRS data recorded 5 seconds before and 15 seconds after the marked time points. Each participant’s event-related time series were averaged to a group level, composing a representative time-locked oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) response for the CTRL group and IGD group. The group level differences of HbO and HbR response accompanying events were compared between the IGD group and CTRL group through two sample t-tests.

   Our observations were focused on the prefrontal cortical area, especially the medial and lateral orbitofrontal cortex (OFC), and the dorsolateral prefrontal cortex (DLPFC), which have been suggested to be associated with substance use, IGD, and addiction (Crockford, Goodyear, Edwards, Quickfall, & el-Guebaly, 2005; Feil et al., 2010; Kober et al., 2010; London, Ernst, Grant, Bonson, & Weinstein, 2000; Schoenbaum, Roesch, & Stalnaker, 2006; Tanabe et al., 2007; Tanabe et al., 2009; Volkow, Wang, Tomasi, & Baler, 2013). Previous research emphasizing the functional distinction between the medial and lateral OFC suggests the medial OFC to be related to pleasant stimuli and rewards, and the lateral OFC to be related to unpleasant stimuli, not receiving rewards and punishment (Kringelbach, 2005; Kringelbach & Rolls, 2004; O’Doherty, Kringelbach, Rolls, Hornak, & Andrews, 2001; Rolls, Cheng, & Feng, 2020). As research indicates that preference to win (high reward sensitivity) and insensitivity to loss (low punishment sensitivity) are characteristics defining substance use and internet addiction (Dong, Huang, & Du, 2011; Dong, Hu, & Lin, 2013; He et al., 2017; Jonker, Ostafin, Glashouwer, van Hemel-Ruiter, & de Jong, 2014; Potts, Bloom, Evans, & Drobes, 2014), we hypothesized that individuals who score high on the IGD scale would show stronger medial OFC activation in response to positive game events, and weaker lateral OFC activation in response to negative game events, meaning that they would be sensitive to rewards but less responsive to punishment.

   Research on the function of the DLPFC in substance use disorder and gambling disorder have focused on its association with craving. For example, Grant et al. (1996) hypothesized that activation in the DLPFC reflects triggering of memories, which in turn leads to craving. The hypothesis was based on his observation on the correlations between metabolic increases in the DLPFC and other regions related to memory, including the amygdala and cerebellum when individuals who abused cocaine were exposed to drug-related stimuli. More recently, George and Koob (2013) suggested that DLPFC activation increases craving by potentiating the response to drug-related stimuli. To test such hypotheses and draw causal relations between the DLPFC and craving, Hayashi, Ko, Strafella, and Dagher (2013) inactivated the DLPFC using transcranial magnetic stimulation while exposing smokers to smoking cues and discovered that it prevented increase in craving. Based on such studies, we hypothesized that individuals who score high on the IGD scale would demonstrate higher craving for gaming and that such high craving would be reflected in the DLPFC following positive events in the game.

   Considering all regions measured, the IGD group generally showed stronger HbO responses than the CTRL group following positive events. Particularly, such difference was statistically significant in channel 3, located on the right DLPFC (t = 2.07, p = .048). The t-values were 0.94 (p = .35) and 1.09 (p = .29) in channels 7 and 10, respectively, which measured activations in the hypothesized medial OFC. Differences in HbR responses were statistically nonsignificant in all channels. Symmetrically reflecting the results in HbO responses, the lowest t-value was -1.58 (p = .13) in channel 3.

   Following negative events, the HbO responses differed significantly between the two groups in that the IGD group showed weaker activation than the CTRL group in channel 1, which is sited on the right lateral OFC (t = −2.06, p = .049). Difference in HbR response was significant in channel 7, located on the medial OFC. The IGD group’s HbR concentration was stronger than that of the CTRL group’s (t = 2.37, p = .03). However, the HbO response in channel 7 was statistically nonsignificant (t = 0.22, p = .82). Though horizontally symmetrical to the HbO response, the HbR concentration difference in channel 1 was not significant statistically (t = 1.74, p = .09). The t-maps of HbO and HbR responses to positive and negative events are shown in Fig. 5, and visuals on significant regions are shown in Fig. 6.

   As hypothesized, significantly weaker activation following negative events in the IGD group’s lateral OFC was observed through the HbO response. In the corresponding HbR results, the horizontally symmetrical concentration pattern showing an increase in the IGD group and decrease in the CTRL group supports the results in the HbO response, indicating evidently weaker activation in the region. Based on previous research, we suggest that activation differences in the lateral OFC may reflect the low punishment sensitivity characteristic to individuals with addictive disorders including substance use disorder, pathological gambling, and IGD (Fauth-Bühler & Mann, 2017; Jonker et al., 2014; Yao et al., 2020).

    The significant DLPFC activation in the IGD group may be related to the anticipation or craving for more positive events after such has been experienced. The high craving score, measured through the Korean Gaming Craving Scale for youths (KGCS; Im, Kwon, Heo, & Lee, 2014), in the IGD group supports such a possibility. However, it must be acknowledged that the craving measurement was not collected immediately following positive events. Thus, whether the stronger activation in the DLPFC reflects the acquired craving data remains speculative. Such a limitation was due to the structure of the game and ethical issues in constantly interrupting participants while playing a ranked game. To mitigate the limitation, we performed linear regression to test if the HbO activation of channel 3 predicted the KGCS score. The results indicated that the HbO activation of channel 3 explains a significant amount of the variance in the KGCS score, F(1, 26) = 6.38, P = 0.02, R 2 = 0.20, R 2 adjusted = 0.17. The regression coefficient was B = 3325.17 (Fig. 7).

   Although the present study is not without limitations, it holds important implications for IGD and research methodology on behavioral addictions. To our knowledge, this is the first neuroimaging study to examine the neural characteristics of IGD during actual gameplay. Taking advantage of the merits of the fNIRS, we observed distinguishing activation patterns in the lateral OFC and DLPFC following specific events in the game. The results of the study provide preliminary evidence that IGD is similar in neural features to other addiction related disorders, and that response to in-game events may reflect psychological constructs characteristic to addiction. Perhaps most importantly, the present study paves way for future studies to use the fNIRS on diverse behavioral addiction conditions.