Brain–Heart Interaction and the Experience of Flow While Playing a Video Game

Using caffeine as a chemical means to induce flow states

Flow is an intrinsically rewarding state characterised by positive affect and total task absorption. Because cognitive and physical performance are optimal in flow, chemical means to facilitate this state are appealing. Caffeine, a non-selective adenosine receptor antagonist, has been emphasized as a potential flow-inducer. Thus, we review the psychological and biological effects of caffeine that, conceptually, enhance flow. Caffeine may facilitate flow through various effects, including: i) upregulation of dopamine D1/D2 receptor affinity in reward-associated brain areas, leading to greater energetic arousal and 'wanting'; ii) protection of dopaminergic neurons; iii) increases in norepinephrine release and alertness, which offset sleep-deprivation and hypoarousal; iv) heightening of parasympathetic high frequency heart rate variability, resulting in improved cortical stress appraisal, v) modification of striatal endocannabinoid-CB1 receptor-signalling, leading to enhanced stress tolerance; and vi) changes in brain network activity in favour of executive function and flow. We also discuss the application of caffeine to treat attention deficit hyperactivity disorder and caveats. We hope to inspire studies assessing the use of caffeine to induce flow.

Heart Rate Variability during Online Video Game Playing in Habitual Gamers: Effects of Internet Addiction Scale, Ranking Score and Gaming Performance

Previous studies have demonstrated that individuals with internet gaming disorder (IGD) display abnormal autonomic activities at rest and during gameplay. Here, we examined whether and how in-game autonomic activity is modulated by human characteristics and behavioral performance of the player. We measured heart rate variability (HRV) in 42 male university student habitual gamers (HGs) when they played a round of League of Legends game online. Short-term HRV indices measured in early, middle and late phases of the game were compared between the players at high risk of developing IGD and those at low risk, as assessed by the revised Chen Internet addiction scale (CIAS-R). Multiple linear regression (MLR) was used to identify significant predictors of HRV measured over the whole gameplay period (WG), among CIAS-R, ranking score, hours of weekly playing and selected in-game performance parameters. The high-risk players showed a significantly higher low-frequency power/high-frequency power ratio (LF/HF) relative to the low-risk players, regardless of game phase. MLR analysis revealed that LF/HF measured in WG was predicted by, and only by, CIAS-R. The HRV indicators of sympathetic activity were found to be predicted only by the number of slain in WG (NSlain), and the indicators of parasympathetic activity were predicted by both CIAS-R and NSlain. Collectively, the results demonstrated that risk of developing IGD is associated with dysregulated autonomic balance during gameplay, and in-game autonomic activities are modulated by complex interactions among personal attributes and in-game behavioral performance of the player, as well as situational factors embedded in game mechanics.