Exploring timescale-specific functional brain networks and their associations with aging and cognitive performance in a healthy cohort without dementia.

INTRODUCTION: Functional brain networks (FBNs) coordinate brain functions and are studied in fMRI using blood-oxygen-level-dependent (BOLD) signal correlations. Previous research links FBN changes to aging and cognitive decline, but various physiological factors influnce BOLD signals. Few studies have investigated the intrinsic components of the BOLD signal in different timescales using signal decomposition. This study aimed to explore differences between intrinsic FBNs and traditional BOLD-FBN, examining their associations with age and cognitive performance in a healthy cohort without dementia. MATERIALS AND METHODS: A total of 396 healthy participants without dementia (men = 157; women = 239; age range = 20-85 years) were enrolled in this study. The BOLD signal was decomposed into several intrinsic signals with different timescales using ensemble empirical mode decomposition, and FBNs were constructed based on both the BOLD and intrinsic signals. Subsequently, network features-global efficiency and local efficiency values-were estimated to determine their relationship with age and cognitive performance. RESULTS: The findings revealed that the global efficiency of traditional BOLD-FBN correlated significantly with age, with specific intrinsic FBNs contributing to these correlations. Moreover, local efficiency analysis demonstrated that intrinsic FBNs were more meaningful than traditional BOLD-FBN in identifying brain regions related to age and cognitive performance. CONCLUSIONS: These results underscore the importance of exploring timescales of BOLD signals when constructing FBN and highlight the relevance of specific intrinsic FBNs to aging and cognitive performance. Consequently, this decomposition-based FBN-building approach may offer valuable insights for future fMRI studies.

Roles of Hostility and Depression in the Association between the MAOA Gene Polymorphism and Internet Gaming Disorder.

The metabolism of bioamine in the central nervous system contributes to the development of addiction. We examined the roles of hostility and depression in the association between internet gaming disorder (IGD) and monoamine oxidase-A (MAOA) EcoRV polymorphism (rs1137070). A total of 69 adults with IGD and 138 without IGD were recruited through diagnostic interviewing. We evaluated participants for rs1137070, depression, and hostility. The participants with the TT genotype of rs1137070 had a higher odds ratio of 2.52 (1.37-4.64) for IGD compared with the C carriers. Expressive hostility behavior and hostility cognition mediated the association between rs1137070 and IGD. Indicating lower MAOA activity, the TT genotype predicted IGD and higher expressive hostility behavior and hostility cognition. Expressive hostility behavior and hostility cognition may underline the association between rs1137070 and IGD. Assessment of and intervention for hostility behavior and cognition should be provided to attenuate the risk of IGD, particularly in those with the TT genotype. Further brain imaging or neurobiological studies are required to elucidate the possible mechanism underlying the association between MAOA activity and IGD.

The Clinical Utility of the Chen Internet Addiction Scale-Gaming Version, for Internet Gaming Disorder in the DSM-5 among Young Adults.

Objectives: The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) includes the diagnostic criteria for Internet gaming disorder (IGD). This study evaluated (1) the screening, diagnostic, and prevalence-estimated cutoff points of the Chen Internet Addiction Scale-Gaming Version (CIAS-G) for IGD in the DSM-5; and (2) the differences in the CIAS-G and subscale scores among individuals with IGD, regular gamers (RGs), and other control subjects. Methods: We recruited 69 participants with IGD, 69 RGs, and 69 healthy participants based on diagnostic interviews conducted by a psychiatrist according to DSM-5 IGD criteria. All participants completed the CIAS-G and were assessed using the clinical global impression scale. Results: The optimal screening and diagnostic cutoff points were 68 or more (sensitivity, 97.1%; specificity, 76.8%) and 72 or more (sensitivity, 85.5%; specificity, 87.0%) for IGD based on DSM-5 criteria, respectively. The 76 or more cutoff point had the highest number needed to misdiagnose and was the optimal prevalence estimated cutoff point. Conclusions: The screening cutoff point could be used to identify individuals with IGD for further diagnostic interviewing to confirm the diagnosis in the clinical setting or for two-stage epidemiological evaluation. The diagnostic cutoff point provides a provisional diagnosis of IGD when diagnostic interviewing is unavailable. The prevalence-estimated cutoff point could be used to estimate the prevalence of IGD in large-scale epidemiological investigations when further diagnostic interviewing is impractical. The clinical and epidemiological utility of CIAS-G warrants further study.