Population maps of the corpus callosum (CC) and cortical lobe connections were generated by combining cortical gray matter parcellation with the diffusion tensor fiber tractography of individual subjects. This method is based on the fact that the cortical lobes of both hemispheres are interconnected by the corpus callosal fibers. T1-weighted structural MRIs and diffusion tensor MRIs (DT-MRI) of 22 right-handed, healthy subjects were used. Forty-seven cortical parcellations in the dorsal prefrontal cortex, ventral prefrontal cortex, sensory-motor cortex, parietal cortex, temporal cortex, and occipital cortex were semi-automatically derived from structural MRIs, registered to DT-MRI, and used to identify callosal fibers. The probabilistic connections to each cortex were mapped on entire mid-sagittal CC voxels that had anatomical homology between subjects as determined by spatial registration. According to the population maps of the callosal connections, the ventral prefrontal cortex and parts of the dorsal prefrontal cortex both project fibers through the genu and rostrum. The CC regions through which the superior frontal cortex passes extend into the posterior body. Fibers arising from the parietal lobe and occipital lobe run mainly through the splenium, while fibers arising from the sensory-motor cortex pass through the isthmus. In general, dorsal or medial cortical lobes project fibers through the dorsal region of the CC, while lateral cortical lobes project fibers through the ventral region of the CC. The probabilistic subdivision of the CC by connecting cortical gray matter provides a more precise understanding of the CC.

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Background and aimsProblematic Internet game use is an important social issue that increases social expenditures for both individuals and nations. This study identified predictors and patterns of problematic Internet game use.MethodsData were collected from online surveys between November 26 and December 26, 2014. We identified 3,881 Internet game users from a total of 5,003 respondents. A total of 511 participants were assigned to the problematic Internet game user group according to the Diagnostic and Statistical Manual of Mental Disorders Internet gaming disorder criteria. From the remaining 3,370 participants, we used propensity score matching to develop a normal comparison group of 511 participants. In all, 1,022 participants were analyzed using the chi-square automatic interaction detector (CHAID) algorithm.ResultsAccording to the CHAID algorithm, six important predictors were found: gaming costs (50%), average weekday gaming time (23%), offline Internet gaming community meeting attendance (13%), average weekend and holiday gaming time (7%), marital status (4%), and self-perceptions of addiction to Internet game use (3%). In addition, three patterns out of six classification rules were explored: cost-consuming, socializing, and solitary gamers.ConclusionThis study provides direction for future work on the screening of problematic Internet game use in adults.

Internet gaming addiction (IGA) is becoming a common and widespread mental health concern. Although IGA induces a variety of negative psychosocial consequences, it is yet ambiguous whether the brain addicted to Internet gaming is considered to be in a pathological state. We investigated IGA-induced abnormalities of the brain specifically from the network perspective and qualitatively assessed whether the Internet gaming-addicted brain is in a state similar to the pathological brain. Topological properties of brain functional networks were examined by applying a graphtheoretical approach to analyzing functional magnetic resonance imaging data acquired during a resting state in 19 IGA adolescents and 20 age-matched healthy controls. We compared functional distance-based measures, global and local efficiency of resting state brain functional networks between the two groups to assess how the IGA subjects' brain was topologically altered from the controls' brain. The IGA subjects had severer impulsiveness and their brain functional networks showed higher global efficiency and lower local efficiency relative to the controls. These topological differences suggest that IGA induced brain functional networks to shift toward the random topological architecture, as exhibited in other pathological states. Furthermore, for the IGA subjects, the topological alterations were specifically attributable to interregional connections incident on the frontal region, and the degree of impulsiveness was associated with the topological alterations over the frontolimbic connections. The current findings lend support to the proposition that the Internet gaming-addicted brain could be in the state similar to pathological states in terms of topological characteristics of brain functional networks.

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