As the previous studies have mainly focused on the reward system and the corresponding brain regions, the relationship between brain morphology and excessive internet use (EIU) were not clear; the purpose of the study was to investigate if the brain regions other than the reward system were associated with EIU. Data were acquired from 131 excessive internet users. Psychological measures included internet use, life quality, personality, mental illness symptoms, impulsivity, and thought suppression. The brain was scanned with 3T magnetic resonance imaging (MRI) and six types of brain morphological indexes were calculated. Lasso regression methods were used to select the predictors. Stepwise linear regression methods were used to build the models and verify the model. The variables remaining in the model were left precentral (curve), left superior temporal (surface area), right cuneus (folding index), right rostral anterior cingulate (folding index), and harm avoidance. The independent variable was the EIU score of the worst week in the past year. The study found that the brain morphological indexes other than the reward system, including the left precentral (curve), the left superior temporal (surface area), the right cuneus (folding index), and the right rostral anterior cingulate (folding index), can predict the severity of EIU, suggesting an extensive change in the brain. In this study, a whole-brain data analysis was conducted and it was concluded that the changes in certain brain regions were more predictive than the reward system and psychological measures or more important for EIU.Li Wan and Rujing Zha are co-first authors.

Natural language processing (NLP) is central to the communication with machines and among ourselves, and NLP research field has long sought to produce human‐quality language. Identification of informative criteria for measuring NLP‐produced language quality will support development of ever‐better NLP tools. The authors hypothesize that mentalizing network neural activity may be used to distinguish NLP‐produced language from human‐produced language, even for cases where human judges cannot subjectively distinguish the language source. Using the social chatbots Google Meena in English and Microsoft XiaoIce in Chinese to generate NLP‐produced language, behavioral tests which reveal that variance of personality perceived from chatbot chats is larger than for human chats are conducted, suggesting that chatbot language usage patterns are not stable. Using an identity rating task with functional magnetic resonance imaging, neuroimaging analyses which reveal distinct patterns of brain activity in the mentalizing network including the DMPFC and rTPJ in response to chatbot versus human chats that cannot be distinguished subjectively are conducted. This study illustrates a promising empirical basis for measuring the quality of NLP‐produced language: adding a judge's implicit perception as an additional criterion.

Background and aims Internet gaming disorder (IGD) leads to serious impairments in cognitive functions, and lacks of effective treatments. Cue-induced craving is a hallmark feature of this disease and is associated with addictive memory elements. Memory retrieval-extinction manipulations could interfere with addictive memories and attenuate addictive syndromes, which might be a promising intervention for IGD. The aims of this study were to explore the effect of a memory retrieval-extinction manipulation on gaming cue-induced craving and reward processing in individuals with IGD. Methods A total of 49 individuals (mean age: 20.52 ± 1.58) with IGD underwent a memory retrieval-extinction training (RET) with a 10-min interval (R-10min-E, n = 24) or a RET with a 6-h interval (R-6h-E, n = 25) for two consecutive days. We assessed cue-induced craving pre- and post-RET, and at the 1- and 3-month follow-ups. The neural activities during reward processing were also assessed pre- and post-RET. Results Compared with the R-6h-E group, gaming cravings in individuals with IGD were significantly reduced after R-10min-E training at the 3-month follow-up (P < 0.05). Moreover, neural activities in the individuals with IGD were also altered after R-10min-E training, which was corroborated by enhanced reward processing, such as faster responses (P < 0.05) and stronger frontoparietal functional connectivity to monetary reward cues, while the R-6h-E training had no effects. Discussion and Conclusions The two-day R-10min-E training reduced addicts’ craving for Internet games, restored monetary reward processing in IGD individuals, and maintained long-term efficacy.

No abstract