The processes involved in value evaluation and self‐control are critical when making behavioral choices. However, the evidence linking these two types of processes to behavioral choices in intertemporal decision‐making remains elusive. As the ventromedial prefrontal cortex (vmPFC), striatum, and dorsolateral prefrontal cortex (dlPFC) have been associated with these two processes, we focused on these three regions. We employed functional magnetic resonance imaging during a delayed discounting task (DDT) using a relatively large sample size, three independent samples. We evaluated how much information about a specific choice could be decoded from local patterns in each brain area using multivoxel pattern analysis (MVPA). To investigate the relationship between the dlPFC and vmPFC/striatum regions, we performed a psychophysiological interaction (PPI) analysis. In Experiment I, we found that the vmPFC and dlPFC, but not the striatum, could determine choices in healthy participants. Furthermore, we found that the dlPFC showed significant functional connectivity with the vmPFC, but not the striatum, when making decisions. These results could be replicated in Experiment II with an independent sample of healthy participants. In Experiment III, the choice‐decoding accuracy in the vmPFC and dlPFC was lower in patients with addiction (smokers and participants with Internet gaming disorder) than in healthy participants, and decoding accuracy in the dlPFC was related to impulsivity in addicts. Taken together, our findings may provide neural evidence supporting the hypothesis that value evaluation and self‐control processes both guide the intertemporal choices, and might provide potential neural targets for the diagnosis and treatment of impulsivity‐related brain disorders.

The outbreak of the novel coronavirus disease 2019 (COVID-19) has increased concern about people's mental health under such serious stressful situation, especially depressive symptoms. Cognitive biases have been related to depression degree in previous studies. Here, we used behavioral and brain imaging analysis, to determine if and how the COVID-19 pandemic affects the relationship between current cognitive biases and future depression degree and the underlying neural basis in a nonclinical depressed population. An out-expectation result showed that a more negative memory bias was associated with a greater decrease in future depressive indices in nonclinical depressed participants during the COVID-19 pandemic, which might be due to decreased social stress. These data enhance our understanding of how the depressive degree of nonclinical depressed populations will change during the COVID-19 pandemic and also provide support for social distancing policies from a psychological perspective.

In the grand challenges of successful social encounters with socially sophisticated robots and shaping the future development of robots in socially acceptable ways, we need to quantify people perception to the robots. The critical assumption at the perception to humanoid robots, namely that people perceive humanoid robots as an evolutionary threat, has not been directly confirmed. We assume the existence of behavioral and neural automaticity for humanoid robots that were previously only evident for evolutionary threats. Here, we observed a monocular advantage for the perception of humanoid robots the same as an evolutionary threat (i.e., snakes). Our neuroimaging analysis indicated that unconscious presentation of humanoid robot vs. human images led to significant left amygdala activation that was associated with negative implicit attitude to humanoid robots. After successfully weakening negative attitude, the left amygdala response to unconscious presentation of humanoid robot images decreased, and the decrease of left amygdala response was positively associated with the decrease of negative attitude. Our results reveal that processing of information about humanoid robots displays automaticity with regard to recruitment of visual pathway and amygdala activation. Our findings that humans may perceive humanoid robots as an evolutionary threat will guide the future direction of robots development and bring us closer to interacting with socially sophisticated robots.

Objective This research aims to develop a laboratory model that can accurately distinguish pneumonia from nonpneumonia in patients with COVID-19 and to identify potential protective factors against lung infection. Methods We recruited 50 patients diagnosed with COVID-19 infection with or without pneumonia. We selected candidate predictors through group comparison and punitive least absolute shrinkage and selection operator (LASSO) analysis. A stepwise logistic regression model was used to distinguish patients with and without pneumonia. Finally, we used a decision-tree method and randomly selected 50% of the patients 1000 times from the same specimen to verify the effectiveness of the model. Results We found that the percentage of eosinophils, a high–fluorescence-reticulocyte ratio, and creatinine had better discriminatory power than other factors. Age and underlying diseases were not significant for discrimination. The model correctly discriminated 77.1% of patients. In the final validation step, we observed that the model had an overall predictive rate of 81.3%. Conclusion We developed a laboratory model for COVID-19 pneumonia in patients with mild to moderate symptoms. In the clinical setting, the model will be able to predict and differentiate pneumonia vs nonpneumonia before any lung computed tomography findings. In addition, the percentage of eosinophils, a high–fluorescence-reticulocyte ratio, and creatinine were considered protective factors against lung infection in patients without pneumonia.

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.