Fundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity and between-pipeline reproducibility of the processed gray matter brain maps were generally low between pipelines. Examination of sex-differences and age-related changes revealed considerable differences between the pipelines in terms of the specific regions identified. Machine learning-based multivariate analyses allowed accurate predictions of sex and age, however accuracy differed between pipelines. Our findings suggest that the choice of pipeline alone leads to considerable variability in brain structural markers which poses a serious challenge for reproducibility and interpretation.

Background and aimsGrowing concerns about the addictive nature of Internet and computer games led to the preliminary recognition of Internet Gaming Disorder (IGD) as an emerging disorder by the American Psychiatric Association (APA) and the official recognition of Gaming Disorder (GD) as a new diagnosis by the World Health Organization (WHO). While the definition of clear diagnostic criteria for (I) GD represents an important step for diagnosis and treatment of the disorder, potential neurobiological correlates of the criteria remain to be explored.MethodsThe present study employed a dimensional Magnetic Resonance Imaging (MRI) approach to determine associations between (I)GD symptom-load according to the APA and WHO diagnostic frameworks and brain structure in a comparably large sample of n = 82 healthy subjects.ResultsHigher symptom-load on both, the APA and WHO diagnostic frameworks convergently associated with lower volumes of the striatum.DiscussionThe results from this exploratory study provide the first initial evidence for a neurobiological foundation of the proposed diagnostic criteria for (I)GD according to both diagnostic classification systems and suggest that the transition from non-disordered to disordered gaming may be accompanied by progressive neuroplastic changes in the striatum, thus resembling progressive changes in other addictive disorders.ConclusionsThe proposed (I)GD criteria in both diagnostic systems were associated with neurostructural alterations in the striatum, suggesting an association with progressive changes in the motivational systems of the brain.

A large number of computer-based training programs have been developed as an intervention to help individuals with autism spectrum disorders (ASD) improve their facial emotion recognition ability, as well as social skills. However, it is unclear to what extent these facial emotion training programs can produce beneficial, long-lasting, and generalizable results. Using standard meta-analytic techniques, we investigated the effects of facial emotion training including generalization and maintenance restricted to randomized control trial studies comprising a total of 595 individuals with ASD. Our findings revealed that the intervention resulted in a robust improvement in emotion recognition for individuals receiving training compared with controls. However, while there was also some evidence for generalization of training effects, the small number of studies which conducted follow-ups and assessed social skills reported that improvements were not maintained and there was no evidence for general improvement in social skills. Overall, the analysis revealed a medium effect size in training improvement indicating that facial emotion training may be an effective method for enhancing emotion recognition skills in ASD although more studies are required to assess maintenance of effects and possible general improvements in social skills. Lay summaryFacial emotion training as an intervention may be a potential way to help improve emotion recognition in autism spectrum disorder (ASD), however robust empirical support for its efficacy has not been sufficiently established. Here, we conducted a meta-analysis of previous studies to summarize the effects of facial emotion training on ASD. Our results show that the training produces a robust improvement in subsequent emotion recognition, while maintenance and generalization effects still need further investigation. To date, no experimentally verified improvements in social skills have been reported.

The motivation to strive for and consume primary rewards such as palatable food is bound by internal satiation and devaluation mechanisms, yet secondary rewards such as money may not be bound by these regulatory mechanisms. The present study therefore aimed at determining diverging devaluation trajectories for primary (chocolate milk) and secondary (money) reinforcers on the behavioral and neural level. Satiation procedures combined with a choice (Experiment 1) and an incentive delay (Experiment 2) paradigm consistently revealed decreased hedonic value for the primary reward as reflected by decreasing hedonic evaluation and choice preference, while hedonic value and preferences for the secondary reward increased. Concomitantly acquired functional near-infrared spectroscopy (fNIRS) data during the incentive delay paradigm revealed that increasing value of the secondary reward was accompanied by increasing anticipatory activation in the lateral orbitofrontal cortex, while during the consummatory phase the secondary reinforcer associated with higher medial orbitofrontal activity irrespective of devaluation stage. Overall, the findings suggest that -in contrast to primary reinforcers -secondary reinforcers can acquire progressively enhanced incentive motivation with repeated receipt, suggesting a mechanism which could promote escalating striving to obtain secondary rewards..

Own race faces tend to be recognized more accurately than those of other less familiar races, however, findings to date have been inconclusive. The present study aimed to determine whether Chinese exhibit different recognition accuracy and eye gaze patterns for Asian (own-race) and White (other-race) facial expressions (neutral, happiness, sadness, anger, disgust, fear). A total of 89 healthy Chinese adults viewed Asian and White facial expressions while undergoing eye-tracking and were subsequently required to identify expressions and rate their intensity and effect on arousal. Results revealed that subjects recognized sad expressions in Asian faces better than in White ones. On the other hand, recognition accuracy was higher for White neutral, happy, fearful, and disgusted expressions although this may have been due to subjects more often misclassifying these Asian expressions as sadness. Moreover, subjects viewed the eyes of emotional expressions longer in Asian compared to White faces and the nose of sad ones, especially during the late phase of presentation, whereas pupil sizes, indicative of cognitive load and arousal, were smaller. Eye-gaze patterns were not, however, associated with recognition accuracy. Overall, findings demonstrate an own-race bias in Chinese for identifying sad expressions and more generally across emotional expressions in terms of viewing the eye region of emotional faces for longer and with reduced pupil size. Interestingly, subjects were significantly more likely to miss-identify Asian faces as sad resulting in an apparent other-race bias for recognizing neutral, happy, fearful, and disgusted expressions.