Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts.

Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population. IHI can be visually assessed on coronal slices of T1 weighted MR images, using a composite score that combines four anatomical criteria. IHI has been associated with several brain disorders (epilepsy, schizophrenia). However, these studies were based on small samples. Furthermore, the factors (genetic or environmental) that contribute to the genesis of IHI are largely unknown. Large-scale studies are thus needed to further understand IHI and their potential relationships to neurological and psychiatric disorders. However, visual evaluation is long and tedious, justifying the need for an automatic method. In this paper, we propose, for the first time, to automatically rate IHI. We proceed by predicting four anatomical criteria, which are then summed up to form the IHI score, providing the advantage of an interpretable score. We provided an extensive experimental investigation of different machine learning methods and training strategies. We performed automatic rating using a variety of deep learning models ("conv5-FC3", ResNet and "SECNN") as well as a ridge regression. We studied the generalization of our models using different cohorts and performed multi-cohort learning. We relied on a large population of 2,008 participants from the IMAGEN study, 993 and 403 participants from the QTIM and QTAB studies as well as 985 subjects from the UKBiobank. We showed that deep learning models outperformed a ridge regression. We demonstrated that the performances of the "conv5-FC3" network were at least as good as more complex networks while maintaining a low complexity and computation time. We showed that training on a single cohort may lack in variability while training on several cohorts improves generalization (acceptable performances on all tested cohorts including some that are not included in training). The trained models will be made publicly available should the manuscript be accepted.

Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents.

Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use.

Prediction of alcohol drinking in adolescents: Personality-traits, behavior, brain responses, and genetic variations in the context of reward sensitivity.

Adolescence is a time that can set the course of alcohol abuse later in life. Sensitivity to reward on multiple levels is a major factor in this development. We examined 736 adolescents from the IMAGEN longitudinal study for alcohol drinking during early (mean age=14.37) and again later (mean age=16.45) adolescence. Conducting structural equation modeling we evaluated the contribution of reward-related personality traits, behavior, brain responses and candidate genes. Personality seems to be most important in explaining alcohol drinking in early adolescence. However, genetic variations in ANKK1 (rs1800497) and HOMER1 (rs7713917) play an equal role in predicting alcohol drinking two years later and are most important in predicting the increase in alcohol consumption. We hypothesize that the initiation of alcohol use may be driven more strongly by personality while the transition to increased alcohol use is more genetically influenced.

Cannabis use in early adolescence: Evidence of amygdala hypersensitivity to signals of threat.

Cannabis use in adolescence may be characterized by differences in the neural basis of affective processing. In this study, we used an fMRI affective face processing task to compare a large group (n=70) of 14-year olds with a history of cannabis use to a group (n=70) of never-using controls matched on numerous characteristics including IQ, SES, alcohol and cigarette use. The task contained short movies displaying angry and neutral faces. Results indicated that cannabis users had greater reactivity in the bilateral amygdalae to angry faces than neutral faces, an effect that was not observed in their abstinent peers. In contrast, activity levels in the cannabis users in cortical areas including the right temporal-parietal junction and bilateral dorsolateral prefrontal cortex did not discriminate between the two face conditions, but did differ in controls. Results did not change after excluding subjects with any psychiatric symptomology. Given the high density of cannabinoid receptors in the amygdala, our findings suggest cannabis use in early adolescence is associated with hypersensitivity to signals of threat. Hypersensitivity to negative affect in adolescence may place the subject at-risk for mood disorders in adulthood.

The Brain's Response to Reward Anticipation and Depression in Adolescence: Dimensionality, Specificity, and Longitudinal Predictions in a Community-Based Sample.

OBJECTIVE: The authors examined whether alterations in the brain's reward network operate as a mechanism across the spectrum of risk for depression. They then tested whether these alterations are specific to anhedonia as compared with low mood and whether they are predictive of depressive outcomes. METHOD: Functional MRI was used to collect blood-oxygen-level-dependent (BOLD) responses to anticipation of reward in the monetary incentive task in 1,576 adolescents in a community-based sample. Adolescents with current subthreshold depression and clinical depression were compared with matched healthy subjects. In addition, BOLD responses were compared across adolescents with anhedonia, low mood, or both symptoms, cross-sectionally and longitudinally. RESULTS: Activity in the ventral striatum was reduced in participants with subthreshold and clinical depression relative to healthy comparison subjects. Low ventral striatum activation predicted transition to subthreshold or clinical depression in previously healthy adolescents at 2-year follow-up. Brain responses during reward anticipation decreased in a graded manner between healthy adolescents, adolescents with current or future subthreshold depression, and adolescents with current or future clinical depression. Low ventral striatum activity was associated with anhedonia but not low mood; however, the combined presence of both symptoms showed the strongest reductions in the ventral striatum in all analyses. CONCLUSIONS: The findings suggest that reduced striatal activation operates as a mechanism across the risk spectrum for depression. It is associated with anhedonia in healthy adolescents and is a behavioral indicator of positive valence systems, consistent with predictions based on the Research Domain Criteria.

New evidence of factor structure and measurement invariance of the SDQ across five European nations.

The main purpose of the present study was to analyse the internal structure and to test the measurement invariance of the Strengths and Difficulties Questionnaire (SDQ), self-reported version, in five European countries. The sample consisted of 3012 adolescents aged between 12 and 17 years (M = 14.20; SD = 0.83). The five-factor model (with correlated errors added), and the five-factor model (with correlated errors added) with the reverse-worded items allowed to cross-load on the Prosocial subscale, displayed adequate goodness of-fit indices. Multi-group confirmatory factor analysis showed that the five-factor model (with correlated errors added) had partial strong measurement invariance by countries. A total of 11 of the 25 items were non-invariant across samples. The level of internal consistency of the Total difficulties score was 0.84, ranging between 0.69 and 0.78 for the SDQ subscales. The findings indicate that the SDQ's subscales need to be modified in various ways for screening emotional and behavioural problems in the five European countries that were analysed.