In the current functional MRI study, we investigated interactions between reward and threat processing. Visual cues at the start of each trial informed participants about the chance of winning monetary reward and/or receiving a mild aversive shock. We tested two competing hypothesis: according to the 'salience hypothesis', in the condition involving both reward and threat, enhanced activation would be observed because of increased salience; according to the 'competition hypothesis', the processing of reward and threat would trade-off against each other, leading to reduced activation. Analysis of skin conductance data during a delay phase revealed an interaction between reward and threat processing, such that the effect of reward was reduced during threat and the effect of threat was reduced during reward. Analysis of imaging data during the same task phase revealed interactions between reward and threat processing in several regions, including the midbrain/ventral tegmental area, caudate, putamen, bed nucleus of the stria terminalis, anterior insula, middle frontal gyrus and dorsal anterior cingulate cortex. Taken together, our findings reveal conditions during which reward and threat trade-off against each other across multiple sites. Such interactions are suggestive of competitive processes and may reflect the organization of opponent systems in the brain.

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.

Epileptic seizures can initiate a neural circuit and lead to aberrant neural communication with brain areas outside the epileptogenic region. We focus on interictal activity in focal temporal lobe epilepsy and evaluate functional connectivity differences that emerge as function of bilateral versus strictly unilateral epileptiform activity. We assess the strength of functional connectivity at rest between the ictal and non-ictal temporal lobes, in addition to whole brain connectivity with the ictal temporal lobe. Results revealed strong connectivity between the temporal lobes for both patient groups, but this did not vary as a function of unilateral versus bilateral interictal status. Both the left and right unilateral temporal lobe groups showed significant anti-correlated activity in regions outside the epileptogenic temporal lobe, primarily involving the contralateral (non-ictal/non-pathologic) hemisphere, with precuneus involvement prominent. The bilateral groups did not show this contralateral anti-correlated activity. This anti-correlated connectivity may represent a form of protective and adaptive inhibition, helping to constrain epileptiform activity to the pathologic temporal lobe. The absence of this activity in the bilateral groups may be indicative of flawed inhibitory mechanisms, helping to explain their more widespread epileptiform activity. Our data suggest that the location and build up of epilepsy networks in the brain are not truly random, and are not limited to the formation of strictly epileptogenic networks. Functional networks may develop to take advantage of the regulatory function of structures such as the precuneus to instantiate an anti-correlated network, generating protective cortico-cortico inhibition for the purpose of limiting seizure spread or epileptogenesis.

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Although neuroimaging studies in adults demonstrate that cognitive reappraisal effectively down-regulates negative affect and results in increased prefrontal and decreased amygdala activity, very limited empirical data exist on the neural basis of cognitive reappraisal in children. This study aimed to pilot test a developmentally-appropriate guided cognitive reappraisal task in order to examine the effects of cognitive reappraisal on children’s self-reports of affect and brain responses. Study 1 (N =19, 4–10 years-old) found that children successfully employed guided cognitive reappraisal to decrease subjective ratings of negative affect, supporting the effectiveness of the guided cognitive reappraisal task. Study 2 (N =15, ages 6–10 years-old) investigated the neural responses to guided cognitive reappraisal and found that the neural responses showed increased activation in the amygdala and ventromedial prefrontal cortex during the cognitive reappraisal condition compared to the no regulation condition. In addition, amygdala activity was positively correlated with ventromedial prefrontal cortex activation during cognitive reappraisal. Findings suggest that the neural networks supporting cognitive reappraisal in children involve similar brain regions but brain responses deviate from findings in adults. Our findings suggest that the neural networks supporting emotion regulation are still developing during middle childhood, and future research is necessary to delineate age-related development of the neural network involved in cognitive reappraisal.

It is unclear whether deviations in brain and behavioral development, which may underpin elevated substance use during adolescence, are predispositions for or consequences of substance use initiation. Here, we examine behavioral and neuroimaging indices at early and mid-adolescence in drug-naive youths to identify possible predisposing factors for substance use initiation and its possible consequences. Method: Among 304 drug-naive adolescents at baseline (age 14 years) from the IMAGEN dataset, 83 stayed drug-naive, 133 used alcohol on 1 to 9 occasions, 42 on 10 to 19 occasions, 27 on 20 to 39 occasions, and 19 on >40 occasions at follow-up (age 16 years). Baseline measures included brain activation during the Monetary Incentive Delay task. Data at both baseline and follow-up included measures of trait impulsivity and delay discounting. Results: From baseline to follow-up, impulsivity decreased in the 0 and 1-to 9-occasions groups (p < .004), did not change in the 10-to 19-occasions and 20-to 29-occasions groups (p > .294), and uncharacteristically increased in the >40-occasions group (p ¼ .046). Furthermore, blunted medial orbitofrontal cortex activation during reward outcome at baseline significantly predicted higher alcohol use frequency at follow-up, above and beyond behavioral and clinical variables (p ¼ .008). Conclusion:These results suggest that the transition from no use to frequent drinking in early to mid-adolescence may disrupt normative developmental changes in behavioral control. In addition, blunted activity of the medial orbitofrontal cortex during reward outcome may underscore a predisposition toward the development of more severe alcohol use in adolescents. This distinction is clinically important, as it informs early intervention efforts in preventing the onset of substance use disorder in adolescents.

Individuals with mood/anxiety disorders may use cannabis for "self-medication," i.e., to induce positive mood or attenuate aversive mood states. However, little neurobiological evidence supports such use. The goal of this investigation was to test the hypothesis that cannabis use attenuates striatal response to reward in those with mood/ anxiety disorders. Reward-related processing was measured using a monetary incentive delay task under functional MRI. Individuals with any lifetime mood/anxiety disorder diagnoses and problematic cannabis use ("Mood/Anxiety +CB"; n = 41) were compared with a propensity score-matched group of similar subjects without cannabis use ("Mood/Anxiety-CB"; n = 41), and a cannabis-naïve healthy control group (n = 35). Activations during win-and lossanticipations were extracted from bilateral nucleus accumbens, dorsal caudate, and dorsolateral putamen. Mixed models were estimated for each region separately for win-and loss-anticipations, with a test for the main effect of group, condition (e.g., high-win, low-win, neutral), and their interaction. A significant main effect of group for win-and loss-anticipation was observed for each striatal region. Specifically, the Mood/Anxiety+CB group exhibited the lowest striatal activations across condition levels relative to both the Mood/Anxiety-CB and healthy group. A significant group-by-condition interaction was only observed for the dorsolateral putamen and indicated divergent activation modulation as a function of win and loss-magnitude for Mood/Anxiety+CB subjects. Finally, individuals with heavier recent cannabis use showed greater attenuation of gain-related activation in all three striatal regions. There was no such relationship for other illicit drugs. These data support the hypothesis that cannabis use in individuals with mood/ anxiety disorders is associated with attenuated brain processing of reward magnitude, which may contribute to persistent affective symptoms.

Background and aims: Graph theoretic analysis of structural covariance networks (SCN) provides an assessment of brain organization that has not yet been applied to alcohol dependence (AD). We estimated whether SCN differences are present in adults with AD and heavy-drinking adolescents at age 19 and age 14, prior to substantial exposure to alcohol.Design: Cross-sectional sample of adults and a cohort of adolescents. Correlation matrices for cortical thicknesses across 68 regions were summarized with graph theoretic metrics.Setting and participants: A total of 745 adults with AD and 979 non-dependent controls from 24 sites curated by the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA)-Addiction consortium, and 297 hazardous drinking adolescents and 594 controls at ages 19 and 14 from the IMAGEN study, all from Europe.Measurements: Metrics of network segregation (modularity, clustering coefficient and local efficiency) and integration (average shortest path length and global efficiency).