Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood.

Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.

The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features.

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.

Individual differences in stop-related activity are inflated by the adaptive algorithm in the stop signal task.

Research using the Stop Signal Task employing an adaptive algorithm to accommodate individual differences often report inferior performance on the task in individuals with ADHD, OCD, and substance use disorders compared to non-clinical controls. Furthermore, individuals with deficits in inhibitory control tend to show reduced neural activity in key inhibitory regions during successful stopping. However, the adaptive algorithm systematically introduces performance-related differences in objective task difficulty that may influence the estimation of individual differences in stop-related neural activity. This report examines the effect that these algorithm-related differences have on the measurement of neural activity during the stop signal task. We compared two groups of subjects (n = 210) who differed in inhibitory ability using both a standard fMRI analysis and an analysis that resampled trials to remove the objective task difficulty confound. The results show that objective task difficulty influences the magnitude of between-group differences and that controlling for difficulty attenuates stop-related activity differences between superior and poor inhibitors. Specifically, group differences in the right inferior frontal gyrus, right middle occipital gyrus, and left inferior frontal gyrus are diminished when differences in objective task difficulty are controlled for. Also, when objective task difficulty effects are exaggerated, group differences in stop related activity emerge in other regions of the stopping network. The implications of these effects for how we interpret individual differences in activity levels are discussed.

Low Smoking Exposure, the Adolescent Brain, and the Modulating Role of CHRNA5 Polymorphisms.

BACKGROUND: Studying the neural consequences of tobacco smoking during adolescence, including those associated with early light use, may help expose the mechanisms that underlie the transition from initial use to nicotine dependence in adulthood. However, only a few studies in adolescents exist, and they include small samples. In addition, the neural mechanism, if one exists, that links nicotinic receptor genes to smoking behavior in adolescents is still unknown. METHODS: Structural and diffusion tensor magnetic resonance imaging data were acquired from a large sample of 14-year-old adolescents who completed an extensive battery of neuropsychological, clinical, personality, and drug-use assessments. Additional assessments were conducted at 16 years of age. RESULTS: Exposure to smoking in adolescents, even at low doses, is linked to volume changes in the ventromedial prefrontal cortex and to altered neuronal connectivity in the corpus callosum. The longitudinal analyses strongly suggest that these effects are not preexisting conditions in those who progress to smoking. There was a genetic contribution wherein the volume reduction effects were magnified in smokers who were carriers of the high-risk genotype of the alpha 5 nicotinic receptor subunit gene, rs16969968. CONCLUSIONS: These findings give insight into a mechanism involving genes, brain structure, and connectivity underlying why some adolescents find nicotine especially addictive.

A split-brain case study on the hemispheric lateralization of inhibitory control.

Understanding the neurobiological mechanisms underlying inhibitory control is crucial given its role in various disease states and substance abuse/misuse. Neuroimaging research examining inhibitory control has yielded conflicting results on the relative importance of the left and right hemisphere during successful inhibition of a motor response. In the current study, a split-brain patient was examined in order to assess the independent inhibitory capabilities of each hemisphere. The patient's right hemisphere exhibited superior inhibitory ability compared to his left hemisphere on three inhibitory control tasks. Although inferior to the right, the left hemisphere inhibited motor responses on inhibitory trials in all three tasks. The results from this study support the dominance of the right hemisphere in inhibitory control.

Age-related volumetric change of limbic structures and subclinical anxious/depressed symptomatology in typically developing children and adolescents.

OBJECTIVE: To investigate the extent to which subclinical variation in anxious/depressed psychopathology is associated with volume and age-related volumetric change of limbic structures in a longitudinal sample of healthy youths. METHODS: Linear mixed-effects models were used to analyze longitudinal behavioral and neuroimaging data (up to 3 data points per subject, collected at 2 year-intervals) in 371 typically developing youths, from 4 to 18 years of age (196 females; 723 MRIs). Volumetric measures were obtained using a validated segmentation method. The best-fit model (cubic, quadratic, or first-order linear) was determined for the effect of age on amygdalar and hippocampal volume (adjusted for total brain volume). Next, amygdalar and hippocampal volumes were regressed against Child Behavior Checklist Anxious/Depressed (A/D) scores. Age-by-A/D and sex-by-A/D interactions were tested. RESULTS: Analyses revealed age-related linear and quadratic volumetric change in the amygdalae and hippocampi, respectively. A/D was positively associated with total amygdalar volume (p=0.045), independent of age and sex. Age-by-A/D and sex-by-A/D interactions were not associated with amygdalar or hippocampal volume. CONCLUSIONS: Results suggest that amygdalar structure is tied to A/D among typically developing youths, independent of age and sex. Developmental trajectories of amygdalar and hippocampal volume were not associated with subclinical anxiety. Taken together, increased amygdalar volume may serve as a significant marker of anxiety, regardless of developmental phase.

Inattention and Reaction Time Variability Are Linked to Ventromedial Prefrontal Volume in Adolescents.

BACKGROUND: Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability-an index of lapses in attention. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression. METHODS: Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated. RESULTS: Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology. CONCLUSIONS: This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD.