Distinct neural networks predict cocaine versus cannabis treatment outcomes.

Treatment outcomes for individuals with substance use disorders (SUDs) are variable and more individualized approaches may be needed. Cross-validated, machine-learning methods are well-suited for probing neural mechanisms of treatment outcomes. Our prior work applied one such approach, connectome-based predictive modeling (CPM), to identify dissociable and substance-specific neural networks of cocaine and opioid abstinence. In Study 1, we aimed to replicate and extend prior work by testing the predictive ability of the cocaine network in an independent sample of 43 participants from a trial of cognitive-behavioral therapy for SUD, and evaluating its ability to predict cannabis abstinence. In Study 2, CPM was applied to identify an independent cannabis abstinence network. Additional participants were identified for a combined sample of 33 with cannabis-use disorder. Participants underwent fMRI scanning before and after treatment. Additional samples of 53 individuals with co-occurring cocaine and opioid-use disorders and 38 comparison subjects were used to assess substance specificity and network strength relative to participants without SUDs. Results demonstrated a second external replication of the cocaine network predicting future cocaine abstinence, however it did not generalize to cannabis abstinence. An independent CPM identified a novel cannabis abstinence network, which was (i) anatomically distinct from the cocaine network, (ii) specific for predicting cannabis abstinence, and for which (iii) network strength was significantly stronger in treatment responders relative to control particpants. Results provide further evidence for substance specificity of neural predictors of abstinence and provide insight into neural mechanisms of successful cannabis treatment, thereby identifying novel treatment targets. Clinical trials registation: "Computer-based training in cognitive-behavioral therapy web-based (Man VS Machine)", registration number: NCT01442597 . "Maximizing the Efficacy of Cognitive Behavior Therapy and Contingency Management", registration number: NCT00350649 . "Computer-Based Training in Cognitive Behavior Therapy (CBT4CBT)", registration number: NCT01406899 .

Predicting the future of neuroimaging predictive models in mental health.

Predictive modeling using neuroimaging data has the potential to improve our understanding of the neurobiology underlying psychiatric disorders and putatively information interventions. Accordingly, there is a plethora of literature reviewing published studies, the mathematics underlying machine learning, and the best practices for using these approaches. As our knowledge of mental health and machine learning continue to evolve, we instead aim to look forward and "predict" topics that we believe will be important in current and future studies. Some of the most discussed topics in machine learning, such as bias and fairness, the handling of dirty data, and interpretable models, may be less familiar to the broader community using neuroimaging-based predictive modeling in psychiatry. In a similar vein, transdiagnostic research and targeting brain-based features for psychiatric intervention are modern topics in psychiatry that predictive models are well-suited to tackle. In this work, we target an audience who is a researcher familiar with the fundamental procedures of machine learning and who wishes to increase their knowledge of ongoing topics in the field. We aim to accelerate the utility and applications of neuroimaging-based predictive models for psychiatric research by highlighting and considering these topics. Furthermore, though not a focus, these ideas generalize to neuroimaging-based predictive modeling in other clinical neurosciences and predictive modeling with different data types (e.g., digital health data).

Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling.

Opioid use disorder is a major public health crisis. While effective treatments are available, outcomes vary widely across individuals and relapse rates remain high. Understanding neural mechanisms of treatment response may facilitate the development of personalized and/or novel treatment approaches. Methadone-maintained, polysubstance-using individuals (n = 53) participated in fMRI scanning before and after substance-use treatment. Connectome-based predictive modeling (CPM)-a recently developed, whole-brain approach-was used to identify pretreatment connections associated with abstinence during the 3-month treatment. Follow-up analyses were conducted to determine the specificity of the identified opioid abstinence network across different brain states (cognitive vs. reward task vs. resting-state) and different substance use outcomes (opioid vs. cocaine abstinence). Posttreatment fMRI data were used to assess network changes over time and within-subject replication. To determine further clinical relevance, opioid abstinence network strength was compared with healthy subjects (n = 38). CPM identified an opioid abstinence network (p = 0.018), characterized by stronger within-network motor/sensory connectivity, and reduced connectivity between the motor/sensory network and medial frontal, default mode, and frontoparietal networks. This opioid abstinence network was anatomically distinct from a previously identified cocaine abstinence network. Relationships between abstinence and opioid and cocaine abstinence networks replicated across multiple brain states but did not generalize across substances. Network connectivity measured at posttreatment related to abstinence at 6-month follow-up (p < 0.009). Healthy comparison subjects displayed intermediate network strengths relative to treatment responders and nonresponders. These data indicate dissociable anatomical substrates of opioid vs. cocaine abstinence. Results may inform the development of novel opioid-specific treatment approaches to combat the opioid epidemic.

Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study.

Adolescence is the peak period for the emergence of substance use, which can lead to long-term psychosocial, occupational and interpersonal complications. Ongoing large-scale, longitudinal, consortium initiatives, such as the Adolescent Brain and Cognitive Development (ABCD) study, offer unprecedented opportunities to elucidate key risk factors for problematic substance use in a well-powered sample and to examine how changes in risk factors relate to symptoms across time. Delay discounting has been proposed as a putative risk marker for early substance-use initiation and other forms of psychopathology. However, the extent to which other factors (e.g., socio-economic status and cognitive ability) influence discounting behaviour in young adolescents is not well established. The present study leverages data from the ABCD study (n = 11 045) to assess associations between core demographic and familial variables and delay discounting in youth-operationalized using hyperbolic discounting rates (k)-before the onset of significant psychopathology. Model estimates revealed significant effects of individual difference factors (e.g., sex and socio-economic status) and alcohol risk status (based on family history) on delay discounting. No significant differences were observed in the primary sample when comparing the presence of parent drug problems or prenatal drug exposures. These effects will require replication in later waves of ABCD. Nonetheless, these results provide support for delay discounting as a potential risk marker for problematic alcohol use and demonstrate a relationship between key demographic variables and adolescent discounting behaviour. Further, these results provide an empirical baseline from which developmental trajectories of delay discounting and substance use may be tracked throughout future waves of ABCD.

Volumetric Differences in Cerebellar Lobes in Individuals from Multiplex Alcohol Dependence Families and Controls: Their Relationship to Externalizing and Internalizing Disorders and Working Memory.

Offspring from families with multiple cases of alcohol dependence have a greater likelihood of developing alcohol dependence and related substance use disorders. Greater susceptibility for these disorders may be related to cerebellar morphology. Because posterior regions of the cerebellum are associated with cognitive abilities, we investigated whether high-risk offspring would display regionally specific differences in cerebellar morphology and whether these would be related to working memory performance. The relationship to externalizing and internalizing psychopathology was of interest because cerebellar morphology has previously been associated with a cognitive affective syndrome. A total of 131 participants underwent magnetic resonance imaging (MRI) with volumes of the cerebellar lobes obtained with manual tracing. These individuals were from high-risk (HR) for alcohol dependence families (N = 72) or from low-risk (LR) control families (N = 59). All were enrolled in a longitudinal follow-up that included repeated clinical assessments during childhood and young-adulthood prior to the scan that provided information on Axis I psychopathology. The Working Memory Index of the Wechsler Memory Scale was given at the time of the scan. Larger volumes of the corpus medullare and inferior posterior lobes and poorer working memory performance were found for the HR offspring relative to LR controls. Across all subjects, a significant positive association between working memory and total volume of corpus of the cerebellum was seen, controlling for familial risk. Presence of an internalizing or externalizing disorder interacting with familial risk was also associated with volume of the corpus medullare.

Identification of a Composite Latent Dimension of Reward and Impulsivity Across Clinical, Behavioral, and Neurobiological Domains Among Youth.

BACKGROUND: Individual differences in reward processing are central to heightened risk-taking behaviors during adolescence, but there is inconsistent evidence for the relationship between risk-taking phenotypes and the neural substrates of these behaviors. METHODS: Here, we identify latent features of reward in an attempt to provide a unifying framework linking together aspects of the brain and behavior during early adolescence using a multivariate pattern learning approach. Data (N = 8295; n male = 4190; n female = 4105) were acquired as part of the Adolescent Brain Cognitive Development (ABCD) Study and included neuroimaging (regional neural activity responses during reward anticipation) and behavioral (e.g., impulsivity measures, delay discounting) variables. RESULTS: We revealed a single latent dimension of reward driven by shared covariation between striatal, thalamic, and anterior cingulate responses during reward anticipation, negative urgency, and delay discounting behaviors. Expression of these latent features differed among adolescents with attention-deficit/hyperactivity disorder and disruptive behavior disorder, compared with those without, and higher expression of these latent features was negatively associated with multiple dimensions of executive function and cognition. CONCLUSIONS: These results suggest that cross-domain patterns of anticipatory reward processing linked to negative features of impulsivity exist in both the brain and in behavior during early adolescence and that these are representative of 2 commonly diagnosed reward-related psychiatric disorders, attention-deficit/hyperactivity disorder and disruptive behavior disorder. Furthermore, they provide an explicit baseline from which multivariate developmental trajectories of reward processes may be tracked in later waves of the ABCD Study and other developmental cohorts.

Brain Networks and Adolescent Alcohol Use.

Importance: Alcohol misuse in adolescence is a leading cause of disability and mortality in youth and is associated with higher risk for alcohol use disorder. Brain mechanisms underlying risk of alcohol misuse may inform prevention and intervention efforts. Objective: To identify neuromarkers of alcohol misuse using a data-driven approach, with specific consideration of neurodevelopmental sex differences. Design, Setting, and Participants: Longitudinal multisite functional magnetic resonance imaging (fMRI) data collected at ages 14 and 19 years were used to assess whole-brain patterns of functional organization associated with current and future alcohol use risk as measured by the Alcohol Use Disorder Identification Test (AUDIT). Primary data were collected by the IMAGEN consortium, a European multisite study of adolescent neurodevelopment. Model generalizability was further tested using data acquired in a single-site study of college alcohol consumption conducted in the US. The primary sample was a developmental cohort of 1359 adolescents with neuroimaging, phenotyping, and alcohol use data. Model generalizability was further assessed in a separate cohort of 114 individuals. Main Outcomes and Measures: Brain-behavior model accuracy, as defined by the correspondence between model-predicted and actual AUDIT scores in held-out testing data, Bonferroni corrected across the number of models run at each time point, 2-tailed α < .008, as determined via permutation testing. Results: Among 1359 individuals in the study, the mean (SD) age was 14.42 (0.40) years, and 729 individuals (54%) were female. The data-driven, whole-brain connectivity approach identified networks associated with vulnerability for future and current AUDIT-defined alcohol use risk (primary outcome, as specified above, future: ρ, 0.22; P < .001 and present: ρ, 0.27; P < .001). Results further indicated sex divergence in the accuracies of brain-behavior models, such that female-only models consistently outperformed male-only models. Specifically, female-only models identified networks conferring vulnerability for future and current severity using data acquired during both reward and inhibitory fMRI tasks. In contrast, male-only models were successful in accurately identifying networks using data acquired during the inhibitory control-but not reward-task, indicating domain specificity of alcohol use risk networks in male adolescents only. Conclusions and Relevance: These data suggest that interventions focusing on inhibitory control processes may be effective in combating alcohol use risk in male adolescents but that both inhibitory and reward-related processes are likely of relevance to alcohol use behaviors in female adolescents. They further identify novel networks of alcohol use risk in youth, which may be used to identify adolescents who are at risk and inform intervention efforts.

THC, CBD, and Anxiety: A review of recent findings on the anxiolytic and anxiogenic effects of cannabis' primary cannabinoids.

Purpose of review: In the context of ongoing decriminalization and legalization of cannabis, a better understanding of how THC and CBD impact anxiety is critical to elucidate the risks of recreational cannabis use as well as to establish the therapeutic potential of cannabis products for anxiety-related applications. Recent findings: Recent literature supports anxiogenic effects of THC administration, which may be attenuated among regular cannabis users. Data regarding anxiolytic effects of CBD administration are mixed. Most newer studies contradict earlier findings in reporting no effects of CBD on anxiety in healthy participants, whereas inconsistent results have been reported among individuals with anxiety disorders, substance use disorders, and other clinical populations. Summary: Future research is needed to reconcile heterogenous findings, explore sex differences in the effects of THC and CBD on anxiety, as well as to assess how effects change with extended exposure, the impact of different CBD doses, and interactions between THC, CBD, and other cannabis compounds.

Systematic literature review of human studies assessing the efficacy of cannabidiol for social anxiety.

The current review evaluates the potential of cannabidiol (CBD) as a promising pharmacotherapy for social anxiety disorder (SAD). Although a number of evidence-based treatments for SAD are available, less than a third of affected individuals experience symptom remission after one year of treatment. Therefore, improved treatment options are urgently needed, and CBD is one candidate medication that may have certain benefits over current pharmacotherapies, including the absence of sedating side effects, reduced abuse liability, and rapid course of action. The current review provides a brief overview of CBD's mechanisms of action, neuroimaging in SAD, and evidence for CBD's effects on the neural substrates of SAD, as well as systematically reviewing literature directly examining the efficacy of CBD for improving social anxiety among healthy volunteers and individuals with SAD. In both populations, acute CBD administration significantly decreased anxiety without co-occurring sedation. A single study has also shown chronic administration to decrease social anxiety symptoms in individuals with SAD. Collectively, the current literature suggests CBD may be a promising treatment for SAD. However, further research is needed to establish optimal dosing, assess the timecourse of CBD's anxiolytic effects, evaluate long-term CBD administration, and explore sex differences in CBD for social anxiety.

Cannabis, connectivity, and coming of age: Associations between cannabis use and anterior cingulate cortex connectivity during the transition to adulthood.

Cannabis use is common among adolescents and emerging adults and is associated with significant adverse consequences for a subset of users. Rates of use peak between the ages of 18-25, yet the neurobiological consequences for neural systems that are actively developing during this time remain poorly understood. In particular, cannabis exposure may interfere with adaptive development of white matter pathways underlying connectivity of the anterior cingulate cortex, including the cingulum and anterior thalamic radiations (ATR). The current study examined the association between cannabis use during adolescence and emerging adulthood and white matter microstructure of the cingulum and ATR among 158 male subjects enrolled in the Pitt Mother and Child Project, a prospective, longitudinal study of risk and resilience among men of low socioeconomic status. Participants were recruited in infancy, completed follow-up assessments throughout childhood and adolescence, and underwent diffusion imaging at ages 20 and 22. At age 20, moderate cannabis use across adolescence (age 12-19) was associated with higher fractional anisotropy (FA) of the cingulum and ATR, relative to both minimal and heavy adolescent use. Longitudinally, moderate and heavy extended cannabis use (age 12-21) was associated with reduced positive change in FA in the cingulum from age 20 to 22, relative to minimal use. These longitudinal results suggest that cannabis exposure may delay cingulum maturation during the transition to adulthood and potentially impact individuals' functioning later in development.

A multidimensional approach to understanding the emergence of sex differences in internalizing symptoms in adolescence.

Women are more vulnerable to internalizing disorders (e.g., depression and anxiety). This study took an integrative developmental approach to investigate multidimensional factors associated with the emergence of sex differences in internalizing symptoms, using data from the Adolescent Brain Cognitive Development (ABCD) study. Indices of sex hormone levels (dehydroepiandrosterone, testosterone, and estradiol), physical pubertal development, task-based functional brain activity, family conflict, and internalizing symptoms were drawn from the ABCD study's baseline sample (9- to 10-year-old; N = 11,844). Principal component analysis served as a data-driven dimensionality reduction technique on the internalizing subscales to yield a single robust measure of internalizing symptoms. Moderated mediation analyses assessed whether associations between known risk factors and internalizing symptoms vary by sex. Results revealed direct and indirect effects of physical pubertal development on internalizing symptoms through family conflict across sexes. No effects were found of sex hormone levels or amygdala response to fearful faces on internalizing symptoms. Females did not report overall greater internalizing symptoms relative to males, suggesting that internalizing symptoms have not yet begun to increase in females at this age. Findings provide an essential baseline for future longitudinal research on the endocrine, neurocognitive, and psychosocial factors associated with sex differences in internalizing symptoms.

Identification and Validation of Distinct Latent Neurodevelopmental Profiles in the Adolescent Brain and Cognitive Development Study.

BACKGROUND: Regardless of the precise mechanism, all neurodevelopmental models of risk assume that, at the population level, there exist subgroups of individuals that share similar patterns of neural function and development-and that these subgroups somehow relate to psychiatric risk. However, the existence of multiple neurodevelopmental subgroups at the population level has not been assessed previously. METHODS: In the current study, cross-validated latent profile analysis was used to test for the presence of empirically derived, brain-based developmental subgroups using functional magnetic resonance imaging data from 6758 individuals (49.4% female; mean age = 9.94 years) in the Adolescent Brain and Cognitive Development (ABCD) study wave 1 release. Data were randomly split into training and testing samples. RESULTS: Analyses in the training sample (n = 3379) identified a seven-profile solution (entropy = 0.880) that was replicated in the held-out testing data (n = 3379, entropy = 0.890). Identified subgroups included a moderate group (66.8%), high reward (4.3%) and low reward (4.0%) groups, high inhibition (9.8%) and low inhibition (6.7%) groups, and high emotion regulation (4.0%) and low emotion regulation (4.3%) groups. Relative to the moderate group, other subgroups were characterized by more males (χ2 = 24.10, p = .0005), higher proportions of individuals from lower-income households (χ2 = 122.17, p < .0001), poorer cognitive performance (ps < .0001), more screen time (F = 6.80, p < .0001), heightened impulsivity (ps < .006), and higher rates of neurodevelopmental disorders (χ2 = 26.20, p = .0002). CONCLUSIONS: These data demonstrate the existence of multiple, distinct neurodevelopmental subgroups at the population level. They indicate that these empirically derived, brain-based developmental profiles relate to differences in clinical features, even at a young age, and prior to the peak period of risk for the development of psychopathology.

Effects of Smoking Status and State on Intrinsic Connectivity.

BACKGROUND: Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity. METHODS: Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution. RESULTS: Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent. CONCLUSIONS: These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

Systematic review of structural and functional neuroimaging studies of cannabis use in adolescence and emerging adulthood: evidence from 90 studies and 9441 participants.

Cannabis use peaks in adolescence, and adolescents may be more vulnerable to the neural effects of cannabis and cannabis-related harms due to ongoing brain development during this period. In light of ongoing cannabis policy changes, increased availability, reduced perceptions of harm, heightened interest in medicinal applications of cannabis, and drastic increases in cannabis potency, it is essential to establish an understanding of cannabis effects on the developing adolescent brain. This systematic review aims to: (1) synthesize extant literature on functional and structural neural alterations associated with cannabis use during adolescence and emerging adulthood; (2) identify gaps in the literature that critically impede our ability to accurately assess the effect of cannabis on adolescent brain function and development; and (3) provide recommendations for future research to bridge these gaps and elucidate the mechanisms underlying cannabis-related harms in adolescence and emerging adulthood, with the long-term goal of facilitating the development of improved prevention, early intervention, and treatment approaches targeting adolescent cannabis users (CU). Based on a systematic search of Medline and PsycInfo and other non-systematic sources, we identified 90 studies including 9441 adolescents and emerging adults (n = 3924 CU, n = 5517 non-CU), which provide preliminary evidence for functional and structural alterations in frontoparietal, frontolimbic, frontostriatal, and cerebellar regions among adolescent cannabis users. Larger, more rigorous studies are essential to reconcile divergent results, assess potential moderators of cannabis effects on the developing brain, disentangle risk factors for use from consequences of exposure, and elucidate the extent to which cannabis effects are reversible with abstinence. Guidelines for conducting this work are provided.

Mechanisms and Clinical Features of Co-occurring Opioid and Nicotine Use.

PURPOSE OF REVIEW: To review the literature addressing shared pathophysiological and clinical features of opioid and nicotine use to inform etiology and treatment, and highlight areas for future research. RECENT FINDINGS: Opioid and nicotine use co-occur at an alarmingly high rate, and this may be driven in part by interactions between the opioid and cholinergic systems underlying drug reward and the transition to dependence. Pain, among other shared risk factors, is strongly implicated in both opioid and nicotine use and appears to play an important role in their co-occurrence. Additionally, there are important sex/gender considerations that require further study. Regarding treatment, smoking cessation can improve treatment outcomes in opioid use disorder, and pharmacological approaches that target the opioid and cholinergic systems may be effective for treating both classes of substance use disorders. SUMMARY: Understanding overlapping etiological and pathophysiological mechanisms of opioid and nicotine use can aid in understanding their co-occurrence and guiding their treatment.

Nucleus accumbens functional connectivity at age 20 is associated with trajectory of adolescent cannabis use and predicts psychosocial functioning in young adulthood.

AIMS: (1) To identify trajectories of cannabis use across adolescence, (2) to measure the influence of cannabis use characteristics on functional connectivity of the nucleus accumbens (NAcc) and (3) to assess whether patterns of functional connectivity related to cannabis use are associated with psychosocial functioning 2 years later. DESIGN: The Pitt Mother and Child Project (PMCP) is a prospective, longitudinal study of male youth at high risk for psychopathology based on family income and gender. SETTING: Participants were recruited between age 6 and 17 months from the Women, Infants and Children Nutritional Supplement program (WIC) in the Pittsburgh, Pennsylvania area. PARTICIPANTS: A total of 158 PMCP young men contributed functional magnetic resonance imaging (fMRI) and substance use data at age 20 years. MEASUREMENTS: Latent class growth analysis was used to determine trajectories of cannabis use frequency from age 14 to 19 years. Psychophysiological interaction (PPI) analysis was used to measure functional connectivity between the NAcc and prefrontal cortex (PFC). Adolescent cannabis use trajectory, recent frequency of use and age of initiation were considered as developmental factors. We also tested whether functional connectivity was associated with depressive symptoms, anhedonia and educational attainment at age 22. FINDINGS: We identified three distinct trajectories of adolescent cannabis use, characterized by stable high, escalating or stable low use. The cannabis use trajectory group had a significant effect on NAcc functional connectivity to the medial PFC (F = 11.32, Z = 4.04, Pfamily-wise error-corrected (FWE-corr)  = 0.000). The escalating trajectory group displayed a pattern of negative NAcc-mPFC connectivity that was linked to higher levels of depressive symptoms (r = -0.17, P < .05), anhedonia (r = -0.19, P < .05) and lower educational attainment (t = -2.77, P < .01) at age 22. CONCLUSIONS: Pattern of cannabis use frequency across adolescence in US youth could have consequences for mood symptoms and educational attainment in early adulthood via altered function in neural reward circuitry.

Adolescent brain development and depression: A case for the importance of connectivity of the anterior cingulate cortex.

We propose that structural and functional connectivity of the anterior cingulate cortex (ACC) represents a critical component of adolescent developmental psychopathology. We hypothesize that connectivity of the ACC, a hub for integrating cognitive, affective, and social information to guide self-regulation across domains, supports adaptive development of self-regulation during adolescence and that, conversely, disrupted maturation of ACC connectivity contributes to the development of depression. To integrate findings on typical development, we report results of a meta-analysis of diffusion imaging findings of typical adolescent development of the cingulum and anterior thalamic radiations, the tracts most relevant to ACC connectivity, and provide a critical review of the literature on ACC functional connectivity. Finally, we review the evidence for altered structural and functional connectivity in adolescents with depression. Although the evidence for our claim is persuasive, a more comprehensive understanding of the ACC's role depends upon future investigations with sophisticated modeling of networks, prospective and longitudinal designs, and examination of structure-function associations.

Diffusion Capillary Phantom vs. Human Data: Outcomes for Reconstruction Methods Depend on Evaluation Medium.

PURPOSE: Diffusion MRI provides a non-invasive way of estimating structural connectivity in the brain. Many studies have used diffusion phantoms as benchmarks to assess the performance of different tractography reconstruction algorithms and assumed that the results can be applied to in vivo studies. Here we examined whether quality metrics derived from a common, publically available, diffusion phantom can reliably predict tractography performance in human white matter tissue. MATERIALS AND METHODS: We compared estimates of fiber length and fiber crossing among a simple tensor model (diffusion tensor imaging), a more complicated model (ball-and-sticks) and model-free (diffusion spectrum imaging, generalized q-sampling imaging) reconstruction methods using a capillary phantom and in vivo human data (N = 14). RESULTS: Our analysis showed that evaluation outcomes differ depending on whether they were obtained from phantom or human data. Specifically, the diffusion phantom favored a more complicated model over a simple tensor model or model-free methods for resolving crossing fibers. On the other hand, the human studies showed the opposite pattern of results, with the model-free methods being more advantageous than model-based methods or simple tensor models. This performance difference was consistent across several metrics, including estimating fiber length and resolving fiber crossings in established white matter pathways. CONCLUSIONS: These findings indicate that the construction of current capillary diffusion phantoms tends to favor complicated reconstruction models over a simple tensor model or model-free methods, whereas the in vivo data tends to produce opposite results. This brings into question the previous phantom-based evaluation approaches and suggests that a more realistic phantom or simulation is necessary to accurately predict the relative performance of different tractography reconstruction methods.

Maladaptive decision making and substance use outcomes in high-risk individuals: preliminary evidence for the role of 5-HTTLPR variation.

OBJECTIVE: Individuals with multiple alcohol-dependent (AD) relatives are at increased risk for substance use disorders (SUDs). Prospective, longitudinal studies of high-risk (HR) individuals afford the opportunity to determine potential risk markers of SUDs. The current study assessed the effect of familial risk and genetic variation on Iowa Gambling Task (IGT) performance and tested for an association between IGT performance and SUD outcomes. METHOD: Individuals from multiplex AD families (n = 63) and low-risk (LR; n = 45) control families, ages 16-34 years, were tested using a computerized version of the IGT. SUD outcomes were assessed at approximately yearly intervals. 5-HTTLPR and COMT genotypes were available for the majority of participants (n = 86). RESULTS: HR offspring showed poorer performance overall on the IGT and especially poor performance on the final trial block (Block 5), indicating a failure to improve decision making with previous experience. The 5-HTTLPR short-allele homozygote participants performed worse than long-allele carriers, with HR S/S carriers exhibiting particularly poor performance. There was no main effect of COMT on IGT performance and no significant COMT by Risk interaction. Significantly more individuals in the HR than LR group met criteria for SUD. Importantly, disadvantageous performance on IGT Block 5 was significantly associated with an earlier age at SUD onset. CONCLUSIONS: This is the first study to show that both familial risk of SUD and 5-HTTLPR variation impact performance on the IGT. Poorer IGT performance was associated with earlier onset of SUD, suggesting that HR individuals who fail to appropriately attend to long-term costs and benefits during a decision-making task are especially at risk for developing SUD in adolescence and young adulthood.

Familial risk for alcohol dependence and developmental changes in BMI: the moderating influence of addiction and obesity genes.

AIM: Familial loading for alcohol dependence (AD) and variation in genes reported to be associated with AD or BMI were tested in a longitudinal study. MATERIALS & METHODS: Growth curve analyses of BMI data collected at approximately yearly intervals and obesity status (BMI > 30) were examined. RESULTS: High-risk males were found to have higher BMI than low-risk males, beginning at age 15 years (2.0 kg/m(2) difference; p = 0.046), persisting through age 19 years (3.3 kg/m(2) difference; p = 0.005). CHRM2 genotypic variance predicted longitudinal BMI and obesity status. Interactions with risk status and sex were also observed for DRD2 and FTO gene variation. CONCLUSION: Variation at loci implicated in addiction may be influential in determining susceptibility to increased BMI in childhood and adolescence.