Publications by authors named "Sarah Lichenstein"

Increases in impulsivity and negative affect (e.g., neuroticism) are common during adolescence and are both associated with risk for alcohol-use initiation and other risk behaviors.

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Impulsivity is a multifaceted construct that typically increases during adolescence and is implicated in risk for substance use disorders that develop later in life. Here, we take a multivariate approach to identify latent dimensions of impulsivity, broadly defined, among youth enrolled in the Adolescent Brain and Cognitive Development (ABCD) study and explore associations with individual differences in demographics, substance-use initiation and canonical resting state networks (N=11,872, ages ~9-10). Using principal component analysis, we identified eight latent impulsivity dimensions, the top three of which together accounted for the majority of the variance across all impulsivity assessments.

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Background: Cannabis use is common, particularly during emerging adulthood when brain development is ongoing, and its use is associated with harmful outcomes for a subset of people. An improved understanding of the neural mechanisms underlying risk for problem-level use is critical to facilitate the development of more effective prevention and treatment approaches.

Methods: In the current study, we applied a whole-brain, data-driven, machine learning approach to identify neural features predictive of problem-level cannabis use in a nonclinical sample of college students (n = 191, 58% female) based on reward task functional connectivity data.

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Neural variability, or variation in brain signals, facilitates dynamic brain responses to ongoing demands. This flexibility is important during development from childhood to young adulthood, a period characterized by rapid changes in experience. However, little is known about how variability in the engagement of recurring brain states changes during development.

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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.

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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.

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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.

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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.

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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.

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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).

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Neurodevelopmental research has traditionally focused on development of individual structures, yet multiple lines of evidence indicate parallel development of large-scale systems, including canonical neural networks (i.e., default mode, frontoparietal).

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The brain functional connectome, the collection of interconnected neural circuits along functional networks, facilitates a cutting-edge understanding of brain functioning, and has a potential to play a mediating role within the effect pathway between an exposure and an outcome. While existing mediation analytic approaches are capable of providing insight into complex processes, they mainly focus on a univariate mediator or mediator vector, without considering network-variate mediators. To fill the methodological gap and accomplish this exciting and urgent application, in the article, we propose an integrative mediation analysis under a Bayesian paradigm with networks entailing the mediation effect.

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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.

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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.

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Article Synopsis
  • - Cannabis use is most common in adolescence, which poses risks due to ongoing brain development, leading to questions about the effects of cannabis on youth.
  • - The review examines existing studies on changes in brain structure and function for adolescents using cannabis, while also identifying research gaps and suggesting future study directions.
  • - A total of 90 studies involving over 9,400 participants were analyzed, highlighting significant brain changes in cannabis users, but more extensive and rigorous research is needed to clarify these findings and their long-term implications.
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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.

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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.

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Current models of addiction biology highlight altered neural responses to non-drug rewards as a central feature of addiction. However, given that drugs of abuse can directly impact reward-related dopamine circuitry, it is difficult to determine the extent to which reward processing alterations are a trait feature of individuals with addictions, or primarily a consequence of exogenous drug exposure. Examining individuals with behavioral addictions is one promising approach for disentangling neural features of addiction from the direct effects of substance exposure.

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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.

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Purpose Of Review: This review provides an overview of the neurobiological mechanisms underlying opioid use disorder (OUD) drawing from genetic, functional and structural magnetic resonance imaging (MRI) research.

Recent Findings: Preliminary evidence suggests an association between OUD and specific variants of the DRD2, δ-opioid receptor 1 (OPRD1) and μ-opioid receptor 1 (OPRM1) genes. Additionally, MRI research indicates functional and structural alterations in striatal and corticolimbic brain regions and pathways underlying reward, emotion/stress and cognitive control processes among individuals with OUD.

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Article Synopsis
  • The review explores the common biological and clinical characteristics of opioid and nicotine use to improve treatment and identify areas for future research.
  • High rates of co-use are linked to interactions between opioid and cholinergic systems, with pain and other risk factors playing significant roles in this relationship.
  • Smoking cessation may enhance treatment outcomes for opioid use disorder, and targeted pharmacological approaches could be beneficial for addressing both substance use disorders simultaneously.
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The current opioid epidemic is an urgent public health problem, with enormous individual, societal, and healthcare costs. Despite effective, evidence-based treatments, there is significant individual variability in treatment responses and relapse rates are high. In addition, the neurobiology of opioid-use disorder (OUD) and its treatment is not well understood.

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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.

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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.

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