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Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and long-term stability of individual differences in task-fMRI measures using fMRI measures of brain activation provided by the adolescent brain cognitive development (ABCD) Study Release v4.0 as an individual's average regional activity, using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability (quantified as the ratio of non-scanner related stable variance to all variances) was poor in virtually all brain regions, with an average value of 0.088 and 0.072 for short term (within-session) reliability and long-term (between-session) stability, respectively, in regions of interest (ROIs) historically-recruited by the tasks. Only one reliability or stability value in ROIs exceeded the 'poor' cut-off of 0.4, and in fact rarely exceeded 0.2 (only 4.9%). Motion had a pronounced effect on estimated reliability/stability, with the lowest motion quartile of participants having a mean reliability/stability 2.5 times higher (albeit still 'poor') than the highest motion quartile. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue urgently needs to be addressed through optimization of task design, scanning parameters, data acquisition protocols, preprocessing pipelines, and data denoising methods.

Temporal stability of individual differences is an important prerequisite for accurate tracking of prospective relationships between neurocognition and real-world behavioral outcomes such as substance abuse and psychopathology. Here we report age-related changes and longitudinal test-retest stability (TRS) for the Neurocognition battery of the Adolescent Brain and Cognitive Development (ABCD) study, which included the NIH Toolbox (TB) Cognitive Domain and additional memory and visuospatial processing tests administered at baseline (ages 9-11) and two-year follow-up. As expected, performance improved significantly with age, but the effect size varied broadly, with Pattern Comparison and the Crystallized Cognition Composite showing the largest age-related gain (Cohen's d:.99 and.97, respectively). TRS ranged from fair (Flanker test: r = 0.44) to excellent (Crystallized Cognition Composite: r = 0.82). A comparison of longitudinal changes and cross-sectional age-related differences within baseline and follow-up assessments suggested that, for some measures, longitudinal changes may be confounded by practice effects and differences in task stimuli or procedure between baseline and follow-up. In conclusion, a subset of measures showed good stability of individual differences despite significant age-related changes, warranting their use as prospective predictors. However, caution is needed in the interpretation of observed longitudinal changes as indicators of neurocognitive development.

Cue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies of substance use disorders (SUDs). Although there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD treatments, the interpretability and reproducibility of these studies is limited by incomplete reporting of participants' characteristics, task design, craving assessment, scanning preparation and analysis decisions in fMRI drug cue reactivity (FDCR) experiments. This hampers clinical translation, not least because systematic review and meta-analysis of published work are difficult. This consensus paper and Delphi study aims to outline the important methodological aspects of FDCR research, present structured recommendations for more comprehensive methods reporting and review the FDCR literature to assess the reporting of items that are deemed important. Forty-five FDCR scientists from around the world participated in this study. First, an initial checklist of items deemed important in FDCR studies was developed by several members of the Enhanced NeuroImaging Genetics through Meta-Analyses (ENIGMA) Addiction working group on the basis of a systematic review. Using a modified Delphi consensus method, all experts were asked to comment on, revise or add items to the initial checklist, and then to rate the importance of each item in subsequent rounds. The reporting status of the items in the final checklist was investigated in 108 recently published FDCR studies identified through a systematic review. By the final round, 38 items reached the consensus threshold and were classified under seven major categories: 'Participants' Characteristics', 'General fMRI Information', 'General Task Information', 'Cue Information', 'Craving Assessment Inside Scanner', 'Craving Assessment Outside Scanner' and 'Pre- and Post-Scanning Considerations'. The review of the 108 FDCR papers revealed significant gaps in the reporting of the items considered important by the experts. For instance, whereas items in the 'General fMRI Information' category were reported in 90.5% of the reviewed papers, items in the 'Pre- and Post-Scanning Considerations' category were reported by only 44.7% of reviewed FDCR studies. Considering the notable and sometimes unexpected gaps in the reporting of items deemed to be important by experts in any FDCR study, the protocols could benefit from the adoption of reporting standards. This checklist, a living document to be updated as the field and its methods advance, can help improve experimental design, reporting and the widespread understanding of the FDCR protocols. This checklist can also provide a sample for developing consensus statements for protocols in other areas of task-based fMRI.

Individuals with opioid use disorder (OUD) often relapse when exposed to opioid-related cues. Previous functional magnetic resonance imaging (fMRI) studies have identified neuronal corticolimbic changes related to drug cue reactivity in OUD. However, the corresponding manner in which brain regions interact is still unclear. Effective (directional) connectivity was analyzed using dynamic causal modeling of fMRI data acquired from 27 OUD participants (13 with OUD and 14 with OUD and cocaine use disorder [OUD+CUD]), while performing an opioid-word Stroop task. Participants were shown opioid and neutral words presented in different colors and were instructed to indicate word color but ignore word meaning. The effects of opioid words relative to neutral words on effective connectivity and on behavioral reaction time were defined as modulatory change and attentional bias, respectively. For all the 27 participants, left anterior cingulate cortex (ACC) to right hippocampus effective connectivity exhibited the largest modulatory change, which was positively correlated with attentional bias. The findings for the ACC to hippocampus EC were consistent across OUD and CUD found in a previous study.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

The Adolescent Brain Cognitive Development (ABCD) study is poised to be the largest single-cohort long-term longitudinal study of neurodevelopment and child health in the United States. Baseline data on N= 4521 children aged 9-10 were released for public access on November 2, 2018. In this paper we performed principal component analyses of the neurocognitive assessments administered to the baseline sample. The neurocognitive battery included seven measures from the NIH Toolbox as well as five other tasks. We implemented a Bayesian Probabilistic Principal Components Analysis (BPPCA) model that incorporated nesting of subjects within families and within data collection sites. We extracted varimax-rotated component scores from a three-component model and associated these scores with parent-rated Child Behavior Checklist (CBCL) internalizing, externalizing, and stress reactivity. We found evidence for three broad components that encompass general cognitive ability, executive function, and learning/memory. These were significantly associated with CBCL scores in a differential manner but with small effect sizes. These findings set the stage for longitudinal analysis of neurocognitive and psychopathological data from the ABCD cohort as they age into the period of maximal adolescent risk-taking.

The ABCD study is recruiting and following the brain development and health of over 10,000 9-10 year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature.

Children diagnosed with attention-deficit/hyperactivity disorder (ADHD) are at increased risk for substance abuse. Response inhibition is a hallmark of ADHD, yet the combined effects of ADHD and regular substance use on neural networks associated with response inhibition are unknown. Task-based functional Magnetic Resonance Imaging (fMRI) data from young adults with childhood ADHD with (n = 25) and without (n = 25) cannabis use ≥ monthly in the past year were compared with a local normative comparison group (LNCG) with (n = 11) and without (n = 12) cannabis use. Go/NoGo behavioral and fMRI data were evaluated for main and interaction effects of ADHD diagnosis and cannabis use. ADHD participants made significantly more commission errors on NoGo trials than controls. ADHD participants also had less frontoparietal and frontostriatal activity, independent of cannabis use. No main effects of cannabis use on response inhibition or functional brain activation were observed. An interaction of ADHD diagnosis and cannabis use was found in the right hippocampus and cerebellar vermis, with increased recruitment of these regions in cannabis-using controls during correct response inhibition. ADHD participants had impaired response inhibition combined with less fronto-parietal/striatal activity, regardless of cannabis use history. Cannabis use did not impact behavioral response inhibition. Cannabis use was associated with hippocampal and cerebellar activation, areas rich in cannabinoid receptors, in LNCG but not ADHD participants. This may reflect recruitment of compensatory circuitry in cannabis using controls but not ADHD participants. Future studies targeting hippocampal and cerebellar-dependent function in these groups may provide further insight into how this circuitry is altered by ADHD and cannabis use.

BackgroundBoth Attention Deficit Hyperactivity Disorder (ADHD) and chronic cannabis (CAN) use have been associated with brain structural abnormalities, although little is known about the effects of both in young adults.MethodsParticipants included: those with a childhood diagnosis of ADHD who were CAN users (ADHD_CAN; n=37) and non-users (NU) (ADHD_NU; n=44) and a local normative comparison group (LNCG) who did (LNCG_CAN; n=18) and did not (LNCG_NU; n=21) use CAN regularly. Multiple regressions and MANCOVAs were used to examine the independent and interactive effects of a childhood ADHD diagnosis and CAN group status and age of onset (CUO) on subcortical volumes and cortical thickness.ResultsAfter controlling for age, gender, total brain volume, nicotine use, and past-year binge drinking, childhood ADHD diagnosis did not predict brain structure; however, persistence of ADHD was associated with smaller left precentral/postcentral cortical thickness. Compared to all non-users, CAN users had decreased cortical thickness in right hemisphere superior frontal sulcus, anterior cingulate, and isthmus of cingulate gyrus regions and left hemisphere superior frontal sulcus and precentral gyrus regions. Early cannabis use age of onset (CUO) in those with ADHD predicted greater right hemisphere superior frontal and postcentral cortical thickness.DiscussionYoung adults with persistent ADHD demonstrated brain structure abnormalities in regions underlying motor control, working memory and inhibitory control. Further, CAN use was linked with abnormal brain structure in regions with high concentrations of cannabinoid receptors. Additional large-scale longitudinal studies are needed to clarify how substance use impacts neurodevelopment in youth with and without ADHD.

Objectives: Insomnia symptoms are negatively related to opioid use disorder (OUD) treatment outcomes, possibly reflecting the influence of sleep on neurofunctional domains implicated in addiction. Moreover, the intersection between OUD recovery and sleep represents an area well-suited for the development of novel, personalized treatment strategies. This study assessed the prevalence of clinically significant insomnia symptoms and characterized its neurofunctional correlates among a clinical sample of adults with OUD receiving buprenorphine. Methods: Adults (N = 129) receiving buprenorphine for OUD from an outpatient clinic participated in a cross-sectional survey. Participants completed an abbreviated version of NIDA's Phenotyping Assessment Battery, which assessed 6 neurofunctional domains: sleep, negative emotionality, metacognition, interoception, cognition, and reward. Bivariate descriptive statistics compared those with evidence of clinically significant insomnia symptoms (Insomnia Severity Index [ISI] score of ≥11) to those with minimal evidence of clinically significant insomnia symptoms (ISI score of ≤10) across each of the neurofunctional domains. Results: Roughly 60% of participants reported clinically significant insomnia symptoms (ISI score of ≥11). Experiencing clinically significant insomnia symptoms was associated with reporting greater levels of depression, anxiety, post-traumatic stress, stress intolerance, unhelpful metacognition, and interoceptive awareness (ps<0.05). Participants with evidence of clinically significant insomnia were more likely to report that poor sleep was interfering with their OUD treatment and that improved sleep would assist with their treatment (ps<0.05). Conclusions: Insomnia was prevalent among adults receiving buprenorphine for OUD. Insomnia was associated with neurofunctional performance, which may impact OUD treatment trajectories. Our findings indicate potential targets in the development of personalized treatment plans for patients with co-morbid insomnia and OUD. To inform the development of novel treatment strategies, more research is needed to understand the potential mechanistic links between sleep disturbances and substance use. [ABSTRACT FROM AUTHOR]

Key Points: Question: What is the current status of functional magnetic resonance imaging drug cue reactivity (FDCR) research, and how could it support the discovery of biomarkers to facilitate intervention development and clinical care for substance use disorders? Findings: In this systematic review including 415 FDCR studies, results from 357 studies could potentially help develop diagnostic, prognostic, susceptibility, severity, monitoring, predictive, or response biomarkers. Substantial heterogeneity in task and study design was identified that can hinder biomarker development. Meaning: A sizable literature supports the development of FDCR-derived biomarkers, but moving forward requires large-scale collaboration, methodological harmonization and optimization, and clinical and analytical validation. This systematic review summarizes the state of the field of functional magnetic resonance imaging (fMRI) drug cue reactivity, assesses their potential for biomarker development, and outlines a clear process for biomarker qualification to guide future research and validation efforts Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments. [ABSTRACT FROM AUTHOR]

Background and objectives Use of psychotropic substances in childhood has been associated with both impulsivity and other manifestations of poor executive function as well as escalation over time to use of progressively stronger substances. However, how this relationship may start in earlier childhood has not been well explored. Here, we investigated the neurobehavioral correlates of daily caffeinated soda consumption in preadolescent children and examined whether caffeinated soda intake is associated with a higher risk of subsequent alcohol initiation. Methods Using Adolescent Brain Cognitive Development study data (N = 2,092), we first investigated cross-sectional relationships between frequent caffeinated soda intake and well-known risk factors of substance misuse: impaired working memory, high impulsivity, and aberrant reward processing. We then examined whether caffeinated soda intake at baseline predicts more alcohol sipping at 12 months follow-up using a machine learning algorithm. Results Daily consumption of caffeinated soda was cross-sectionally associated with neurobehavioral risk factors for substance misuse such as higher impulsivity scores and lower working memory performance. Furthermore, caffeinated soda intake predicted a 2.04 times greater likelihood of alcohol sipping after 12 months, even after controlling for rates of baseline alcohol sipping rates. Conclusions These findings suggest that previous linkages between caffeine and substance use in adolescence also extend to younger initiation, and may stem from core neurocognitive features thought conducive to substance initiation. [ABSTRACT FROM AUTHOR]