Specialization of amygdala subregions in emotion processing.

The amygdala is important for human fear processing. However, recent research has failed to reveal specificity, with evidence that the amygdala also responds to other emotions. A more nuanced understanding of the amygdala's role in emotion processing, particularly relating to fear, is needed given the importance of effective emotional functioning for everyday function and mental health. We studied 86 healthy participants (44 females), aged 18-49 (mean 26.12 ± 6.6) years, who underwent multiband functional magnetic resonance imaging. We specifically examined the reactivity of four amygdala subregions (using regions of interest analysis) and related brain connectivity networks (using generalized psycho-physiological interaction) to fear, angry, and happy facial stimuli using an emotional face-matching task. All amygdala subregions responded to all stimuli (p-FDR < .05), with this reactivity strongly driven by the superficial and centromedial amygdala (p-FDR < .001). Yet amygdala subregions selectively showed strong functional connectivity with other occipitotemporal and inferior frontal brain regions with particular sensitivity to fear recognition and strongly driven by the basolateral amygdala (p-FDR < .05). These findings suggest that amygdala specialization to fear may not be reflected in its local activity but in its connectivity with other brain regions within a specific face-processing network.

Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study.

Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.

The prevalence of cannabis use disorders in people who use medicinal cannabis: A systematic review and meta-analysis.

BACKGROUND: The prevalence of cannabis use disorders (CUDs) in people who use cannabis recreationally has been estimated at 22%, yet there is a dearth of literature exploring CUDs among people who use medicinal cannabis. We aimed to systematically review the prevalence of CUDs in people who use medicinal cannabis. METHODS: In our systematic review and meta-analysis, we followed PRISMA guidelines and searched three databases (PsychInfo, Embase and PubMed) to identify studies examining the prevalence of CUDs in people who use medicinal cannabis. Meta-analyses were calculated on the prevalence of CUDs. Prevalence estimates were pooled across different prevalence periods using the DSM-IV and DSM-5. RESULTS: We conducted a systematic review of 14 eligible publications, assessing the prevalence of CUDs, providing data for 3681 participants from five different countries. The systematic review demonstrated that demographic factors, mental health disorders and the management of chronic pain with medicinal cannabis were associated with an elevated risk of CUDs. Meta-analyses were conducted on the prevalence of CUDs. For individuals using medicinal cannabis in the past 6-12 months, the prevalence of CUDs was 29% (95% CI: 21-38%) as per DSM-5 criteria. Similar prevalence was observed using DSM-IV (24%, CI: 14-38%) for the same period. When including all prevalence periods and using the DSM-5, the prevalence of CUDs in people who use medicinal cannabis was estimated at 25% (CI: 18-33%). CONCLUSIONS: The prevalence of CUDs in people who use medicinal cannabis is substantial and comparable to people who use cannabis for recreational reasons, emphasizing the need for ongoing research to monitor the prevalence of CUDs in people who use medicinal cannabis.

A phase III multisite randomised controlled trial to compare the efficacy of cannabidiol to placebo in the treatment of cannabis use disorder: the CBD-CUD study protocol.

BACKGROUND: Cannabis use disorder (CUD) is increasingly common and contributes to a range of health and social problems. Cannabidiol (CBD) is a non-intoxicating cannabinoid recognised for its anticonvulsant, anxiolytic and antipsychotic effects with no habit-forming qualities. Results from a Phase IIa randomised clinical trial suggest that treatment with CBD for four weeks reduced non-prescribed cannabis use in people with CUD. This study examines the efficacy, safety and quality of life of longer-term CBD treatment for patients with moderate-to-severe CUD. METHODS/DESIGN: A phase III multi-site, randomised, double-blinded, placebo controlled parallel design of a 12-week course of CBD to placebo, with follow-up at 24 weeks after enrolment. Two hundred and fifty adults with moderate-to-severe CUD (target 20% Aboriginal), with no significant medical, psychiatric or other substance use disorders from seven drug and alcohol clinics across NSW and VIC, Australia will be enrolled. Participants will be administered a daily dose of either 4 mL (100 mg/mL) of CBD or a placebo dispensed every 3-weeks. All participants will receive four-sessions of Cognitive Behavioural Therapy (CBT) based counselling. Primary endpoints are self-reported cannabis use days and analysis of cannabis metabolites in urine. Secondary endpoints include severity of CUD, withdrawal severity, cravings, quantity of use, motivation to stop and abstinence, medication safety, quality of life, physical/mental health, cognitive functioning, and patient treatment satisfaction. Qualitative research interviews will be conducted with Aboriginal participants to explore their perspectives on treatment. DISCUSSION: Current psychosocial and behavioural treatments for CUD indicate that over 80% of patients relapse within 1-6 months of treatment. Pharmacological treatments are highly effective with other substance use disorders but there are no approved pharmacological treatments for CUD. CBD is a promising candidate for CUD treatment due to its potential efficacy for this indication and excellent safety profile. The anxiolytic, antipsychotic and neuroprotective effects of CBD may have added benefits by reducing many of the mental health and cognitive impairments reported in people with regular cannabis use. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry: ACTRN12623000526673 (Registered 19 May 2023).

Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability.

Visibility graphs provide a novel approach for analysing time-series data. Graph theoretical analysis of visibility graphs can provide new features for data mining applications in fMRI. However, visibility graphs features have not been used widely in the field of neuroscience. This is likely due to a lack of understanding of their robustness in the presence of noise (e.g., motion) and their test-retest reliability. In this study, we investigated visibility graph properties of fMRI data in the human connectome project (N = 1010) and tested their sensitivity to motion and test-retest reliability. We also characterised the strength of connectivity obtained using degree synchrony of visibility graphs. We found that strong correlation (r > 0.5) between visibility graph properties, such as the number of communities and average degrees, and motion in the fMRI data. The test-retest reliability (Intraclass correlation coefficient (ICC)) of graph theoretical features was high for the average degrees (0.74, 95% CI = [0.73, 0.75]), and moderate for clustering coefficient (0.43, 95% CI = [0.41, 0.44]) and average path length (0.41, 95% CI = [0.38, 0.44]). Functional connectivity between brain regions was measured by correlating the visibility graph degrees. However, the strength of correlation was found to be moderate to low (r < 0.35). These findings suggest that even small movement in fMRI data can strongly influence robustness and reliability of visibility graph features, thus, requiring robust motion correction strategies prior to data analysis. Further studies are necessary for better understanding of the potential application of visibility graph features in fMRI.

How much cannabis is used in a joint in Australia? An experimental investigation into use by potency and frequency.

INTRODUCTION: Cannabis use is highly prevalent in Australia, yet current survey metrics measure tetrahydrocannabinol (THC) exposure with limited accuracy. Often survey items measure cannabis quantity by assuming specific modes of use (i.e., 'how many joints do you use?'), which fail to capture variations in cannabis use and the diverse modes of use (e.g., joints, cones, spliffs). This study investigated how much cannabis is used in these modes of administration in an Australian sample. METHODS: Participants (N = 31, Mage = 25.77; 51% university students) completed the Roll a Joint Paradigm in which they rolled joints, spliffs and packed cones as they would typically, using oregano as 'cannabis.' Participants then prepared each again but with cannabis of higher or lower potency. RESULTS: The amount of cannabis used across different modes of administration was variable: joints (range 0.10-1.25 g), spliffs (range 0.12-1.21 g) and cones (range 0.03-0.41 g). Participants who used cannabis daily rolled three times the amount of cannabis into a joint. DISCUSSION AND CONCLUSIONS: The amount of cannabis used in common modes of administration may be highly variable. Daily use may be associated using larger quantities of cannabis. Titration attempts based on potency were not proportional or consistent across modes of administration. The results indicate people may adjust the quantity of cannabis based on perceived potency, however, not proportional to THC concentration. Inconsistency in the amount of cannabis used based on potency and within different modes of administration may represent a problem for self-report metrics which ask participants to report cannabis use in joints.

Enhanced cannabis timeline followback (EC-TLFB): Comprehensive assessment of cannabis use including standard THC units and validation through biological measures.

AIMS: The aims of this study were to present an enhanced cannabis timeline followback (EC-TLFB) enabling comprehensive assessment of cannabis use measures, including standard tetrahydrocannabinol (THC) units, and to validate these against objectively indexed urinary 11-nor-9-carboxy-tetrahydrocannabinol (THC-COOH) concentrations. DESIGN: We used cross-sectional baseline data from the 'CannTeen' observational longitudinal study. SETTING: The study was conducted in London, UK. PARTICIPANTS: A total of 147 participants who used cannabis regularly took part in the study (n = 71 female, n = 76 male; mean age = 21.90, standard deviation = 5.32). MEASUREMENTS: The EC-TLFB was used to calculate frequency of cannabis use, method of administration, including co-administration with tobacco, amount of cannabis used (measured with unaided self-report and also using pictorial aided self-report) and type of cannabis product (flower, hash) which was used to estimate THC concentration (both from published data on THC concentration of products and analysis of cannabis samples donated by participants in this study). We calculated total weekly standard THC units (i.e. 5 mg THC for all cannabis products and methods of administration) using the EC-TLFB. The outcome variable for validation of past week EC-TLFB assessments was creatinine-normalized carboxy-tetrahydrocannabinol (THC-COOH) in urine. FINDINGS: All measures of cannabis exposure included in this analysis were positively correlated with levels of THC-COOH in urine (r = 0.41-0.52). Standard THC units, calculated with average concentrations of THC in cannabis in the UK and unaided self-report measures of amount of cannabis used in grams showed the strongest correlation with THC-COOH in urine (r = 0.52, 95% bias-corrected and accelerated = 0.26-0.70). CONCLUSIONS: The enhanced cannabis timeline followback (EC-TLFB) can provide a valid assessment of a comprehensive set of cannabis use measures including standard tetrahydrocannabinol units as well as and traditional TLFB assessments (e.g. frequency of use and grams of cannabis use).

Meditation attenuates default-mode activity: A pilot study using ultra-high field 7 Tesla MRI.

OBJECTIVES: Mapping the neurobiology of meditation has been bolstered by functional MRI (fMRI) research, with advancements in ultra-high field 7 Tesla fMRI further enhancing signal quality and neuroanatomical resolution. Here, we utilize 7 Tesla fMRI to examine the neural substrates of meditation and replicate existing widespread findings, after accounting for relevant physiological confounds. METHODS: In this feasibility study, we scanned 10 beginner meditators (N = 10) while they either attended to breathing (focused attention meditation) or engaged in restful thinking (non-focused rest). We also measured and adjusted the fMRI signal for key physiological differences between meditation and rest. Finally, we explored changes in state mindfulness, state anxiety and focused attention attributes for up to 2 weeks following the single fMRI meditation session. RESULTS: Group-level task fMRI analyses revealed significant reductions in activity during meditation relative to rest in default-mode network hubs, i.e., antero-medial prefrontal and posterior cingulate cortices, precuneus, as well as visual and thalamic regions. These findings survived stringent statistical corrections for fluctuations in physiological responses which demonstrated significant differences (p < 0.05/n, Bonferroni controlled) between meditation and rest. Compared to baseline, State Mindfulness Scale (SMS) scores were significantly elevated (F(3,9) = 8.16, p < 0.05/n, Bonferroni controlled) following the fMRI meditation session, and were closely maintained at 2-week follow up. CONCLUSIONS: This pilot study establishes the feasibility and utility of investigating focused attention meditation using ultra-high field (7 Tesla) fMRI, by supporting widespread evidence that focused attention meditation attenuates default-mode activity responsible for self-referential processing. Future functional neuroimaging studies of meditation should control for physiological confounds and include behavioural assessments.

Daily Cannabidiol Administration for 10 Weeks Modulates Hippocampal and Amygdalar Resting-State Functional Connectivity in Cannabis Users: A Functional Magnetic Resonance Imaging Open-Label Clinical Trial.

Introduction: Cannabis use is associated with brain functional changes in regions implicated in prominent neuroscientific theories of addiction. Emerging evidence suggests that cannabidiol (CBD) is neuroprotective and may reverse structural brain changes associated with prolonged heavy cannabis use. In this study, we examine how an ∼10-week exposure of CBD in cannabis users affected resting-state functional connectivity in brain regions functionally altered by cannabis use. Materials and Methods: Eighteen people who use cannabis took part in a ∼10 weeks open-label pragmatic trial of self-administered daily 200 mg CBD in capsules. They were not required to change their cannabis exposure patterns. Participants were assessed at baseline and post-CBD exposure with structural magnetic resonance imaging (MRI) and a functional MRI resting-state task (eyes closed). Seed-based connectivity analyses were run to examine changes in the functional connectivity of a priori regions-the hippocampus and the amygdala. We explored if connectivity changes were associated with cannabinoid exposure (i.e., cumulative cannabis dosage over trial, and plasma CBD concentrations and Δ9-tetrahydrocannabinol (THC) plasma metabolites postexposure), and mental health (i.e., severity of anxiety, depression, and positive psychotic symptom scores), accounting for cigarette exposure in the past month, alcohol standard drinks in the past month and cumulative CBD dose during the trial. Results: Functional connectivity significantly decreased pre-to-post the CBD trial between the anterior hippocampus and precentral gyrus, with a strong effect size (d=1.73). Functional connectivity increased between the amygdala and the lingual gyrus pre-to-post the CBD trial, with a strong effect size (d=1.19). There were no correlations with cannabinoids or mental health symptom scores. Discussion: Prolonged CBD exposure may restore/reduce functional connectivity differences reported in cannabis users. These new findings warrant replication in a larger sample, using robust methodologies-double-blind and placebo-controlled-and in the most vulnerable people who use cannabis, including those with more severe forms of Cannabis Use Disorder and experiencing worse mental health outcomes (e.g., psychosis, depression).

Measuring white matter microstructure in 1,457 cannabis users and 1,441 controls: A systematic review of diffusion-weighted MRI studies.

Introduction: Cannabis is the most widely used regulated substance by youth and adults. Cannabis use has been associated with psychosocial problems, which have been partly ascribed to neurobiological changes. Emerging evidence to date from diffusion-MRI studies shows that cannabis users compared to controls show poorer integrity of white matter fibre tracts, which structurally connect distinct brain regions to facilitate neural communication. However, the most recent evidence from diffusion-MRI studies thus far has yet to be integrated. Therefore, it is unclear if white matter differences in cannabis users are evident consistently in selected locations, in specific diffusion-MRI metrics, and whether these differences in metrics are associated with cannabis exposure levels. Methods: We systematically reviewed the results from diffusion-MRI imaging studies that compared white matter differences between cannabis users and controls. We also examined the associations between cannabis exposure and other behavioral variables due to changes in white matter. Our review was pre-registered in PROSPERO (ID: 258250; https://www.crd.york.ac.uk/prospero/). Results: We identified 30 diffusion-MRI studies including 1,457 cannabis users and 1,441 controls aged 16-to-45 years. All but 6 studies reported group differences in white matter integrity. The most consistent differences between cannabis users and controls were lower fractional anisotropy within the arcuate/superior longitudinal fasciculus (7 studies), and lower fractional anisotropy of the corpus callosum (6 studies) as well as higher mean diffusivity and trace (4 studies). Differences in fractional anisotropy were associated with cannabis use onset (4 studies), especially in the corpus callosum (3 studies). Discussion: The mechanisms underscoring white matter differences are unclear, and they may include effects of cannabis use onset during youth, neurotoxic effects or neuro adaptations from regular exposure to tetrahydrocannabinol (THC), which exerts its effects by binding to brain receptors, or a neurobiological vulnerability predating the onset of cannabis use. Future multimodal neuroimaging studies, including recently developed advanced diffusion-MRI metrics, can be used to track cannabis users over time and to define with precision when and which region of the brain the white matter changes commence in youth cannabis users, and whether cessation of use recovers white matter differences. Systematic review registration: www.crd.york.ac.uk/prospero/, identifier: 258250.

Brain volumes in alcohol use disorder: Do females and males differ? A whole-brain magnetic resonance imaging mega-analysis.

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group-by-sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD.

Do mindfulness-based interventions change brain function in people with substance dependence? A systematic review of the fMRI evidence.

BACKGROUND: Substance use disorders (SUDs) affect ~ 35 million people globally and are associated with strong cravings, stress, and brain alterations. Mindfulness-based interventions (MBIs) can mitigate the adverse psychosocial outcomes of SUDs, but the underlying neurobiology is unclear. Emerging findings were systematically synthesised from fMRI studies about MBI-associated changes in brain function in SUDs and their associations with mindfulness, drug quantity, and craving. METHODS: PsycINFO, Medline, CINAHL, PubMed, Scopus, and Web of Science were searched. Seven studies met inclusion criteria. RESULTS: Group by time effects indicated that MBIs in SUDs (6 tobacco and 1 opioid) were associated with changes in the function of brain pathways implicated in mindfulness and addiction (e.g., anterior cingulate cortex and striatum), which correlated with greater mindfulness, lower craving and drug quantity. CONCLUSIONS: The evidence for fMRI-related changes with MBI in SUD is currently limited. More fMRI studies are required to identify how MBIs mitigate and facilitate recovery from aberrant brain functioning in SUDs.

Cognitive training and remediation interventions for substance use disorders: a Delphi consensus study.

AIMS: Substance use disorders (SUD) are associated with cognitive deficits that are not always addressed in current treatments, and this hampers recovery. Cognitive training and remediation interventions are well suited to fill the gap for managing cognitive deficits in SUD. We aimed to reach consensus on recommendations for developing and applying these interventions. DESIGN, SETTING AND PARTICIPANTS: We used a Delphi approach with two sequential phases: survey development and iterative surveying of experts. This was an on-line study. During survey development, we engaged a group of 15 experts from a working group of the International Society of Addiction Medicine (Steering Committee). During the surveying process, we engaged a larger pool of experts (n = 54) identified via recommendations from the Steering Committee and a systematic review. MEASUREMENTS: Survey with 67 items covering four key areas of intervention development: targets, intervention approaches, active ingredients and modes of delivery. FINDINGS: Across two iterative rounds (98% retention rate), the experts reached a consensus on 50 items including: (i) implicit biases, positive affect, arousal, executive functions and social processing as key targets of interventions; (ii) cognitive bias modification, contingency management, emotion regulation training and cognitive remediation as preferred approaches; (iii) practice, feedback, difficulty-titration, bias modification, goal-setting, strategy learning and meta-awareness as active ingredients; and (iv) both addiction treatment work-force and specialized neuropsychologists facilitating delivery, together with novel digital-based delivery modalities. CONCLUSIONS: Expert recommendations on cognitive training and remediation for substance use disorders highlight the relevance of targeting implicit biases, reward, emotion regulation and higher-order cognitive skills via well-validated intervention approaches qualified with mechanistic techniques and flexible delivery options.

Effects of cannabinoids on resting state functional brain connectivity: A systematic review.

Cannabis products are widely used for medical and non-medical reasons worldwide and vary in content of cannabinoids such as delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Resting state functional connectivity offers a powerful tool to investigate the effects of cannabinoids on the human brain. We systematically reviewed functional neuroimaging evidence of connectivity during acute cannabinoid administration. A pre-registered (PROSPERO ID: CRD42020184264) systematic review of 13 studies comprising 318 participants (mean age of 25 years) was conducted and reported using the PRISMA checklist. During THC and THCv exposure vs placebo reduced connectivity with the NAcc was widely reported. Limited evidence shows that such effects are offset by co-administration of CBD. NAcc-frontal region connectivity was associated with intoxication levels. Cannabis intoxication vs placebo was associated with lower striatal-ACC connectivity. CBD and CBDv vs placebo were associated with both higher and lower connectivity between striatal-prefrontal/other regions. Overall, cannabis and cannabinoids change functional connectivity in the human brain during resting state as a function of the type of cannabinoid examined.

Brain Anatomical Alterations in Young Cannabis Users: Is it All Hype? A Meta-Analysis of Structural Neuroimaging Studies.

Introduction: Cannabis use has a high prevalence in young youth and is associated with poor psychosocial outcomes. Such outcomes have been ascribed to the impact of cannabis exposure on the developing brain. However, findings from individual studies of volumetry in youth cannabis users are equivocal. Objectives: Our primary objective was to systematically review the evidence on brain volume differences between young cannabis users and nonusers aged 12-26 where profound neuromaturation occurs, accounting for the role of global brain volumes (GBVs). Our secondary objective was to systematically integrate the findings on the association between youth age and volumetry in youth cannabis users. Finally, we aimed to evaluate the quality of the evidence. Materials and Methods: A systematic search was run in three databases (PubMed, Scopus, and PsycINFO) and was reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We run meta-analyses (with and without controlling for GBV) of brain volume differences between young cannabis users and nonusers. We conducted metaregressions to explore the role of age on volumetric differences. Results: Sixteen studies were included. The reviewed samples included 830 people with mean age 22.5 years (range 14-26 years). Of these, 386 were cannabis users (with cannabis use onset at 15-19 years) and 444 were controls. We found no detectable group differences in any of the GBVs (intracranium, total brain, total white matter, and total gray matter) and regional brain volumes (i.e., hippocampus, amygdala, orbitofrontal cortex, and total cerebellum). Age and cannabis use level did not predict (standardized mean) volume group differences in metaregression. We found little evidence of publication bias (Egger's test p>0.1). Conclusions: Contrary to evidence in adult samples (or in samples mixing adults and youth), previous single studies in young cannabis users, and meta-analyses of brain function in young cannabis users, this early evidence suggests nonsignificant volume differences between young cannabis users and nonusers. While prolonged and long-term exposure to heavy cannabis use may be required to detect gross volume alterations, more studies in young cannabis users are needed to map in detail cannabis-related neuroanatomical changes.

Recalibrating single-study effect sizes using hierarchical Bayesian models.

Introduction: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. Methods: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. Results: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Discussion: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Brain reward function in people who use cannabis: a systematic review.

Rationale: Cannabis is one of the most widely used psychoactive substances globally. Cannabis use can be associated with alterations of reward processing, including affective flattening, apathy, anhedonia, and lower sensitivity to natural rewards in conjunction with higher sensitivity to cannabis-related rewards. Such alterations have been posited to be driven by changes in underlying brain reward pathways, as per prominent neuroscientific theories of addiction. Functional neuroimaging (fMRI) studies have examined brain reward function in cannabis users via the monetary incentive delay (MID) fMRI task; however, this evidence is yet to be systematically synthesised. Objectives: We aimed to systematically integrate the evidence on brain reward function in cannabis users examined by the MID fMRI task; and in relation to metrics of cannabis exposure (e.g., dosage, frequency) and other behavioural variables. Method: We pre-registered the review in PROSPERO and reported it using PRISMA guidelines. Literature searches were conducted in PsycINFO, PubMed, Medline, CINAHL, and Scopus. Results: Nine studies were included, comprising 534 people with mean ages 16-to-28 years, of which 255 were people who use cannabis daily or almost daily, and 279 were controls. The fMRI literature to date led to largely non-significant group differences. A few studies reported group differences in the ventral striatum while participants anticipated rewards and losses; and in the caudate while participants received neutral outcomes. A few studies examined correlations between brain function and withdrawal, dosage, and age of onset; and reported inconsistent findings. Conclusions: There is emerging but inconsistent evidence of altered brain reward function in cannabis users examined with the MID fMRI task. Future fMRI studies are required to confirm if the brain reward system is altered in vulnerable cannabis users who experience a Cannabis Use Disorder, as postulated by prominent neuroscientific theories of addiction.