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.

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).

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.

Resting-state neuroimaging in social anxiety disorder: a systematic review.

There has been a growing interest in resting-state brain alterations in people with social anxiety disorder. However, the evidence has been mixed and contested and further understanding of the neurobiology of this disorder may aid in informing methods to increase diagnostic accuracy and treatment targets. With this systematic review, we aimed to synthesize the findings of the neuroimaging literature on resting-state functional activity and connectivity in social anxiety disorder, and to summarize associations between brain and social anxiety symptoms to further characterize the neurobiology of the disorder. We systematically searched seven databases for empirical research studies. Thirty-five studies met the inclusion criteria, with a total of 1611 participants (795 people with social anxiety disorder and 816 controls). Studies involving resting-state seed-based functional connectivity analyses were the most common. Individuals with social anxiety disorder (vs. controls) displayed both higher and lower connectivity between frontal-amygdala and frontal-parietal regions. Frontal regions were the most consistently implicated across other analysis methods, and most associated with social anxiety symptoms. Small sample sizes and variation in the types of analyses used across studies may have contributed to the inconsistencies in the findings of this review. This review provides novel insights into established neurobiological models of social anxiety disorder and provides an update on what is known about the neurobiology of this disorder in the absence of any overt tasks (i.e., resting state). The knowledge gained from this body of research enabled us to also provide recommendations for a more standardized imaging pre-processing approach to examine resting-state brain activity and connectivity that could help advance knowledge in this field. We believe this is warranted to take the next step toward clinical translation in social anxiety disorder that may lead to better treatment outcomes by informing the identification of neurobiological targets for treatment.

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.

How do substance use disorders compare to other psychiatric conditions on structural brain abnormalities? A cross-disorder meta-analytic comparison using the ENIGMA consortium findings.

Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto-cerebellar and meso-cortico-limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large-scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case-control differences and to compare brain-correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta-analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age- and sex-matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case-control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co-variates . After correcting for multiple comparisons, AUD case-control meta-analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta-analysis of CUD case-control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross-disorder comparison of brain correlates of substance use disorders and showed alcohol-related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex.

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group.

Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.

Accuracy of automated amygdala MRI segmentation approaches in Huntington's disease in the IMAGE-HD cohort.

Smaller manually-segmented amygdala volumes have been associated with poorer motor and cognitive function in Huntington's disease (HD). Manual segmentation is the gold standard in terms of accuracy; however, automated methods may be necessary in large samples. Automated segmentation accuracy has not been determined for the amygdala in HD. We aimed to determine which of three automated approaches would most accurately segment amygdalae in HD: FreeSurfer, FIRST, and ANTS nonlinear registration followed by FIRST segmentation. T1-weighted images for the IMAGE-HD cohort including 35 presymptomatic HD (pre-HD), 36 symptomatic HD (symp-HD), and 34 healthy controls were segmented using FreeSurfer and FIRST. For the third approach, images were nonlinearly registered to an MNI template using ANTS, then segmented using FIRST. All automated methods overestimated amygdala volumes compared with manual segmentation. Dice overlap scores, indicating segmentation accuracy, were not significantly different between automated approaches. Manually segmented volumes were most statistically differentiable between groups, followed by those segmented by FreeSurfer, then ANTS/FIRST. FIRST-segmented volumes did not differ between groups. All automated methods produced a bias where volume overestimation was more severe for smaller amygdalae. This bias was subtle for FreeSurfer, but marked for FIRST, and moderate for ANTS/FIRST. Further, FreeSurfer introduced a hemispheric bias not evident with manual segmentation, producing larger right amygdalae by 8%. To assist choice of segmentation approach, we provide sample size estimation graphs based on sample size and other factors. If automated segmentation is employed in samples of the current size, FreeSurfer may effectively distinguish amygdala volume between controls and HD.

Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study.

While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.

Neuroanatomical alterations in people with high and low cannabis dependence.

OBJECTIVES: We aimed to investigate whether severity of cannabis dependence is associated with the neuroanatomy of key brain regions of the stress and reward brain circuits. METHODS: To examine dependence-specific regional brain alterations, we compared the volumes of regions relevant to reward and stress, between high-dependence cannabis users (CD+, n = 25), low-dependence cannabis users (CD-, n = 20) and controls (n = 37). RESULTS: Compared to CD- and/or controls, the CD+ group had lower cerebellar white matter and hippocampal volumes, and deflation of the right hippocampus head and tail. CONCLUSION: These findings provide initial support for neuroadaptations involving stress and reward circuits that are specific to high-dependence cannabis users.

Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits.

Individual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains cortical-striatal-thalamic-cortical dysfunction across different disorders remains unclear. Here, we characterized the relationship between cortical-striatal-thalamic-cortical effective connectivity, estimated using dynamic causal modelling of resting-state functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder and gambling disorder. 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 obsessive-compulsive disorder patients, 22 gambling disorder patients, and 39 healthy controls, who underwent functional magnetic resonance imaging. Three core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients' scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and greater bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with lower bottom-up connectivity in the dorsal circuit. In patients, higher clinical severity was also linked to lower bottom-up connectivity in the dorsal circuit, but these findings were independent of phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels and only weak associations were observed for functional connectivity measures. Together, our results demonstrate that cortical-striatal-thalamic-cortical dysfunction across obsessive-compulsive disorder and gambling disorder may be better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.

Defining Compulsive Behavior.

Compulsive tendencies are a central feature of problematic human behavior and thereby are of great interest to the scientific and clinical community. However, no consensus exists about the precise meaning of 'compulsivity,' creating confusion in the field and hampering comparison across psychiatric disorders. A vague conceptualization makes compulsivity a moving target encompassing a fluctuating variety of behaviors, which is unlikely to improve the new dimension-based psychiatric or psychopathology approach. This article aims to help progress the definition of what constitutes compulsive behavior, cross-diagnostically, by analyzing different definitions in the psychiatric literature. We searched PubMed for articles in human psychiatric research with 'compulsive behavior' or 'compulsivity' in the title that focused on the broader concept of compulsivity-returning 28 articles with nine original definitions. Within the definitions, we separated three types of descriptive elements: phenomenological, observational and explanatory. The elements most applicable, cross-diagnostically, resulted in this definition: Compulsive behavior consists of repetitive acts that are characterized by the feeling that one 'has to' perform them while one is aware that these acts are not in line with one's overall goal. Having a more unified definition for compulsive behavior will make its meaning precise and explicit, and therefore more transferable and testable across clinical and non-clinical populations.

Does regular cannabis use affect neuroanatomy? An updated systematic review and meta-analysis of structural neuroimaging studies.

Regular cannabis use is associated with adverse cognitive and mental health outcomes that have been ascribed to aberrant neuroanatomy in brain regions densely innervated with cannabinoid receptors. Neuroanatomical differences between cannabis users and controls have been assessed in multiple structural magnetic resonance imaging (sMRI) studies. However, there is heterogeneity in the results leading to cautious interpretation of the data so far. We examined the sMRI evidence to date in human cannabis users, to establish more definitely whether neuroanatomical alterations are associated with regular cannabis use. The regional specificity and association with cannabis use indices (i.e. cumulative dosage, duration) were also explored. We systematically reviewed and meta-analysed published sMRI studies investigating regional brain volumes (cortical, subcortical and global) in cannabis users and non-user controls. Three electronic databases were searched (PubMed, Scopus, and PsycINFO). A total of 17 meta-analyses were conducted (one for each cortical, subcortical and global volume) using the generic inverse variance method, whereby standardised mean difference in volume was calculated between users and non-users. Exploratory meta-regressions were conducted to investigate the association between cannabis use indices and regional brain volumes. A total of 30 articles were eligible for inclusion, contributing 106 effect sizes across 17 meta-analyses. Regular cannabis users had significantly smaller volumes of the hippocampus (SMD = 0.14, 95% CIs [0.02, 0.27]; Z = 2.29, p = 0.02, I2 = 74%) and orbitofrontal cortex {medial (SMD = 0.30, 95% CIs [0.15, 0.45]; Z = 3.89, p = 0.0001, I2 = 51%), lateral (SMD = 0.19, 95% CIs [0.07, 0.32]; Z = 3.10, p = 0.002, I2 = 26%)} relative to controls. The volumes of the hippocampus and orbitofrontal cortex were not significantly associated with cannabis duration and dosage. Our findings are consistent with evidence of aberrance in brain regions involved in reward, learning and memory, and motivation circuits in the regular use of substances other than cannabis, pointing to commonality in neurobiological abnormalities between regular users of cannabis and of other substances.

Alteration to hippocampal volume and shape confined to cannabis dependence: a multi-site study.

Cannabis use is highly prevalent and often considered to be relatively harmless. Nonetheless, a subset of regular cannabis users may develop dependence, experiencing poorer quality of life and greater mental health problems relative to non-dependent users. The neuroanatomy characterizing cannabis use versus dependence is poorly understood. We aimed to delineate the contributing role of cannabis use and dependence on morphology of the hippocampus, one of the most consistently altered brain regions in cannabis users, in a large multi-site dataset aggregated across four research sites. We compared hippocampal volume and vertex-level hippocampal shape differences (1) between 121 non-using controls and 140 cannabis users; (2) between 106 controls, 50 non-dependent users and 70 dependent users; and (3) between a subset of 41 controls, 41 non-dependent users and 41 dependent users, matched on sample characteristics and cannabis use pattern (onset age and dosage). Cannabis users did not differ from controls in hippocampal volume or shape. However, cannabis-dependent users had significantly smaller right and left hippocampi relative to controls and non-dependent users, irrespective of cannabis dosage. Shape analysis indicated localized deflations in the superior-medial body of the hippocampus. Our findings support neuroscientific theories postulating dependence-specific neuroadaptations in cannabis users. Future efforts should uncover the neurobiological risk and liabilities separating dependent and non-dependent use of cannabis.

The anticipation and outcome phases of reward and loss processing: A neuroimaging meta-analysis of the monetary incentive delay task.

The processing of rewards and losses are crucial to everyday functioning. Considerable interest has been attached to investigating the anticipation and outcome phases of reward and loss processing, but results to date have been inconsistent. It is unclear if anticipation and outcome of a reward or loss recruit similar or distinct brain regions. In particular, while the striatum has widely been found to be active when anticipating a reward, whether it activates in response to the anticipation of losses as well remains ambiguous. Furthermore, concerning the orbitofrontal/ventromedial prefrontal regions, activation is often observed during reward receipt. However, it is unclear if this area is active during reward anticipation as well. We ran an Activation Likelihood Estimation meta-analysis of 50 fMRI studies, which used the Monetary Incentive Delay Task (MIDT), to identify which brain regions are implicated in the anticipation of rewards, anticipation of losses, and the receipt of reward. Anticipating rewards and losses recruits overlapping areas including the striatum, insula, amygdala and thalamus, suggesting that a generalised neural system initiates motivational processes independent of valence. The orbitofrontal/ventromedial prefrontal regions were recruited only during the reward outcome, likely representing the value of the reward received. Our findings help to clarify the neural substrates of the different phases of reward and loss processing, and advance neurobiological models of these processes.

Unpacking the role of self-reported compulsivity and impulsivity in obsessive-compulsive disorder.

OBJECTIVE: We aimed to determine whether individuals with obsessive-compulsive disorder (OCD) and demographically matched healthy individuals can be clustered into distinct clinical subtypes based on dimensional measures of their self-reported compulsivity (OBQ-44 and IUS-12) and impulsivity (UPPS-P). METHODS: Participants (n=217) were 103 patients with a clinical diagnosis of OCD; 79 individuals from the community who were "OCD-likely" according to self-report (Obsessive-Compulsive Inventory-Revised scores equal or greater than 21); and 35 healthy controls. All data were collected between 2013 and 2015 using self-report measures that assessed different aspects of compulsivity and impulsivity. Principal component analysis revealed two components broadly representing an individual's level of compulsivity and impulsivity. Unsupervised clustering grouped participants into four subgroups, each representing one part of an orthogonal compulsive-impulsive phenotype. RESULTS: Clustering converged to yield four subgroups: one group low on both compulsivity and impulsivity, comprised mostly of healthy controls and demonstrating the lowest OCD symptom severity; two groups showing roughly equal clinical severity, but with opposing drivers (i.e., high compulsivity and low impulsivity, and vice versa); and a final group high on both compulsivity and impulsivity and recording the highest clinical severity. Notably, the largest cluster of individuals with OCD was characterized by high impulsivity and low compulsivity. Our results suggest that both impulsivity and compulsivity mediate obsessive-compulsive symptomatology. CONCLUSIONS: Individuals with OCD can be clustered into distinct subtypes based on measures of compulsivity and impulsivity, with the latter being found to be one of the more defining characteristics of the disorder. These dimensions may serve as viable and novel treatment targets.

Investigating the role of anticipatory reward and habit strength in obsessive-compulsive disorder.

Aims To determine the rates and associated illness characteristics of obsessive-compulsive disorder (OCD) patients who describe their symptoms as either rewarding or habitual. METHODS: Seventy-three treatment-seeking OCD patients had their dominant compulsive behavior assessed with a structured interview (the Temporal Impulsive-Compulsive Scale-Revised) to track the progression of rewarding (ie, gain in positive affect), aversive (ie, decrease in negative affect), and neutral (or non-affective) states and a self-report scale (the Self-Report Habit Index) to evaluate their habitual features. Additional measures included structured diagnostic interviews for axis I and II disorders, measures of OCD symptoms severity, and a battery of instruments to comprehensively assess relevant aspects of sensitivity to reward and fear. RESULTS: Almost half (49%) of our OCD patients (particularly washers) endorsed that they anticipated obtaining a reward (ie, positive affect) from the enactment of their dominant compulsive behavior. Washers stood out in that their positive affects during and after compulsive behaviors were highly (and positively) correlated with duration of illness. In contrast, habit strength did not differ between washers, checkers, and arrangers, although it also correlated with duration of illness among checkers. Furthermore, the severity of OCD and comorbidity with impulse control disorders predicted up to 35% of the variance in the habit strength of OCD behaviors. CONCLUSION: Compulsive washing may be more clearly characterized by problems in reward processing. In contrast, duration of checking, severity of OCD, and comorbidity with impulse control disorders shape compulsive behaviors by imparting them with habitual tendencies.

Gross morphological brain changes with chronic, heavy cannabis use.

We investigated the morphology of multiple brain regions in a rare sample of 15 very heavy cannabis users with minimal psychiatric comorbidity or significant exposure to other substances (compared with 15 age- and IQ-matched non-cannabis-using controls) using manual techniques. Heavy cannabis users demonstrated smaller hippocampus and amygdala volumes, but no alterations of the orbitofrontal and anterior- and paracingulate cortices, or the pituitary gland. These findings indicate that chronic cannabis use has a selective and detrimental impact on the morphology of the mediotemporal lobe.