Longitudinal study of hippocampal volumes in heavy cannabis users.

BACKGROUND: Cannabis exposure, particularly heavy cannabis use, has been associated with neuroanatomical alterations in regions rich with cannabinoid receptors such as the hippocampus in some but not in other (mainly cross-sectional) studies. However, it remains unclear whether continued heavy cannabis use alters hippocampal volume, and whether an earlier age of onset and/or a higher dosage exacerbate these changes. METHODS: Twenty heavy cannabis users (mean age 21 years, range 18-24 years) and 23 matched non-cannabis using healthy controls were submitted to a comprehensive psychological assessment and magnetic resonance imaging scan at baseline and at follow-up (average of 39 months post-baseline; standard deviation=2.4). Cannabis users started smoking around 16 years and smoked on average five days per week. A novel aspect of the current study is that hippocampal volume estimates were obtained from manual tracing the hippocampus on T1-weighted anatomical magnetic resonance imaging scans, using a previously validated protocol. RESULTS: Compared to controls, cannabis users did not show hippocampal volume alterations at either baseline or follow-up. Hippocampal volumes increased over time in both cannabis users and controls, following similar trajectories of increase. Cannabis dose and age of onset of cannabis use did not affect hippocampal volumes. CONCLUSIONS: Continued heavy cannabis use did not affect hippocampal neuroanatomical changes in early adulthood. This contrasts with prior evidence on alterations in this region in samples of older adult cannabis users. In young adults using cannabis at this level, cannabis use may not be heavy enough to affect hippocampal neuroanatomy.

Cannabis use and transition to psychosis in individuals at ultra-high risk: review and meta-analysis.

BACKGROUND: Previous research has established the relationship between cannabis use and psychotic disorders. Whether cannabis use is related to transition to psychosis in patients at ultra-high risk (UHR) for psychosis remains unclear. The present study aimed to review the existing evidence on the association between cannabis use and transition to psychosis in UHR samples. METHOD: A search of PsychInfo, Embase and Medline was conducted from 1996 to August 2015. The search yielded 5559 potentially relevant articles that were selected on title and abstract. Subsequently 36 articles were screened on full text for eligibility. Two random-effects meta-analyses were performed. First, we compared transition rates to psychosis of UHR individuals with lifetime cannabis use with non-cannabis-using UHR individuals. Second, we compared transition rates of UHR individuals with a current DSM-IV cannabis abuse or dependence diagnosis with lifetime users and non-using UHR individuals. RESULTS: We found seven prospective studies reporting on lifetime cannabis use in UHR subjects (n = 1171). Of these studies, five also examined current cannabis abuse or dependence. Lifetime cannabis use was not significantly associated with transition to psychosis [odds ratio (OR) 1.14, 95% confidence interval (CI) 0.856-1.524, p = 0.37]. A second meta-analysis yielded an OR of 1.75 (95% CI 1.135-2.710, p = 0.01), indicating a significant association between current cannabis abuse or dependence and transition to psychosis. CONCLUSIONS: Our results show that cannabis use was only predictive of transition to psychosis in those who met criteria for cannabis abuse or dependence, tentatively suggesting a dose-response relationship between current cannabis use and transition to psychosis.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Cue-induced striatal activity in frequent cannabis users independently predicts cannabis problem severity three years later.

Cannabis is the most frequently used illicit drug worldwide, but little is known about the mechanisms underlying continued cannabis use. Cue-reactivity (the physical, psychological, behavioural and neural reaction to substance-related cues) might be related to continued cannabis use. In this 3-year prospective neuroimaging study we investigated whether cannabis cue-induced brain activity predicted continued cannabis use and associated problem severity 3 years later. In addition, baseline brain activations were compared between dependent and non-dependent cannabis users at follow-up. Analyses were focussed on brain areas known to be important in cannabis cue-reactivity: anterior cingulate cortex, orbitofrontal cortex, ventral tegmental area, amygdala and striatum. At baseline, 31 treatment-naive frequent cannabis users performed a cue-reactivity functional magnetic resonance imaging task. Of these participants, 23 completed the 3-year follow-up. None of the cue-induced region of interest activations predicted the amount of cannabis use at follow-up. However, cue-induced activation in the left striatum (putamen) significantly and independently predicted problem severity at follow-up (p < 0.001) as assessed with the Cannabis Use Disorder Identification Test. Also, clinically dependent cannabis users at follow-up showed higher baseline activation at trend level in the left striatum compared with non-dependent users. This indicates that neural cue-reactivity in the dorsal striatum is an independent predictor of cannabis use-related problems. Given the relatively small sample size, these results are preliminary and should be replicated in larger samples of cannabis users.

Cannabis dependence, cognitive control and attentional bias for cannabis words.

One of the characteristics of people suffering from addictive behaviors is the tendency to be distracted by drug cues. This attentional bias for drug cues is thought to lead to increased craving and drug use, and may draw individuals into a vicious cycle of drug addiction. In the current study we developed a Dutch version of the cannabis Stroop task and measured attentional bias for cannabis words in a group of heavy cannabis users and matched controls. The classical Stroop task was used as a global measure of cognitive control and we examined the relationship between cognitive control, cannabis-related problems, cannabis craving and cannabis attentional bias. Using our version of the cannabis Stroop task, a group of heavy cannabis users showed attentional bias to cannabis words, whereas a control group of non-users did not. Furthermore, within the group of cannabis users, those who were clinically recognized as dependent showed a stronger attentional bias than the heavy, non-dependent users. Cannabis users who displayed reduced cognitive control (as measured with the classical Stroop task) showed increased session-induced craving. Contrary to expectations, however, cognitive control did not appear to modulate the relationship between attentional bias to cannabis words (cannabis Stroop task) and cannabis dependence. This study confirmed the relationship between cannabis dependence and attentional bias and extends this by highlighting a moderating role for cognitive control, which may make some more vulnerable to craving.

Investigation of blind tip estimation.

In this work we study functions for maximum likelihood estimation in blind tip estimation. We will implement the expectation maximization (EM), the stochastic EM, and stochastic approximation EM algortithms to estimate the unknown tip geometry. To demonstrate the functionality of the algorithms we applied it to dilated artificial input signal.

Angstrom ruler for high-accuracy pitch measurement.

An x-ray interferometer (XRI), which takes the lattice spacing of silicon as a length unit, can measure displacement with subnanometer resolution. A scanning probe microscope that combines an XRI and a scanning-tunnel microscope is designed to measure pitch. Experimental results have proved the feasibility of the design.