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      The neuropsychopharmacology of cannabis: A review of human imaging studies

      review-article
      a , b , c , d , e , * , a , b , d , a , b , f , g , a , b , h , a , b , h , a , a , i , a , b , j , k
      Pharmacology & Therapeutics
      Pergamon Press
      Addiction, Cannabis, Cognition, Development, Neuroimaging, Psychosis, ACC, Anterior cingulate cortex, ASL, Arterial spin labelling, BOLD, Blood-oxygen-level dependent, CBD, Cannabidiol, CBF, Cerebral blood flow, CB1R, Endocannabinoid type 1 receptor, CT, Computed tomography, D2R, Dopamine type 2 receptor, DLPFC, Dorsolateral prefrontal cortex, DTI, Diffusion tensor imaging, EEG, Electroencephalography, OFC, Orbitofrontal cortex, FDG, Fludeoxyglucose, fMRI, Functional magnetic resonance imaging, GABA, γ-Aminobutyric acid, MID, Monetary incentive delay, MRI, Magnetic resonance imaging, MRS, Magnetic resonance spectroscopy, NAA, N-Acetylaspartate, NAc, Nucleus accumbens, PCC, Posterior cingulate cortex, PET, Positron emission tomography, PFC, Prefrontal cortex, THC, Δ9-Tetrahydrocannabinol

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          Abstract

          The laws governing cannabis are evolving worldwide and associated with changing patterns of use. The main psychoactive drug in cannabis is Δ 9-tetrahydrocannabinol (THC), a partial agonist at the endocannabinoid CB 1 receptor. Acutely, cannabis and THC produce a range of effects on several neurocognitive and pharmacological systems. These include effects on executive, emotional, reward and memory processing via direct interactions with the endocannabinoid system and indirect effects on the glutamatergic, GABAergic and dopaminergic systems. Cannabidiol, a non-intoxicating cannabinoid found in some forms of cannabis, may offset some of these acute effects. Heavy repeated cannabis use, particularly during adolescence, has been associated with adverse effects on these systems, which increase the risk of mental illnesses including addiction and psychosis. Here, we provide a comprehensive state of the art review on the acute and chronic neuropsychopharmacology of cannabis by synthesizing the available neuroimaging research in humans. We describe the effects of drug exposure during development, implications for understanding psychosis and cannabis use disorder, and methodological considerations. Greater understanding of the precise mechanisms underlying the effects of cannabis may also give rise to new treatment targets.

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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            Power failure: why small sample size undermines the reliability of neuroscience.

            A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.
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              FMRIPrep: a robust preprocessing pipeline for functional MRI

              Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad-hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available. The complexity of these workflows has snowballed with rapid advances in acquisition and processing. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for fMRI data. FMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing with no manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software-testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection. Additionally, fMRIPrep introduces less uncontrolled spatial smoothness than commonly used preprocessing tools. FMRIPrep equips neuroscientists with a high-quality, robust, easy-to-use and transparent preprocessing workflow, which can help ensure the validity of inference and the interpretability of their results.
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                Author and article information

                Contributors
                Journal
                Pharmacol Ther
                Pharmacol. Ther
                Pharmacology & Therapeutics
                Pergamon Press
                0163-7258
                1879-016X
                1 March 2019
                March 2019
                : 195
                : 132-161
                Affiliations
                [a ]Translational Psychiatry Research Group, Research Department of Mental Health Neuroscience, Division of Psychiatry, Faculty of Brain Sciences, University College London, United Kingdom
                [b ]Clinical Psychopharmacology Unit, Research Department of Clinical, Educational and Health Psychology, Faculty of Brain Sciences, University College London, United Kingdom
                [c ]Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, London, United Kingdom
                [d ]NIHR University College London Hospitals Biomedical Research Centre, University College Hospital, London, United Kingdom
                [e ]Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, United Kingdom
                [f ]Centre for Neuropsychopharmacology, Division of Brain Sciences, Faculty of Medicine, Imperial College London, United Kingdom
                [g ]Invicro UK, Hammersmith Hospital, London, United Kingdom
                [h ]Institute of Cognitive Neuroscience, Faculty of Brain Sciences, University College London, United Kingdom
                [i ]Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
                [j ]Department of Psychology, University of Bath, United Kingdom
                [k ]National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
                Author notes
                [* ]Corresponding author at: Translational Psychiatry Research Group, Research Department of Mental Health Neuroscience, Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London W1T 7NF, United Kingdom. m.bloomfield@ 123456ucl.ac.uk
                Article
                S0163-7258(18)30190-6
                10.1016/j.pharmthera.2018.10.006
                6416743
                30347211
                c4be130e-e811-4046-a853-813492ad315d
                © 2018 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                Categories
                Article

                Pharmacology & Pharmaceutical medicine
                addiction,cannabis,cognition,development,neuroimaging,psychosis,acc, anterior cingulate cortex,asl, arterial spin labelling,bold, blood-oxygen-level dependent,cbd, cannabidiol,cbf, cerebral blood flow,cb1r, endocannabinoid type 1 receptor,ct, computed tomography,d2r, dopamine type 2 receptor,dlpfc, dorsolateral prefrontal cortex,dti, diffusion tensor imaging,eeg, electroencephalography,ofc, orbitofrontal cortex,fdg, fludeoxyglucose,fmri, functional magnetic resonance imaging,gaba, γ-aminobutyric acid,mid, monetary incentive delay,mri, magnetic resonance imaging,mrs, magnetic resonance spectroscopy,naa, n-acetylaspartate,nac, nucleus accumbens,pcc, posterior cingulate cortex,pet, positron emission tomography,pfc, prefrontal cortex,thc, δ9-tetrahydrocannabinol

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