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Interindividual variability and lateralization of µ-opioid receptors in the human brain

TLDR
In vivo MOR availability in the brains of 204 individuals with no neurologic or psychiatric disorders is quantified using positron emission tomography (PET) with tracer [11C]carfentanil and Bayesian hierarchical modeling to estimate the effects of sex, age, body mass index (BMI) and smoking on [11Cs)carfENTanil binding potential.
Abstract
The brain9s mu-opioid receptors (MORs) are involved in analgesia, reward and mood regulation. Several neuropsychiatric diseases have been associated with dysfunctional MOR system, and there is also considerable variation in receptor density among healthy individuals. Sex, age, body mass and smoking have been proposed to influence the MOR system, but due to small sample sizes the magnitude of their influence remains inconclusive. Here we quantified in vivo MOR availability in the brains of 204 individuals with no neurologic or psychiatric disorders using positron emission tomography (PET) with tracer [11C]carfentanil. We then used Bayesian hierarchical modeling to estimate the effects of sex, age, body mass index (BMI) and smoking on [11C]carfentanil binding potential. We also examined hemispheric lateralization of MOR availability. Age had regionally specific effects on MOR availability, with age-dependent increase in frontotemporal areas but decrease in amygdala, thalamus, and nucleus accumbens. The age-dependent increase was stronger in males. MOR availability was globally lowered in smokers but independent of BMI. Finally, MOR availability was higher in the right versus the left hemisphere. The presently observed variation in MOR availability may explain why some individuals are prone to develop MOR-linked pathological states, such as chronic pain or psychiatric disorders.

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neuromaps: structural and functional interpretation of brain maps

TL;DR: Neuralomaps as mentioned in this paper is a toolbox for accessing, transforming and analyzing structural and functional brain annotations, which includes curated reference maps and biological ontologies of the human brain, such as molecular, microstructural, electrophysiological, developmental and functional ontologies.
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Adult Attachment System Links With Brain Mu Opioid Receptor Availability In Vivo.

TL;DR: Preliminary in vivo evidence is provided that the opioid system may be involved in the neurocircuits associated with individual differences in adult attachment behavior and suggests variation in mu opioid receptor availability may be linked with the individuals' social relationships and psychosocial well-being and thus contributes to risk for psychiatric morbidity.
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Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities

TL;DR: In this article , the authors systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination, as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability).
References
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Book

Bayesian Data Analysis

TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Book

Data Analysis Using Regression and Multilevel/Hierarchical Models

TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.
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Power failure: why small sample size undermines the reliability of neuroscience

TL;DR: It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
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False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant

TL;DR: It is shown that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings, flexibility in data collection, analysis, and reporting dramatically increases actual false- positive rates, and a simple, low-cost, and straightforwardly effective disclosure-based solution is suggested.
Journal ArticleDOI

brms: An R Package for Bayesian Multilevel Models Using Stan

TL;DR: The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan, allowing users to fit linear, robust linear, binomial, Poisson, survival, ordinal, zero-inflated, hurdle, and even non-linear models all in a multileVEL context.
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