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Higher BMI, but not obesity-related genetic polymorphisms, correlates with lower structural connectivity of the reward network in a population-based study

TLDR
Evidence is provided that higher BMI correlates with lower reward network structural connectivity, in line with previous findings of obesity-related decline in white matter microstructure.

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OUP accepted manuscript

TL;DR: Engel et al. as discussed by the authors presented a study on the life-adult-study at the Leipzig Institute for Medical Informatics, Statistics and Epidemiology (Engel-Engel Institute) in Germany.
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Role of the striatal dopamine, GABA and opioid systems in mediating feeding and fat intake

TL;DR: In this article , the authors provided insights concerning the impact of feeding, including fat intake, on different types of receptors and neurotransmitters present in the striatal complex and in particular the nucleus accumbens, with a focus on dopamine, GABA and the opioid system.

Obesity gene NEGR1 associated with white matter integrity in healthy young adults

TL;DR: This is the first study to find an association between an obesity risk gene and differences in white matter integrity, and suggests that NEGR1 has effects on brain structure independent of its effect on obesity.
Journal ArticleDOI

Brain functional and structural magnetic resonance imaging of obesity and weight loss interventions

TL;DR: A comprehensive literature review of the recent neuroimaging advances on the underlying neural mechanisms of both obesity and interventions, in the hope of guiding development of novel and effective treatments is provided in this article .
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Exploring the genetic correlation between obesity-related traits and regional brain volumes: Evidence from UK Biobank cohort

TL;DR: Based on a mixed linear model (MLM), the authors analyzed the association between 1,498 obesity-related SNPs in the GWAS catalog and 164 regional brain volumes from 29,420 participants in UK Biobank.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
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Complex brain networks: graph theoretical analysis of structural and functional systems

TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Journal ArticleDOI

Cortical surface-based analysis. I. Segmentation and surface reconstruction

TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.
Journal ArticleDOI

Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

TL;DR: In this paper, a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set is presented.
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Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

TL;DR: The results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements.
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