Journal ArticleDOI
Network analysis reveals disrupted functional brain circuitry in drug-naive social anxiety disorder
Xun Yang,Jin Liu,Yajing Meng,Mingrui Xia,Zaixu Cui,Xi Wu,Xinyu Hu,Wei Zhang,Gaolang Gong,Qiyong Gong,John A. Sweeney,John A. Sweeney,Yong He +12 more
TLDR
Findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety.About:
This article is published in NeuroImage.The article was published on 2017-01-01. It has received 61 citations till now. The article focuses on the topics: Dorsolateral prefrontal cortex & Posterior cingulate.read more
Citations
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Novel pharmacological targets in drug development for the treatment of anxiety and anxiety-related disorders.
TL;DR: Compounds such as D-cycloserine, MDMA, L-DOPA and cannabinoids have shown efficacy in enhancing fear-extinction learning in humans, and are investigated in clinical trials as an augmentative strategy for speeding up and enhancing the long-term effectiveness of exposure-based psychotherapy.
Journal ArticleDOI
Anxious brain networks: A coordinate-based activation likelihood estimation meta-analysis of resting-state functional connectivity studies in anxiety
Jie Xu,Nicholas T. Van Dam,Nicholas T. Van Dam,Chunliang Feng,Chunliang Feng,Yuejia Luo,Hui Ai,Ruolei Gu,Pengfei Xu +8 more
TL;DR: An activation likelihood estimation meta‐analysis of resting‐state functional connectivity studies in anxiety and anxiety disorders shows that anxiety can be characterized by hypo‐connectivity of the affective network with executive control network and default mode network, as well as decoupling of the ECN with the DMN.
Journal ArticleDOI
Gray Matter Structural Alterations in Social Anxiety Disorder: A Voxel-Based Meta-Analysis.
TL;DR: A systematic search of studies comparing gray matter volume differences between SAD patients and healthy controls using a whole-brain voxel-based morphometry (VBM) approach revealed directionally consistent larger cortical GMVs and smaller subcortical GMVs, including locationally consistent large precuneus and thalamic deficits in the left brain.
Journal ArticleDOI
Statistical inference in brain graphs using threshold-free network-based statistics.
Hugo C. Baggio,Alexandra Abos,Barbara Segura,Anna Campabadal,Anna Isabel Garcia-Diaz,Carme Uribe,Yaroslau Compta,María José Martí,Francesc Valldeoriola,Carme Junqué +9 more
TL;DR: This study uses simulated data to assess the properties of threshold‐free network‐based statistics (TFNBS), and shows that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false‐positive rates.
Journal ArticleDOI
Subcortical brain volumes, cortical thickness and cortical surface area in families genetically enriched for social anxiety disorder - A multiplex multigenerational neuroimaging study.
Janna Marie Bas-Hoogendam,Janna Marie Bas-Hoogendam,Henk van Steenbergen,Renaud L.M. Tissier,Jeanine J. Houwing-Duistermaat,P. Michiel Westenberg,Nic J.A. van der Wee +6 more
TL;DR: Preliminary evidence is provided that GM characteristics of multiple ROIs, which are distributed over the brain, are candidate endophenotypes of SAD and shed light on the genetic vulnerability for SAD.
References
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Statistical Power Analysis for the Behavioral Sciences
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Complex brain networks: graph theoretical analysis of structural and functional systems
Edward T. Bullmore,Olaf Sporns +1 more
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.
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Complex network measures of brain connectivity: uses and interpretations.
Mikail Rubinov,Olaf Sporns +1 more
TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
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Exploring complex networks
TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.
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