2018
DOI: 10.1016/j.neuroscience.2016.11.018
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Resting-state Abnormalities in Heroin-dependent Individuals

Abstract: Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or oth… Show more

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Cited by 28 publications
(17 citation statements)
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“…Density (D) is the number of actual connections among network nodes divided by the maximum possible connections. Small-world (SW) networks (small-world scalar is defined in [ 90 , 91 ]) are characterized by a short path length that is indicative of communication efficiency along with a high clustering coefficient which represents a high suborganization [ 92 , 93 ]. In our study, the comparison of CPL and CC in the SW metric was made against 10,000 random networks with the same number of connections and density to connectivity networks.…”
Section: Methodsmentioning
confidence: 99%
“…Density (D) is the number of actual connections among network nodes divided by the maximum possible connections. Small-world (SW) networks (small-world scalar is defined in [ 90 , 91 ]) are characterized by a short path length that is indicative of communication efficiency along with a high clustering coefficient which represents a high suborganization [ 92 , 93 ]. In our study, the comparison of CPL and CC in the SW metric was made against 10,000 random networks with the same number of connections and density to connectivity networks.…”
Section: Methodsmentioning
confidence: 99%
“…For these reasons, rsFC also holds promise for identification of treatment targets. Other advantages of rsFC over task-based fMRI paradigms include 1) data collection is more straightforward and easily replicable across sites, 2) subject participation does not require intact cognition, and 3) the data is not as susceptible to interference by changes in motivation or performance (Fedota & Stein, 2015;Lu & Stein, 2014;Pandria et al, 2016;Pariyadath et al, 2016;Sutherland et al, 2012;. rsFC has advantages over genetics (although not necessarily epigenetics) and other more static imaging measures like structural imaging because it changes over time and can be utilized to look at treatment mechanisms (Lu & Stein, 2014;Pariyadath et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…One common approach throughout the mental health field is to compare individuals with a diagnosis with individuals matched on important characteristics to those without a diagnosis (healthy comparisons (HC)) (or simply correlating measures of disease severity with measures of brain function) to try to understand underlying functional deficits. Studies like this have been done extensively and in a variety of SUD populations as well [for some excellent reviews see (Fedota & Stein, 2015;Ieong & Yuan, 2017;Lu & Stein, 2014;Moeller et al, 2016;Pandria et al, 2016;Pariyadath et al, 2016;Sutherland et al, 2012;Wilcox et al, 2014;Wilcox et al, 2016)]. However, there is a problem with using these data when collected in a cross-sectional design if the goal is to identify treatment targets, as identified group differences may or may not be causing behavior change.…”
Section: Introductionmentioning
confidence: 99%
“…Despite this potential, effective translation of research findings into the clinical realm remains elusive [35]. To synthesize existing knowledge and facilitate effective translation of findings to real-world clinical settings, we aim to build upon recent reviews focused more broadly on fMRI findings across different substance use disorders [36,37] and others focused more narrowly on resting-state fMRI in OUD [38][39][40] by examining published fMRI literature (both task-based and resting-state) relevant to OUD, with an emphasis on findings related to opioid medications and treatment outcomes, as well as proposing areas for further research. By delineating common and distinct neural mechanisms of OUD pathophysiology and treatment response, it may be possible to identify which individuals are most likely to benefit from different treatments, optimize existing therapeutic approaches to target neural and clinical features of OUD, and unveil novel neuroscience-informed interventions to combat the nationwide opioid epidemic [32,35,41].…”
Section: Introductionmentioning
confidence: 99%