Literature DB >> 24144504

The efficiency of functional brain networks does not differ between smokers and non-smokers.

Thomas Peer Karl Breckel1, Christiane Margarethe Thiel, Carsten Giessing.   

Abstract

Acute nicotine consumption in smokers impacts on functional brain network topology indicating an increase in the efficiency of information transfer and attentional task performance. The effects of chronic nicotine consumption on functional brain network topology are unknown. We here investigated the effects of chronic smoking-behaviour on functional brain network topology. Minimally-deprived smokers (N=18) and non-smokers (N=17) were measured within an fMRI scanner during a resting state condition. Graph-theoretical metrics of functional network integration (global efficiency and clustering) that have been shown to be affected by acute nicotine administration were compared between both groups. Our results revealed that smoking status did not significantly change functional network integration. Additional tests for non-inferiority confirmed the similarity of regional or nodal network properties. Brain regions such as the left insular and middle frontal gyrus, in which acute nicotine consumption affected network topology, did not reveal any decrease in functional network efficiency following chronic nicotine consumption. Within the limitation of the investigated sample size, our data suggest that the integration of functional brain networks is not altered in minimally-deprived smokers. Our findings are of relevance for clinical studies showing changes in network topology between psychiatric patients with high prevalence of smoking and healthy control subjects.
© 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Brain efficiency; Equivalence testing; Graph theory; Resting state; Smoking addiction; fMRI

Mesh:

Substances:

Year:  2013        PMID: 24144504     DOI: 10.1016/j.pscychresns.2013.07.005

Source DB:  PubMed          Journal:  Psychiatry Res        ISSN: 0165-1781            Impact factor:   3.222


  10 in total

1.  Loss of brain graph network efficiency in alcohol dependence.

Authors:  Zsuzsika Sjoerds; Steven M Stufflebeam; Dick J Veltman; Wim Van den Brink; Brenda W J H Penninx; Linda Douw
Journal:  Addict Biol       Date:  2015-12-22       Impact factor: 4.280

2.  Lower gray matter density and functional connectivity in the anterior insula in smokers compared with never smokers.

Authors:  Luke E Stoeckel; Xiaoqian J Chai; Jiahe Zhang; Susan Whitfield-Gabrieli; A Eden Evins
Journal:  Addict Biol       Date:  2015-05-20       Impact factor: 4.280

3.  Network Analysis of Intrinsic Functional Brain Connectivity in Male and Female Adult Smokers: A Preliminary Study.

Authors:  Megan M Moran-Santa Maria; Davy C Vanderweyen; Christopher C Camp; Xun Zhu; Sherry A McKee; Kelly P Cosgrove; Karen J Hartwell; Kathleen T Brady; Jane E Joseph
Journal:  Nicotine Tob Res       Date:  2018-06-07       Impact factor: 4.244

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Authors:  Fuwang Wang; Xiaolei Zhang; Rongrong Fu; Guangbin Sun
Journal:  RSC Adv       Date:  2018-08-23       Impact factor: 4.036

Review 5.  Resting-state functional connectivity and nicotine addiction: prospects for biomarker development.

Authors:  John R Fedota; Elliot A Stein
Journal:  Ann N Y Acad Sci       Date:  2015-09       Impact factor: 5.691

6.  Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency.

Authors:  K Baek; L S Morris; P Kundu; V Voon
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Journal:  Entropy (Basel)       Date:  2018-03-15       Impact factor: 2.524

8.  Oxytocin-Induced Changes in Intrinsic Network Connectivity in Cocaine Use Disorder: Modulation by Gender, Childhood Trauma, and Years of Use.

Authors:  Jane E Joseph; Brandon K Vaughan; Christopher C Camp; Nathaniel L Baker; Brian J Sherman; Megan Moran-Santa Maria; Aimee McRae-Clark; Kathleen T Brady
Journal:  Front Psychiatry       Date:  2019-07-19       Impact factor: 4.157

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Authors:  Fuwang Wang; Xiaolei Zhang; Rongrong Fu; Guangbin Sun
Journal:  Sensors (Basel)       Date:  2018-06-01       Impact factor: 3.576

10.  Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG.

Authors:  Fuwang Wang; Qing Xu; Rongrong Fu
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  10 in total

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