Share this content in WeChat
Clinical Article
Changes of functional connectivity density in different severity of nicotine addicts: A functional magnetic resonance imaging study
NIU Xiaoyu  ZHANG Yong  YANG Zhengui  ZHANG Mengzhe  GAO Xinyu  WANG Weijian  CHENG Jingliang 

Cite this article as: NIU X Y, ZHANG Y, YANG Z G, et al. Changes of functional connectivity density in different severity of nicotine addicts: A functional magnetic resonance imaging study[J]. Chin J Magn Reson Imaging, 2023, 14(4): 11-15. DOI:10.12015/issn.1674-8034.2023.04.003.

[Abstract] Objective We aimed to use the functional connectivity density (FCD) method to investigate the common functional brain alterations in the resting state of nicotine addicts, and whether there were more specific brain changes in functional coordination in different severity of nicotine addicts.Materials and Methods A total of 120 nicotine addicts (59 in the mild group and 61 in the severe group) and 56 normal controls underwent resting state magnetic resonance imaging scanning and FCD values were calculated. FCD values were compared among the three groups by ANOVA analysis, and then the differences between the two groups were studied by post-hoc analysis.Results Compared with the control group, both the mild group and the severe group showed decreased FCD in the bilateral calcarine sulcus cortex; only the severe group showed decreased FCD in the right cuneus (voxel level P<0.005, mass level P<0.01, Gaussian random field adjusted).Conclusions There were common coordination changes related to the visual attention network in different severity of nicotine addicts, and they persisted with the progression of nicotine dependence. In severe nicotine addicts, the specific brain region of abnormal neural activity was observed. These findings provided new insights into the underlying neural mechanisms of different severity nicotine addicts.
[Keywords] nicotine dependence;substance addiction;visual attention network;attentional bias;functional connectivity density;magnetic resonance imaging

NIU Xiaoyu   ZHANG Yong*   YANG Zhengui   ZHANG Mengzhe   GAO Xinyu   WANG Weijian   CHENG Jingliang  

Department of Magnetic Resonance, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450002, China

Corresponding author: Zhang Y, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Key Research and Development and Promotion (Science and Technology) Project of Henan Province (No. 212102310712).
Received  2022-05-03
Accepted  2023-04-06
DOI: 10.12015/issn.1674-8034.2023.04.003
Cite this article as: NIU X Y, ZHANG Y, YANG Z G, et al. Changes of functional connectivity density in different severity of nicotine addicts: A functional magnetic resonance imaging study[J]. Chin J Magn Reson Imaging, 2023, 14(4): 11-15. DOI:10.12015/issn.1674-8034.2023.04.003.

ASMA S, SONG Y, COHEN J, et al. CDC Grand Rounds: global tobacco control[J/OL]. MMWR Morb Mortal Wkly Rep, 2014, 63(13): 277-280 [2022-01-06].
YANG Z G, ZHANG Y, CHENG J L, et al. Meta-analysis of brain gray matter changes in chronic smokers[J/OL]. Eur J Radiol, 2020, 132: 109300 [2022-05-02]. DOI: 10.1016/j.ejrad.2020.109300.
GOLDFARBMUREN K C, JACKSON N D, SAJUTHI S P, et al. Dissecting the cellular specificity of smoking effects and reconstructing lineages in the human airway epithelium[J/OL]. Nat Commun, 2020, 11(1): 2485 [2022-05-02]. DOI: 10.1038/s41467-020-16239-z.
YANG J J, YU D X, WEN W Q, et al. Tobacco smoking and mortality in Asia: a pooled meta-analysis[J/OL]. JAMA Netw Open, 2019, 2(3): e191474 [2022-05-02]. DOI: 10.1001/jamanetworkopen.2019.1474.
EKPU V U, BROWN A K. The economic impact of smoking and of reducing smoking prevalence: review of evidence[J/OL]. Tob Use Insights, 2015, 8: 1-35 [2022-01-06]. DOI: 10.4137/TUI.S15628.
WEILAND B J, SABBINENI A, CALHOUN V D, et al. Reduced executive and default network functional connectivity in cigarette smokers[J]. Hum Brain Mapp, 2015, 36(3): 872-882. DOI: 10.1002/hbm.22672.
OMOLE T, MCNEEL T, CHOI K. Heterogeneity in past-year smoking, current tobacco use, and smoking cessation behaviors among light and/or non-daily smokers[J/OL]. Tob Induc Dis, 2020, 18: 74 [2022-05-02]. DOI: 10.18332/tid/125724.
GHAHREMANI D G, POCHON J B, PEREZ DIAZ M, et al. Functional connectivity of the anterior insula during withdrawal from cigarette smoking[J]. Neuropsychopharmacology, 2021, 46(12): 2083-2089. DOI: 10.1038/s41386-021-01036-z.
KIM J I, LEE J D, HWANG H J, et al. Altered subcallosal and posterior cingulate cortex-based functional connectivity during smoking cue and mental simulation processing in smokers[J/OL]. Prog Neuropsychopharmacol Biol Psychiatry, 2020, 97: 109772 [2022-05-02]. DOI: 10.1016/j.pnpbp.2019.109772.
WANG X F, XIE D D, LIU C, et al. Study on the changes of functional connection of resting executive network in young smokers based on independent component analysis[J]. Chin J Med Phys, 2020, 37(3): 289-292. DOI: 10.3969/j.issn.1005-202X.2020.03.006.
WANG C, HUANG P Y, SHEN Z J, et al. Increased striatal functional connectivity is associated with improved smoking cessation outcomes: a preliminary study[J/OL]. Addict Biol, 2021, 26(2): e12919 [2022-05-02]. DOI: 10.1111/adb.12919.
ABULSEOUD O A, ROSS T J, NAM H W, et al. Short-term nicotine deprivation alters dorsal anterior cingulate glutamate concentration and concomitant cingulate-cortical functional connectivity[J]. Neuropsychopharmacology, 2020, 45(11): 1920-1930. DOI: 10.1038/s41386-020-0741-9.
HAN Y L, LI Y M, LUO Q, et al. Functional connectivity density alterations at resting state in neuromyelitis optica patients[J]. Chin J Magn Reson Imaging, 2018, 9(1): 33-37. DOI: 10.12015/issn.1674-8034.2018.01.007.
JANSE VAN RENSBURG K, TAYLOR A, HODGSON T, et al. Acute exercise modulates cigarette cravings and brain activation in response to smoking-related images: an fMRI study[J]. Psychopharmacology (Berl), 2009, 203(3): 589-598. DOI: 10.1007/s00213-008-1405-3.
ZHAO S Z, LI Y D, LI M, et al. 12-h abstinence-induced functional connectivity density changes and craving in young smokers: a resting-state study[J]. Brain Imaging Behav, 2019, 13(4): 953-962. DOI: 10.1007/s11682-018-9911-3.
ZHANG M Z, HUANG H Y, GAO X Y, et al. Altered inter- and intrahemispheric functional connectivity dynamics in long-term smokers[J]. Chin J Psychiatry, 2022, 55(2): 98-105. DOI: 10.3760/cma.j.cn113661-20210517-00163.
SHEN Z J, HUANG P Y, QIAN W, et al. Severity of dependence modulates smokers' functional connectivity in the reward circuit: a preliminary study[J]. Psychopharmacology (Berl), 2016, 233(11): 2129-2137. DOI: 10.1007/s00213-016-4262-5.
WU G Y, YANG S Q, ZHU L, et al. Altered spontaneous brain activity in heavy smokers revealed by regional homogeneity[J]. Psychopharmacology (Berl), 2015, 232(14): 2481-2489. DOI: 10.1007/s00213-015-3881-6.
WEN M, YANG Z, WEI Y, et al. More than just statics: Temporal dynamic changes of intrinsic brain activity in cigarette smoking [J/OL]. Addict Biol, 2021, 26(6): e13050 [2022-04-21]. DOI: 10.1111/adb.13050.
SADEGHI-ARDEKANI K, HAGHIGHI M, ZARRIN R. Effects of omega-3 fatty acid supplementation on cigarette craving and oxidative stress index in heavy-smoker males: a double-blind, randomized, placebo-controlled clinical trial[J]. J Psychopharmacol, 2018, 32(9): 995-1002. DOI: 10.1177/0269881118788806.
ADDICOTT M A, SWEITZER M M, FROELIGER B, et al. Increased functional connectivity in an Insula-based network is associated with improved smoking cessation outcomes[J]. Neuropsychopharmacology, 2015, 40(11): 2648-2656. DOI: 10.1038/npp.2015.114.
HAN S Q, WANG X, HE Z L, et al. Decreased static and increased dynamic global signal topography in major depressive disorder[J/OL]. Prog Neuropsychopharmacol Biol Psychiatry, 2019, 94: 109665 [2021-11-23]. DOI: 10.1016/j.pnpbp.2019.109665.
ZHANG J F, MAGIONCALDA P, HUANG Z R, et al. Altered global signal topography and its different regional localization in motor cortex and Hippocampus in Mania and depression[J]. Schizophr Bull, 2019, 45(4): 902-910. DOI: 10.1093/schbul/sby138.
TOMASI D, VOLKOW N D. Functional connectivity density mapping[J]. Proc Natl Acad Sci USA, 2010, 107(21): 9885-9890. DOI: 10.1073/pnas.1001414107.
SLIVER M, MONTANA G, NICHOLS T E. False positives in neuroimaging genetics using voxel-based morphometry data[J]. NeuroImage, 2011, 54(2): 992-1000. DOI: 10.1016/j.neuroimage.2010.08.049.
BEZDEK M A, GERRIG R J, WENZEL W G, et al. Neural evidence that suspense narrows attentional focus[J]. Neuroscience, 2015, 303: 338-345. DOI: 10.1016/j.neuroscience.2015.06.055.
SHMUEL A, LEOPOLD D A. Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: implications for functional connectivity at rest[J]. Hum Brain Mapp, 2008, 29(7): 751-761. DOI: 10.1002/hbm.20580.
PASSAMONTI L, LUIJTEN M, ZIAUDDEEN H, et al. Atomoxetine effects on attentional bias to drug-related cues in cocaine dependent individuals[J]. Psychopharmacology (Berl), 2017, 234(15): 2289-2297. DOI: 10.1007/s00213-017-4643-4.
MARKS K R, ALCORN J L, STOOPS W W, et al. Cigarette cue attentional bias in cocaine-smoking and non-cocaine-using cigarette smokers[J]. Nicotine Tob Res, 2016, 18(9): 1915-1919. DOI: 10.1093/ntr/ntw026.
WILCOCKSON T D W, POTHOS E M, OSBORNE A M, et al. Top-down and bottom-up attentional biases for smoking-related stimuli: comparing dependent and non-dependent smokers[J/OL]. Addict Behav, 2021, 118: 106886 [2022-01-15]. DOI: 10.1016/j.addbeh.2021.106886.
BUSCHSCHULTE A, BOEHLER C N, STRUMPF H, et al. Reward- and attention-related biasing of sensory selection in visual cortex[J]. J Cogn Neurosci, 2014, 26(5): 1049-1065. DOI: 10.1162/jocn_a_00539.
QIU Z G, WANG J J. A voxel-wise meta-analysis of task-based functional MRI studies on impaired gain and loss processing in adults with addiction[J/OL]. J Psychiatry Neurosci, 2021, 46(1): E128-E146 [2022-01-12]. DOI: 10.1503/jpn.200047.
HAVERMANS A, VAN SCHAYCK O C P, VUURMAN E F P M, et al. Nicotine deprivation elevates neural representation of smoking-related cues in object-sensitive visual cortex: a proof of concept study[J]. Psychopharmacology (Berl), 2017, 234(16): 2375-2384. DOI: 10.1007/s00213-017-4628-3.
TOMASI D, VOLKOW N D. Association between brain activation and functional connectivity[J]. Cereb Cortex, 2019, 29(5): 1984-1996. DOI: 10.1093/cercor/bhy077.
HAHN B, ROSS T J, STEIN E A. Neuroanatomical dissociation between bottom-up and top-down processes of visuospatial selective attention[J]. NeuroImage, 2006, 32(2): 842-853. DOI: 10.1016/j.neuroimage.2006.04.177.
DI CHIARA G. Role of dopamine in the behavioural actions of nicotine related to addiction[J]. Eur J Pharmacol, 2000, 393(1/2/3): 295-314. DOI: 10.1016/s0014-2999(00)00122-9.
MOGG K, FIELD M, BRADLEY B P. Attentional and approach biases for smoking cues in smokers: an investigation of competing theoretical views of addiction[J]. Psychopharmacology, 2005, 180(2): 333-341. DOI: 10.1007/s00213-005-2158-x.
LIN F C, HAN X, WANG Y, et al. Sex-specific effects of cigarette smoking on caudate and amygdala volume and resting-state functional connectivity[J/OL]. Brain Imaging Behav, 2021, 15(1): 1-13 [2022-02-17]. DOI: 10.1007/s11682-019-00227-z.
MCCARTHY J M, DUMAIS K M, ZEGEL M, et al. Sex differences in tobacco smokers: executive control network and frontostriatal connectivity[J]. Drug Alcohol Depend, 2019, 195: 59-65. DOI: 10.1016/j.drugalcdep.2018.11.023.
BAGGA D, AIGNER C S, CECCHETTO C, et al. Investigating sex-specific characteristics of nicotine addiction using metabolic and structural magnetic resonance imaging[J]. Eur Addict Res, 2018, 24(6): 267-277. DOI: 10.1159/000494260.

PREV Dynamic changes of spontaneous neural activity in the brain of patients with minimal hepatic encephalopathy: A preliminary study of resting-state functional magnetic resonance imaging
NEXT Meta analysis of correlation between characteristics of vulnerable intracranial plaque and occurrence and recurrence of ischemic stroke

Tel & Fax: +8610-67113815    E-mail: