ArticleBrain imaging and behavior2022
Assessment of brain connectome alterations in male chronic smokers using structural and generalized q-sampling MRI.
Article in Brain imaging and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Network localization of gray matter alterations in chronic smokers using the normative functional connectome.Frontiers in public health · 2026Article
- Neural Networks and Chemical Messengers: Insights into Tobacco Addiction.Brain topography · 2025Article
- An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset.PLoS genetics · 2023Article
- Association of smoking with brain gray and white matter volume: a Mendelian randomization study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
An association has been shown between chronic cigarette smoking and structural abnormalities in the brain areas related to several functions relevant to addictive behavior. However, few studies have focused on the structural alternations of chronic smoking by using magnetic resonance imaging (MRI). Also, it remains unclear how structural alternations are associated with tobacco-dependence severity and the positive/negative outcome expectances. The q-sampling imaging (GQI) is an advanced diffusion MRI technique that can reconstruct more precise and consistent images of complex oriented fibers than other methods. We aimed to use GQI to evaluate the impact of the neurological structure caused by chronic smoking. Sixty-seven chronic smokers and 43 nonsmokers underwent a MRI scan. The tobacco dependence severity and the positive/negative outcome expectancies were assessed via self-report. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among groups. Chronic smokers had smaller GM and WM volumes in the bilateral frontal lobe and bilateral frontal region. The GM/WM volumes correlated with dependence severity and outcome expectancies in the brain areas involving high-level functions. Chronic smokers had shape changes in the left hippocampal head and tail and the inferior brain stem. Poorer WM integrity in chronic smokers was found in the left middle frontal region, the right superior fronto-occipital fasciculus, the right temporal region, the left parahippocampus, the left anterior internal capsule, and the right inferior parietal region. WM integrity correlated with dependence severity and outcome expectancies in brain areas involving high-level functions. Chronic smokers had decreased local segregation and global integration among the brain regions and networks. Our results provide further evidence indicating that chronic smoking may be associated with brain structure and connectivity changes.
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