Abstract
Background: Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry.Methods: Traditional voxel-based morphometry has continuously contributed to finding smoking addiction-related regions on structural magnetic resonance imaging. However, voxel-based morphometry has its inherent limitations. In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter volume in heavy smokers.Results: Our proposed method yielded a voxel-wise accuracy of at least 81% for classifying heavy smokers from healthy controls. The identified regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus (bilateral), insula (left), anterior and median cingulate gyri, and precuneus (left).Conclusions: Our results suggested that several regions, which were seldomly reported in voxel-based morphometry analysis, might be latently correlated with smoking addiction. Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment. Multivoxel pattern analysis can be efficient in locating brain discriminative regions which were neglected by voxel-based morphometry.
Highlights
Tobacco smoking in the form of cigarettes continues to be the leading cause of preventable illness and mortality in the world [1]
Several cortical and subcortical regions demonstrated a strong classification ability with gray matter (GM) differences between heavy smokers and healthy controls (HCs). These regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus, insula, anterior and median cingulate gyri (ACG and MCG), and precuneus
Traditional univariate studies prior to this research have constantly discovered that heavy smokers shared similar GM alterations in the cingulum, thalamus, cerebellum, prefrontal gyrus, and precuneus [9, 15,16,17,18, 31]
Summary
Tobacco smoking in the form of cigarettes continues to be the leading cause of preventable illness and mortality in the world [1]. Related neuroimaging studies suggested that the numerous toxic chemicals contained in a cigarette, especially nicotine, could promote potential brain afflictions in chronic cigarette smokers [8, 9]. Apart from these serious public health problems, 78% of smokers who expressed willingness to quit smoking reported a relapse situation in China, and the percentage in America is currently 80% [10, 11], indicating the ineffectiveness of existing cessation treatments. Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry
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