Objective: To explore the neuromechanism of nicotine dependence, structural covariation networks (SCNs) based on voxel-based morphometry (VBM) were used to study the synergistic changes in gray matter volume in different cerebral cortices of nicotine dependent individuals. Methods: During the period from August 2016 to February 2018, a total of 118 long-term smokers and 57 non-smoking healthy controls (both 18-55 male volunteers) through online platforms and leaflets were recruited. The subjects were scanned with SIEMENS Skyro 3.0T magnetic resonance scanner and underwent routine MRI sequence (preliminary elimination of intracranial lesions) and 3D-T1 (3D-mprage) sequence structure. Two imaging experts used Matlab software platform to carry on segmentation by using SPM8, and to find out the differences between the two groups of brain regions, and differences in brain regions as region of interest (ROI) structure association network analysis. Results: The gray matter volume (GMV) of the right anterior central gyrus and the left inferior parietal lobe in the smoking group decreased(voxels size were 55 and 284, respectively), and no gray matter volume (GMV) area increased. The network structure of covariant analysis found that when the inferior parietal lobe as the seed points, the smoking group showed a rising trend in left parietal lobe and left temporal pole, bilateral middle temporal gyrus, left postcentral gyrus and right middle frontal gyrus gray matter volume, and a downtrend in the right side of the left medial frontal gyrus, superior parietal lobe, bilateral temporal gyrus, left cingulate gyrus and left cerebellum (central) compared with the control group. Conclusion: In long-term smokers, there is a volume change of gray matter in the brain structure. Abnormal changes in the structure covariant network of the inferior parietal lobe can lead to impaired brain function in nicotine dependent patients.
Objective: To explore the neuromechanism of nicotine dependence, structural covariation networks (SCNs) based on voxel-based morphometry (VBM) were used to study the synergistic changes in gray matter volume in different cerebral cortices of nicotine dependent individuals. Methods: During the period from August 2016 to February 2018, a total of 118 long-term smokers and 57 non-smoking healthy controls (both 18-55 male volunteers) through online platforms and leaflets were recruited. The subjects were scanned with SIEMENS Skyro 3.0T magnetic resonance scanner and underwent routine MRI sequence (preliminary elimination of intracranial lesions) and 3D-T1 (3D-mprage) sequence structure. Two imaging experts used Matlab software platform to carry on segmentation by using SPM8, and to find out the differences between the two groups of brain regions, and differences in brain regions as region of interest (ROI) structure association network analysis. Results: The gray matter volume (GMV) of the right anterior central gyrus and the left inferior parietal lobe in the smoking group decreased(voxels size were 55 and 284, respectively), and no gray matter volume (GMV) area increased. The network structure of covariant analysis found that when the inferior parietal lobe as the seed points, the smoking group showed a rising trend in left parietal lobe and left temporal pole, bilateral middle temporal gyrus, left postcentral gyrus and right middle frontal gyrus gray matter volume, and a downtrend in the right side of the left medial frontal gyrus, superior parietal lobe, bilateral temporal gyrus, left cingulate gyrus and left cerebellum (central) compared with the control group. Conclusion: In long-term smokers, there is a volume change of gray matter in the brain structure. Abnormal changes in the structure covariant network of the inferior parietal lobe can lead to impaired brain function in nicotine dependent patients.