Research On Brain Network Of Betel Nut Addicts Based On Multi-modal Image Data

Betel quid(BQ),as one of the most commonly consumed psychoactive substances,it has been considered by the World Health Organization as a human carcinogen.Long-term BQ chewing can make people addicted.It is generally believed that substance addiction or dependence is associated with abnormal functional and structural organization in the individual's brain.The purpose of this study is to identify abnormalities in the brain function and structure and network of betel quid dependence through image data of multiple modalities.This study includes data on two modalities of 25 betel quid dependence individuals and 29 healthy controls.Respectively,resting state functional magnetic resonance imaging(rs-fMRI)and diffusion tensor imaging.Among them,the rs-fMRI data includes two scans before betel quid chewing and after betel quid chewing.Based on rs-fMRI data,we calculated the values of two brain function activity indicators,Amplitude of low frequency fluctuation(ALFF)and regional homogeneity(ReHo).In addition,we constructed a brain function connection network using Pearson correlation coefficients.We performed ALFF and ReHo and brain function networks separately comparison between betel quid dependence group and healthy control group;For diffuse tensor imaging data,we mainly used a combination ofTract-based spatial statisticss(TBSS)and white mass spectrometry to investigate altered white matter integrity associated with betel quid dependence individuals,and to establish a network of brain anatomy connections through deterministic fiber tracking to explore the brain regions Abnormalities of white matter fiber bundles.The results show that the effects of betel quid chewing mainly affect brain function activities and brain network in the occipital and parietal lobe areas,especially the precuneus of the parietal lobe can be used as a biomarker of betel quid dependence.At the same time,through comparison of white matter metrics,we found that compared with healthy controls,betel quid dependence individuals exhibited less fractional anisotropy(FA)and higher mean diffusivity(MD)in left anterior limb of internal capsule and left inferior cerebellar,indicating that the white matter integrity of betel quid dependence individuals has changed.In addition,fiber tracking further verified this result.When analyzing the structural network,we found that there are multiple damaged connections in betel quid dependece individuals.In particular,it not only exist abnormal connenction between the left caudate nucleus and the cingulate gyrus,but also between the left caudate nucleus and the left thalamus.Our results show that betel quid chewing can cause certain damage to the function and structure of the brain.Finally,combining the data of the two modalities,we constructed afunctional network and a probabilistic fiber tracking structure network for each subject,and used the connection of the network as a feature to classify betel quid dependence individuals through support vector machines.The results show that the fusion of multi-modal network connections as features has a higher classification accuracy than the single-modal ones,thus providing help for clinical diagnosis.The research in this article gives us an opportunity to understand the neurophysiology related to betel quid,and provides support for the clarification and improvement of betel quid dependence mechanism.