Abnormal Degree Centrality In Chronic Users Of Codeine-containing Cough Syrups

PurposeIn this study,using resting state functional magnetic resonance imaging technology,Degree Centrality analysis method was used to explore the intrinsic abnormal functional connectivity pattern of whole-brain functional networks at the voxel level in chronic users of Codeine-containing cough syrups(CCS).In addition,we also correlated the degree centrality(DC)changes to the Barratt Impulsiveness Scale(BIS-11)total score and Clinical characteristics to explore the neural mechanism to provide a possible imaging basis.Materials and MethodsThis prospective study was approved by the Ethics Committee of Guangdong Second Provincial General Hospital.Written informed consent was obtained from all subjects.We enrolled 72 right-handed participants,including 34 control subjects and 38 CCS-dependent individuals,in this study.The CCS-dependent individuals were recruited from the patients seeking treatment at Addiction Medicine Division of Guangdong Second Provincial General Hospital.All patients were screened based on the DSM-IV criteria from the medical history,and received a urine test and an interview on the same day.The exclusion criteria for all participants included central nervous system diseases,schizophrenia,bipolar disorder,prior significant head trauma,positive human immunodeficiency virus(HIV)status,diabetes,hepatitis C,other major medical illness,and left-handedness.The inclusion criteria for the control subjects were absence of diagnosis of any type of substance abuse or dependence.All MRI datasets were scanned using a Philips Achieva 1.5 T Nova dual MR scanner at the Department of Medical Imaging,Guangdong Second Provincial General Hospital.The R-fMRI dataset[22 axial slices,repetition time(TR)/echo time(TE)=2000 ms/50 ms,matrix = 64x64,field of view(FOV)= 230 x 230 mm2,slice thickness = 4.5 mm without gap,flip angle = 90°]were acquired using an echo planar imaging(EPI)sequence.Each functional run contained 240 volumes(8 min)(the slices were approximately along the anterior commissure-posterior commissure(AC-PC)line and covered approximately 230 to 60 in the inferosuperior direction),and the subjects were asked to lie quietly with their eyes closed and to avoid eye movement,thinking of anything specific,or falling asleep while in the scanner.For the calculation of DC,we performed voxel-wise voxel-based whole-brain correlation analysis on the preprocessed fMRI data.The time course of each voxel in each brain was correlated to every other voxel time course in the GM mask.Thus,we can acquire an n × n matrix of Pearson correlation coefficients between any pair of voxels,where n is the voxel number of the whole-brain mask.We then converted the Pearson correlation data to normally distributed Fisher Z-scores and constructed the whole-brain functional network by thresholding each correlation at r>0.25.The threshold is the default setting in the calculation of the DC map.Only positive Pearson correlation coefficients were considered in the study.In the REST software,a two-sample T-test was used to statistically analyze the DC value differences between the two groups.A correction for multiple comparison was performed by a Monte Carlo simulation using the AlphaSim program.Monte Carlo simulation determines the random distribution of gray matter mass for a given voxel threshold.According to their distribution,the statistical threshold is set to p-value less than 0.01,mass greater than 60 voxels,and voxel level P-value less than 0.001.ResultsAfter the two-sample t test analysis,significantly increased DC values within right hippocampus and right pallidum and significantly decreased DC values within left IPL and left middle temporal lobe and precuneus were found in CCS-dependent individuals compared to the control group.We found the decreased average DC value of left IPL in CCS-dependent individuals was negatively correlated with the subscale of attentional impulsivity,and positively correlated with the age of first use of CCS.ConclusionThe R-fMRI study suggests that the abnormal intrinsic disconnectivity pattern of whole-brain functional networks may further improve our understanding about the neural substrates of abnormalities of the cognitive control circuit,the reward circuit,and the learning and memory circuit in CCS-dependent individuals.