OBJECTIVE: Alcohol causes damage to the brain and is associated with various functional impairments. However, much of the brain damage can be reversed by abstaining for enough time. This study aims to investigate the patterns and degrees of brain function in abstinent patients with alcohol dependence by using resting-state functional connectivity. METHODS: 26 male patients with alcohol dependence (alcohol group) and 28 age-matched male healthy volunteers (control group) were recruited from a mental hospital and the community, respectively. Using 3T MRI scan data, the resting-state functional connectivity of the task-negative and task-positive networks was determined and compared between the groups. RESULTS: There were no significant group differences in the resting-state functional connectivity in the default mode or in the salience and sensorimotor networks. Compared with the control group, the alcohol group showed significantly lower functional connectivity in the executive control network, especially in the cingulo-opercular network and, in some regions of interest, the dorsal attention network. CONCLUSION: This finding suggests that some brain networks do not normalize their functions after abstinence from drinking, and these results may be helpful in future research to investigate the mechanisms for craving alcohol and alcohol relapse prevention.
Alcoholism* ; Brain ; Craving ; Drinking ; Executive Function ; Healthy Volunteers ; Hospitals, Psychiatric ; Humans ; Magnetic Resonance Imaging ; Male ; Secondary Prevention

OBJECTIVE: The structural alteration of brain shown in patients with alcohol use disorder (AUD) can originate from both alcohol effects and genetic or developmental processes. We compared surface-based parameters of patients with AUD with healthy controls to prove the applicability of surface-based morphometry with head size correction and to determine the areas that were sensitive to brain alteration related to AUD. METHODS: Twenty-six abstinent male patients with AUD (alcohol group, mean abstinence=13.2 months) and twenty-eight age-matched healthy participants (control group) were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Surface-based parameters were determined by using FreeSurfer. RESULTS: Every surface-based parameter of the alcohol group was lower than the corresponding control group parameter. There were large group differences in the whole brain, grey and white matter volume, and the differences were more prominent after head size correction. Significant group differences were shown in cortical thicknesses in entire brain regions, especially in parietal, temporal and frontal areas. There were no significant group differences in surface areas, but group difference trends in surface areas of the frontal and parietal cortices were shown after head size correction. CONCLUSION: Most of the surface-based parameters in alcohol group were altered because of incomplete recovery from chronic alcohol exposure and possibly genetic or developmental factors underlying the risk of AUD. Surface-based morphometry with controlling for head size is useful in comparing the volumetric parameters and the surface area to a lesser extent in alcohol-related brain alteration.
Brain* ; Head ; Healthy Volunteers ; Hospitals, Psychiatric ; Humans ; Inpatients ; Magnetic Resonance Imaging ; Male* ; Neuroimaging* ; Parietal Lobe ; Rabeprazole ; White Matter

OBJECTIVES: The power spectral analysis of electroencephalogram has been widely used to reveal the pathophysiology of the alcoholic brain. However, the results were not consistent and the three dimensional study can be hardly found. The purpose of this study was to investigate characteristics of the three dimensional electroencephalographic (EEG) activity of alcohol dependent patients using standardized low resolution electromagnetic tomography (sLORETA). METHODS: The participants consisted of 30 alcohol dependent patients and 30 normal healthy controls. All the participants were males who had refrained from alcohol at least one month and were not taking any medications. Thirty two channel EEG data was collected in the resting state with eyes-closed condition during 30 seconds. The three dimensional data was compared between two groups using sLORETA for delta, theta, alpha, beta1, beta2, and beta3 frequency bands. RESULTS: sLORETA revealed significantly increased brain cortical activity in alpha, beta1, beta2, and beta3 bands each in alcohol dependent patients compared to normal controls. The voxels showing the maximum significance were in the left transverse temporal gyrus, left superior temporal gyrus, left anterior cingulate, and left fusiform gyrus in alpha, beta1, beta2, and beta3 bands respectively. CONCLUSIONS: These results suggest that chronic alcohol intake may cause neurophysiological changes in cerebral activity. Therefore, the measuring of EEG can be helpful in understanding the pathophysiology of cognitive impairements in alcohol dependence.
Alcoholics ; Alcoholism ; Brain ; Electroencephalography ; Functional Neuroimaging ; Humans ; Magnets ; Male

OBJECTIVES: Total intracranial volume (TIV) is a major nuisance of neuroimaging research for interindividual differences of brain structure and function. Authors intended to prove the reliability of the atlas scaling factor (ASF) method for TIV estimation in FreeSurfer by comparing it with the results of manual tracing as reference method. METHODS: The TIVs of 26 normal children and 26 children with attention-deficit hyperactivity disorder (ADHD) were obtained by using FreeSurfer reconstruction and manual tracing with T1-weighted images. Manual tracing performed in every 10th slice of MRI dataset from midline of sagittal plane by one researcher who was blinded from clinical data. Another reseacher performed manual tracing independently for randomly selected 20 dataset to verify interrater reliability. RESULTS: The interrater reliability was excellent (intraclass coefficient = 0.91, p < 7.1e-07). There were no significant differences of age and gender distribution between normal and ADHD groups. No significant differences were found between TIVs from ASF method and manual tracing. Strong correlation between TIVs from 2 different methods were shown (r = 0.90, p < 2.2e-16). CONCLUSIONS: The ASF method for TIV estimation by using FreeSurfer showed good agreement with the reference method. We can use the TIV from ASF method for correction in analysis of structural and functional neuroimaging studies with not only elderly subjects but also children, even with ADHD.