PurposeThe aim of this study was to investigate and compare impulsiveness, negative emotion, cognitive function, and P300 components among gamma-hydroxybutyrate (GHB)-addicted patients, heroin-dependent patients, and methadone maintenance treatment (MMT) subjects.MethodsA total of 48 men including 17 GHB addicts, 16 heroin addicts, 15 MMT subjects, and 15 male mentally healthy controls (HC) were recruited. All subjects were evaluated for symptoms of depression, anxiety, impulsiveness, and cognitive function through the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder 7-item (GAD-7), the Barratt Impulsiveness Scale version II (BIS-II), the Beijing version of the Montreal Cognitive Assessment (BJ-MoCA), the behavioral test (response time), and event-related potential P300 detection.Results(1) The mean scores of BIS-II in the GHB addiction group, heroin dependence group, and MMT group were significantly higher than those of the HC group (F = 30.339, P = 0.000). (2) The total scores of BJ-MOCA in GHB addiction group was the worst among the four groups, followed by heroin addiction, MMT group and HC group (F = 27.880, P = 0.000). (3) The response time in the GHB addiction group was the longest among the four groups, followed by the heroin addiction, MMT, and HC groups (F = 150.499, P = 0.000). (4) The amplitude and latency of P300 in GHB addiction subjects were significantly lower and longer than those of the MMT group and the HC group. (5) For the three types of addiction, the P300 amplitudes at Fz, Cz, Pz, T5, and T6 were negatively correlated with the scores of GAD-7, PHQ-9, and BIS-II; the P300 latencies were positively correlated with the response time and negatively correlated with the scores of the BJ-MoCA.ConclusionPeople with an addiction were likely to have increased impulsiveness. The cognitive function of the GHB and heroin-addicted subjects, including the heroin detoxification and the MMT groups, was severely impaired, especially for the GHB-addicted patients. The impairment manifested as abnormalities of BJ-MoCA, response time, and P300 components.

ObjectiveTo investigate the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on attention cue reactivity in male patients with alcohol use disorder (AUD) after acute withdrawal.MethodsA total of 90 male patients with AUD who were hospitalized were enrolled and divided into study and waiting groups by a random number table. During the study, 18 patients dropped out. After the alcohol withdrawal symptoms were eliminated, the study group received high-frequency rTMS at 10 Hz for 14 consecutive days, and the waiting group was administrated by sham rTMS. All subjects were evaluated for attention cue reactivity, impulsiveness, cognitive function by oddball paradigm, Barratt Impulsiveness Scale version II (BIS-II), and the Montreal Cognitive Assessment (MoCA) at baseline and after true or sham rTMS.Results1. There was no significant difference between the study and the waiting groups regarding the drinking level, cognition level, and demographic data at baseline. 2. In the oddball paradigm, both for alcohol-related and non-alcohol-related cues, the response times were significantly shorter in the study group after rTMS treatment than in the waiting-for-treatment group, either between the two groups or within the study group. There was no significant difference in the accuracy rate for alcohol-related and non-alcohol-related cues between the two groups or within the study group after rTMS intervention. 3. The total score of MoCA was significantly increased, and the total score of BIS-II was significantly decreased in the study group after rTMS treatment, either between the two groups or within the study group.ConclusionThe results suggested that high-frequency rTMS could improve the attention bias of alcohol-related cues and impulsivity for patients with AUD.

PurposeThe purpose of this study is to explore the association of P300 components with clinical characteristics and efficacy of pharmacotherapy in alcohol use disorder (AUD).MethodsOne hundred fifty-one AUD patients and 96 healthy controls were recruited and evaluated for the symptoms of depression, anxiety, sleep, and cognitive function by the Alcohol Use Disorders Identification Test (AUDIT), the 9-item Patient Health Questionnaire (PHQ-9), the 7-item Generalized Anxiety Disorder scale (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), Digit Symbol Substitution test (DSST), and event-related potential P300, which is one of the averaged scalp electroencephalography responses time-locked to specific events. Among the AUD group, 101 patients finished an 8-week pharmacotherapy and were evaluated for the above data at post-intervention.Results1. At baseline, AUD patients had higher scores of AUDIT, PHQ-9, GAD-7, PSQI, and P300 latency at Cz, Pz, and Fz and lower DSST score and smaller P300 amplitudes at Fz, Cz, and Pz compared with controls. P300 components correlated significantly with alcohol dose and score of AUDIT, PHQ-9, GAD-7, PSQI, and DSST. 2. After 8 weeks' treatment, there were significant changes for the P300 components; alcohol dose; and score of AUDIT, PHQ-9, GAD-7, PSQI, and DSST. Variables at baseline, including P300 amplitudes at Fz, Cz, and Pz; latency of Fz and Pz; alcohol dose; and scores of PHQ-9, GAD-7, PSQI, and DSST, were significantly associated with changes of reduction rate of AUDIT scores. However, P300 amplitudes at Fz, Cz, and Pz in AUD patients after 8-week treatment were still significantly shorter than healthy controls (HCs), and P300 latencies at Fz, Cz, and Pz were significantly longer than HCs. 3. When validated area under the receiver operating characteristic curve (AUC) was over 0.80, the baseline variables including amplitudes at Cz and Pz, alcohol dose, and scores of PSQI could predict the changes of reduction rate of AUDIT score.ConclusionP300 amplitudes and latencies at Fz, Cz, and Pz could be used as biological markers for evaluating the clinical characters and severity of AUD. P300 amplitudes at Cz and Pz, sleep condition, and cognitive function at baseline could predict the efficacy of pharmacotherapy for AUD patients.