Virtual agents among participants with methamphetamine use disorders: Acceptability and usability study.

INTRODUCTION: While the potential future role of virtual agents (VAs) in treating addiction is promising, participants' attitudes toward the use of VAs in psychotherapy remain insufficiently investigated. This lack of investigation could pose barriers to the adoption of VA-led psychotherapy for people with substance use disorders (SUD). This research aims to explore the acceptability and usability of VAs for people with methamphetamine use disorder. METHODS: Following a single session of psychotherapy led by VAs through the Echo-app, a group of 49 individuals actively seeking treatment for current DSM-V substance dependence (with a mean age of 39.06 ± 8.02) completed self-administered questionnaires and participated in focus group interviews. These questionnaires aimed to investigate participants' preference regarding the type of psychotherapy and their willingness to engage in VA-led psychotherapy, taking into account their diverse psychological needs. RESULTS: Quantitative data were subjected to analysis through both descriptive and inferential statistical methods. Interestingly, participants exhibited a significantly higher acceptability for traditional face-to-face psychotherapy compared to email-based psychotherapy (p = 0.042), but there was no statistically significant difference between their acceptance of traditional psychotherapy and VA-led psychotherapy (p = 0.059). The questionnaire outcomes indicated participants' willingness to engage in VA-led psychotherapy for purposes such as relapse prevention intervention, addressing emotional issues, managing somatic experiences, and facilitating social and family functional recovery. Furthermore, the participants' attitudes toward VA-led psychotherapy were predicted by factors including the need for anxiety-focused psychotherapy (p = 0.027; OR [95%CI] = 0.14[0.03,0.80]), the presence of chronic somatic diseases (p = 0.017; OR [95%CI] = 13.58[1.59,116.03]), and marital status (p = 0.031; OR [95%CI] = 5.02[1.16,21.79]). DISCUSSION: Through the interviews, the study uncovered the factors that either supported or hindered participants' experiences with VA-led psychotherapy, while also gathering suggestions for future improvements. This research highlights the willingness and practicality of individuals with SUD in embracing VA-led psychotherapy. The findings are anticipated to contribute to the refinement of VA-led tools to better align with the preferences and needs of the users.

Enhanced Beta2-band Oscillations Denote Auditory Hallucination in Schizophrenia Patients and a Monkey Model of Psychosis.

An electroencephalographic (EEG) signature of auditory hallucinations (AHs) is important for facilitating the diagnosis and treatment of AHs in schizophrenia. We recorded EEG from 25 schizophrenia patients with recurrent AHs. During the period of AHs, EEG recordings exhibited significantly elevated beta2-band power in the temporal region, as compared to those recorded in the absence of AHs or during stimulation with verbal sounds. We further generated methamphetamine-treated rhesus monkeys exhibiting psychosis-like behaviors, including repetitive sudden searching actions in the absence of external intrusion, suggesting the occurrence of AHs. Epidural EEG beta2-band power in the temporal region of these monkeys was enhanced immediately after methamphetamine treatment and positively correlated with the frequency of sudden searching actions. Thus, the enhancement of temporal beta2-band oscillations represents a signature for AHs in both patients and a monkey model of psychosis, and this monkey model can be used for developing closed-loop neuromodulation approaches for the treatment of refractory AHs in schizophrenia.

Metabolic and functional substrates of impulsive decision-making in individuals with heroin addiction after prolonged methadone maintenance treatment.

Elevated impulsivity has been frequently reported in individuals with opioid addiction receiving methadone maintenance therapy (MMT), but the underlying neural mechanisms and cognitive subprocesses are not fully understood. We acquired functional magnetic resonance imaging (fMRI) data from 37 subjects with heroin addiction receiving long-term MMT and 33 healthy controls who performed a probabilistic reversal learning task, and measured their resting-state brain glucose using fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET). Subjects receiving MMT exhibited significantly elevated self-reported impulsivity, and computational modeling revealed a marked impulsive decision bias manifested as switching more frequently without available evidence. Moreover, this impulsive decision bias was associated with the dose and duration of methadone use, irrelevant to the duration of heroin use. During the task, the switch-related hypoactivation in the left rostral middle frontal gyrus was correlated with the impulsive decision bias while the function of reward sensitivity was intact in subjects receiving MMT. Using prior brain-wide receptor density data, we found that the highest variance of regional metabolic abnormalities was explained by the spatial distribution of µ-opioid receptors among 10 types of neurotransmitter receptors. Heightened impulsivity in individuals receiving prolonged MMT is manifested as atypical choice bias and noise in decision-making processes, which is further driven by deficits in top-down cognitive control, other than reward sensitivity. Our findings uncover multifaceted mechanisms underlying elevated impulsivity in subjects receiving MMT, which might provide insights for developing complementary therapies to improve retention during MMT.

An exploratory study on the 10-year dynamic changes of mental health policy development and media stigma reporting in China (2011-2020).

BACKGROUND: China has introduced a large number of national mental health policies over the past decade. However, few studies have touched on what changes the policies brought to the media. AIMS: This study aimed to investigate the relationship between stigma reports, classifications of mental disorders (SMI: severe mental illness vs. CMD: common mental disorders) and sources of information (mental health professionals vs. non-mental health professionals) from 2011 to 2020 in China Daily, an established official media of China. METHOD: This study consists of policy review and media review. The policy review reviewed the media management content in Chinese national plans, policies, and laws on mental health from 2011 to 2020. China Daily news articles reporting mental illness-related topics were included in this study as the media material. After a two-step review, the eligible news articles were coded with a structured codebook. The proportion and frequency of stigma depiction of mental disorders, classifications of mental disorders and source of information were counted by year. Chi-test was undertaken to determine the relationship between stigma reports and different classifications of mental disorders and sources of information. An exploratory analysis was conducted to explore the changes in depiction around time points of policy publications. RESULTS: The number of anti-stigmatizing articles increased significantly from 2011 to 2020. There is a statistical difference in the proportion of stigmatizing codes between articles featuring SMI and CMD (χ2 = 44.56, p < .001) and different sources of information (χ2 = 78.49, p < .001). And the statistical difference remained over the decade. CONCLUSION: The results of the research indicate that the media may have alleviated the problem of stigma. But the subtle stigmatization still exists, which needs joint efforts of the government and media.

Network analysis of internet addiction and sleep disturbance symptoms.

BACKGROUND: Internet addiction (IA) is a behavioral addiction to problematic internet use. IA is associated with poorer sleep quality. Few studies to date, however, have explored the interactions between symptoms of IA and symptoms of sleep disturbance. This study uses network analysis to identify bridge symptoms by analyzing these interactions in a large sample of students. METHOD: We recruited 1977 university students to participate in our study. Each student completed the Internet Addiction Test (IAT) and the Pittsburgh Sleep Quality Index (PSQI). We used these collected data for network analysis to identify the bridge symptoms in the IAT-PSQI network by calculating the bridge centrality. Furthermore, the closest symptom connected with the bridge symptom was found to identify the comorbidity mechanisms. RESULTS: The core symptom of IA and the sleep disturbance network was "I08" (Study efficiency suffers due to internet use). The bridge symptoms between IA and sleep disturbance were "I14" (Surfing the internet late instead of sleeping), "P_DD" (Daytime dysfunction), and "I02" (Spending much time online instead of socializing in real life). Among the symptoms, "I14" had the highest bridge centrality. The edge connecting nodes "I14" and "P_SDu" (Sleep duration) had the strongest weight (0.102) around all the symptoms of sleep disturbance. Nodes "I14" and "I15" (Thinking about online shopping, games, social networking, and other network activities when unable to access the internet) had the strongest weight (0.181), connecting all the symptoms of IA. CONCLUSIONS: IA leads to poorer sleep quality, most likely by shortening sleep duration. Preoccupation with and craving the internet while being offline may lead to this situation. Healthy sleep habits should be learned, and craving may be a good point at which to treat the symptoms of IA and sleep disturbance.

Decreased inter-brain synchronization in the right middle frontal cortex in alcohol use disorder during social interaction: An fNIRS hyperscanning study.

BACKGROUND: Alcohol use disorder (AUD) is a widespread mental disorder and has thrust a heavy burden on the health system all over the world. Social cognition and function are reported to be impaired in AUD, but its neural mechanism is rarely investigated. The current study attempts to fill this gap. METHODS: 28 subjects with AUD and 36 healthy controls (HC) were recruited in this study and were paired into 14 AUD dyads and 18 HC dyads. The drinking problems, depression, anxiety, and impulsivity of subjects were measured. Each dyad completed cooperation and competition tasks with simultaneous frontal functional near-infrared spectroscopy (fNIRS) hyperscanning recording. The inter-brain synchronization (IBS) in the frontal cortex was calculated for each dyad and compared between AUD and HC. The significantly altered IBS in AUD was correlated with clinical measures to explore possible influencing factors. RESULTS: The IBS in the right middle frontal cortex was significantly decreased in AUD under both cooperation (t = -2.257, P = 0.028) and competition (t = -2.488, P = 0.016) task. The IBS during the cooperation task in the right middle frontal cortex in AUD was negatively correlated with non-planning impulsivity (r = -0.673, P = 0.006). LIMITATIONS: This study used cross-sectional data, which limited the causal inference. The synchronization between other brain regions besides the frontal cortex should be further explored in patients with AUD. CONCLUSION: The current study could provide new insights into the neural mechanism of social dysfunction in AUD and facilitate clinical intervention in future practice.

Virtual Digital Psychotherapist App-Based Treatment in Patients With Methamphetamine Use Disorder (Echo-APP): Single-Arm Pilot Feasibility and Efficacy Study.

BACKGROUND: Substance use disorder is one of the severe public health problems worldwide. Inequitable resources, discrimination, and physical distances limit patients' access to medical help. Automated conversational agents have the potential to provide in-home and remote therapy. However, automatic dialogue agents mostly use text and other methods to interact, which affects the interaction experience, treatment immersion, and clinical efficacy. OBJECTIVE: The aim of this paper is to describe the design and development of Echo-APP, a tablet-based app with the function of a virtual digital psychotherapist, and to conduct a pilot study to explore the feasibility and preliminary efficacy results of Echo-APP for patients with methamphetamine use disorder. METHODS: Echo-APP is an assessment and rehabilitation program developed for substance use disorder (SUD) by a team of clinicians, psychotherapists, and computer experts. The program is available for Android tablets. In terms of assessment, the focus is on the core characteristics of SUD, such as mood, impulsivity, treatment motivation, and craving level. In terms of treatment, Echo-APP provides 10 treatment units, involving awareness of addiction, motivation enhancement, emotion regulation, meditation, etc. A total of 47 patients with methamphetamine dependence were eventually enrolled in the pilot study to receive a single session of the Echo-APP-based motivational enhancement treatment. The outcomes were assessed before and after the patients' treatment, including treatment motivation, craving levels, self-perception on the importance of drug abstinence, and their confidence in stopping the drug use. RESULTS: In the pilot study, scores on the Stages of Change Readiness and Treatment Eagerness Scale and the questionnaire on motivation for abstaining from drugs significantly increased after the Echo-APP-based treatment (P<.001, Cohen d=-0.60), while craving was reduced (P=.01, Cohen d=0.38). Patients' baseline Generalized Anxiety Disorder-7 assessment score (ß=3.57; P<.001; 95% CI 0.80, 2.89) and Barratt Impulsiveness Scale (BIS)-motor impulsiveness score (ß=-2.10; P=.04; 95% CI -0.94, -0.02) were predictive of changes in the patients' treatment motivation during treatment. Moreover, patients' baseline Generalized Anxiety Disorder-7 assessment score (ß=-1.607; P=.03; 95% CI -3.08, -0.14), BIS-attentional impulsivity score (ß=-2.43; P=.004; 95% CI -4.03, -0.83), and BIS-nonplanning impulsivity score (ß=2.54; P=.002; 95% CI 0.98, 4.10) were predictive of changes in craving scores during treatment. CONCLUSIONS: Echo-APP is a practical, accepted, and promising virtual digital psychotherapist program for patients with methamphetamine dependence. The preliminary findings lay a good foundation for further optimization of the program and the promotion of large-scale randomized controlled clinical studies for SUD.

Changes of internet behavior of adolescents across the period of COVID-19 pandemic in China.

During the COVID-19 pandemic, internet use and gaming of adolescents had been elevated. On the one hand, internet use and gaming in the period was a good approach to killing quarantined time. However, the increased use of the internet and game of adolescents may also increase the risk of internet addiction. This study aimed to describe the internet behavior changes of adolescents and to understand the impact of clinical features on internet addiction after the adolescents back to school in COVID-19 period. We conducted a cross-sectional cohort study using data collected through online investigation in China. Six hundred and twenty-five adolescents completed the online survey. Results indicated that internet addiction, having gaming use behaviors, Strengths and Difficulties Questionnaire (SDQ) Conduct subscale scores and the SDQ Prosocial subscale scores before the COVID-19 outbreak were significant in predicting the internet addiction after the adolescents back to school. The proportion of internet addiction and gaming behaviors among adolescents in China was changed across the COVID-19 pandemic. Clinical features before the COVID-19 pandemic could predict Internet addiction risk after the adolescents back to school.

The preliminary efficacy of virtual agent-assisted intelligent rehabilitation treatment (Echo app v2.0) in patients with alcohol use disorders: Study protocol for a randomized controlled trial.

Background: Alcohol use disorder (AUD) is one of the most common substance use disorders. People with AUD are in great need of highly accessible and comprehensive management, involving medicine, exercise, and psychotherapy. However, due to limited resources, providing comprehensive treatment for every patient is challenging. Virtual agent-assisted intelligent rehabilitation treatment can improve the accessibility of comprehensive management. Objectives: This randomized controlled trial aims to test whether the virtual agent-assisted intelligent rehabilitation treatment (Echo-app-v2.0) plus treatment as usual (TAU) has greater efficacy than only TAU in AUD. Methods: One hundred participants with AUD will be recruited and randomly assigned to either TAU or virtual agent-assisted intelligent rehabilitation treatment plus TAU based on the 1:1 ratio. The virtual agent-assisted intelligent rehabilitation treatment is delivered by the Echo app v2.0 developed by our research team. Participants will be assessed at baseline, week 4 of treatment, one month, and three months after the end of treatment. The primary outcome is the participants' craving for alcohol, measured by Visual Analogue Scale. Other outcomes include the use of alcohol, motivation for treatment, coping style, depression, anxiety, impulsivity, stress, and sleep quality. Discussion: The virtual agent, with vivid human image, high privacy, and the ability to interact with users, has the potential to play an important role in the delivery of digital psychotherapy. The development of Echo app v2.0 has the possibility to raise the availability of comprehensive treatment for people with AUD.

Addiction Symptom Network of Young Internet Users: Network Analysis.

BACKGROUND: An increasing number of people are becoming addicted to the internet as a result of overuse. The Internet Addiction Test (IAT) is a popular tool for evaluating internet use behaviors. The interaction between different symptoms and the relationship between IAT and clinical diagnostic criteria are not well understood. OBJECTIVE: This study aimed to explore the core symptoms of internet addiction (IA) and the correlation between different symptoms of the IA symptom network. Network analysis was also conducted to explore the association between the IAT scale and the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria for IA. METHODS: We recruited 4480 internet users (aged 14-24 years), and they completed the IAT. The final analysis included 63.50% (2845/4480) of the participants after screening the submitted questionnaires. Participants were classified into IA group and non-IA (NIA) group. By using partial correlation with Lasso regularization networks, we identified the core symptoms of IA in each group and compared the group differences in network properties (strength, closeness, and betweenness). Then, we analyzed the symptom networks of the DSM-5 diagnostic criteria and IAT scale for IA. RESULTS: A total of 12.47% (355/2845) of the patients were in the IA group and 87.52% (2490/2845) of the patients were in the NIA group, and both groups were evaluated for the following nodes: IAT_06 (school work suffers; strength=0.511), IAT_08 (job performance suffers; strength=0.531), IAT_15 (fantasize about being on the web; strength=0.474), IAT_17 (fail to stop being on the web; strength=0.526), and IAT_12 (fear about boredom if offline; strength=0.502). The IA groups had a stronger edge between IAT_09 (defensive or secretive about being on the web) and IAT_18 (hidden web time) than the NIA groups. The items in DSM-5 had a strong association with IAT_12 (weight=-0.066), IAT_15 (weight=-0.081), IAT_17 (weight=-0.106), IAT_09 (weight=-0.198), and IAT_18 (weight=-0.052). CONCLUSIONS: The internet use symptom network of the IA group is significantly different from that of the NIA group. Nodes IAT_06 (school work affected) and IAT_08 (work performance affected) are the resulting symptoms affected by other symptoms, whereas nodes IAT_12 (fear about boredom if offline), IAT_17 (inability to stop being on the web), and IAT_15 (fantasize about being on the web) are key symptoms that activate other symptoms of IA and are strongly linked to the inability to control the intention to play games in the DSM-5.

Internet behavior patterns of adolescents before, during, and after COVID-19 pandemic.

Background: The outbreak of COVID-19 has affected the mental health of adolescents. To describe the Internet behavior-changing patterns of adolescents and to understand the impact of clinical features on changing patterns during the COVID-19 pandemic. Materials and methods: We conducted a cross-sectional cohort study using data collected through online investigation in China. A total of 625 adolescents completed the online survey from May 15 to June 7, 2020. The adolescents were asked to retrospect to the Internet behaviors and game behaviors of three time periods as follows: before the COVID-19 outbreak in China, during the COVID-19 outbreak in China, and back to school. The clinical variables of the demographic data, family functionality, and emotional and behavioral symptoms were also collected. According to the Internet behaviors and game behaviors patterns across the three time periods, the subjects will be sub-grouped. Results: Four Internet behavior-changing patterns during the COVID-19 was identified: (1) Continuous Normal Group (55.52%); (2) Normal to Internet Addiction Group (5.28%); (3) Internet Addiction to Normal Group (14.56%); and (4) Continuous Internet Addiction Group (24.64%). Years of education, academic score ranking, family functionality, and emotional and behavioral symptoms were different across the four groups. Proportions of game behaviors, scores of Strengths and Difficulties Questionnaire (SDQ), and SDQ subscale during the period before the COVID-19 outbreak were significant in predicting changing patterns. Conclusion: The Internet behavior patterns of adolescents during the COVID-19 period were various. Clinical features before the COVID-19 pandemic may predict changing patterns. The heterogeneity in characteristics between different changing patterns should be considered when intervening in adolescents' problematic Internet behavior.

Metabolomics changes after rTMS intervention reveal potential peripheral biomarkers in methamphetamine dependence.

Methamphetamine is one of the most commonly used drugs around the world, leading to serious public health and psychiatric problems. Due to the lackness of objective laboratory evaluation indicators, the molecular mechanisms of methamphetamine dependence still remain unclear. Previous evidence demonstrated that repetitive transcranial magnetic stimulation (rTMS) may be useful in treating drug addiction. The aim of this study was to identify and validate plasma metabolomics biomarkers in patients with methamphetamine use disorder before and after rTMS intervention. An untargeted gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) based metabolomics approach was applied to characterize the metabolic profile of forty methamphetamine dependent subjects and thirty-eight healthy controls in peripheral blood mononuclear cells (PBMCs). Patients were randomized to receive either rTMS or sham over the DLPFC for four weeks (20 daily sessions, 900 pulses per day). Cognitive function were assessed before and after rTMS intervention. Eight PBMC metabolites responsible for distinguishing real rTMS from sham treatment were identified. These metabolites were mainly involved in energy metabolism and oxidative stress. Compared with baseline, the expression of three metabolites was reversed after rTMS intervention: alpha-tocopherol, glyceric acid and fumaric acid. Changes of the alpha-tocopherol were associated with cognitive function improvement following rTMS. These findings suggest that energy metabolism and oxidative stress system may be associated with the effect of rTMS on cognitive function in methamphetamine dependence, and warrant further investigation.

The reliability and validity of a screening scale for online gaming disorder among Chinese adolescents and young adults.

BACKGROUND: In recent years, there have been frequent reports of gaming disorder in China, with more focus on young people. We developed and psychometrically tested a Gaming Disorder screening scale (i.e., Gaming Disorder Screening Scale - GDSS) for Chinese adolescents and young adults, based on the existing scales and diagnostic criteria, but also considering the development status of China. METHODS: For testing content and criterion validity, 1747 participants competed the GDSS and the Internet Addiction Test (IAT). After 15 days, 400 participants were retested with the scales for to assess test-retest reliability. Besides, 200 game players were interviewed for a diagnosis of gaming disorder. RESULTS: The Cronbach's alpha coefficient on the GDSS was 0.93. The test-retest coefficient of 0.79. Principal components analysis identified three factors accounting for 62.4% of the variance; behavior, functioning, cognition and emotion. Confirmatory factor analysis showed a good model fit to the data (χ2 /df = 5.581; RMSEA =0.074; TLI = 0.916, CFI = 0.928). The overall model fit was significantly good in the measurement invariance tested across genders and different age groups. Based on the clinical interview, the screening cut-off point was determined to be ≥47 (sensitivity 41.4%, specificity 82.3%). CONCLUSIONS: The GDSS demonstrated good reliability and validity aspects for screening online gaming disorder among Chinese adolescents and young adults.

The Crosstalk Between Neurons and Glia in Methamphetamine-Induced Neuroinflammation.

Methamphetamine (METH), an illicit psycho-stimulant, is widely known as an addictive drug that may cause neurotoxic effects. Previous researches on METH abuse have mainly focused on neurotransmitters, such as dopamine and glutamate. However, there is growing evidence that neuroinflammation also plays an important role in the etiology and pathophysiology of brain dysfunction induced by METH abuse. This has cast a spotlight on the research of microglia and astrocyte, which are critical mediators of neuroimmune pathology in recent years. In the central nervous system (CNS) immunity, abnormalities of the microglia and astrocytes have been observed in METH abusers from both postmortem and preclinical studies. The bidirectional communication between neurons and glia is essential for the homeostasis and biological function of the CNS while activation of glia induces the release of cytokines and chemokines during pathological conditions, which will affect the neuron-glia interactions and lead to adverse behavioral consequences. However, the underlying mechanisms of interaction between neurons and glia in METH-induced neuroinflammation remain elusive. Notably, discovering and further understanding glial activity and functions, as well as the crosstalk between neurons and glia may help to explain the pathogenesis of METH abuse and behavioral changes in abusers. In this review, we will discuss the current understanding of the crosstalk between neurons and glia in METH-induced neuroinflammation. We also review the existing microglia-astrocyte interaction under METH exposure. We hope the present review will lead the way for more studies on the development of new therapeutic strategies for METH abuse in the near future.

Altered Fecal Microbiota Correlated With Systemic Inflammation in Male Subjects With Methamphetamine Use Disorder.

Methamphetamine use disorder (MUD) is a major public health problem worldwide with limited effective treatment options. Previous studies have reported methamphetamine-associated alterations in gut microbiota. A potential role of gut microbiota in regulating methamphetamine-induced brain dysfunction through interactions with the host immune system has been proposed, but evidence for this hypothesis is limited. The present study aimed to investigate the alterations in the fecal microbiota and explore its relationship with systemic inflammation in MUD. Fecal samples were obtained from 26 male subjects with MUD and 17 sex- and age- matched healthy controls. Fecal microbial profiles were analyzed by 16S rRNA sequencing. Plasma inflammatory markers were measured using enzyme-linked immunosorbent assay. Associations between fecal microbiota, systemic inflammatory markers and clinical characteristics were examined by Spearman partial correlation analysis while controlling for possible confounders. Compared with healthy controls, individuals with MUD showed no difference in fecal microbial diversity, but exhibited differences in the relative abundance of several microbial taxa. At the genus level, a higher abundance of Collinsella, Odoribacter and Megasphaera and lower levels of Faecalibacterium, Blautia, Dorea and Streptococcus were detected in subjects with MUD. More importantly, altered fecal microbiota was found to be correlated with plasma levels of CRP, IL-2, IL-6 and IL-10. The order Lactobacillales, exhibiting lower abundance in participants with MUD, was positively related to the duration of methamphetamine abstinence and the plasma level of anti-inflammatory cytokine IL-10. This study is the first to provide evidence for a link between altered fecal microbiota and systemic inflammation in MUD. Further elucidation of interactions between gut microbiota and the host immune system may be beneficial for the development of novel therapeutic approaches for MUD.

A transcranial magnetic stimulation protocol for decreasing the craving of methamphetamine-dependent patients.

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique. Many substance use disorders lack effective treatments, and TMS is expected to reduce cravings and risk of relapse by regulating brain function. Here, we introduce three alternative TMS settings and specific operations to interfere with methamphetamine use disorders. Theoretically, this protocol can also be applied to diseases with similar brain damage characteristics. For complete details on the use and execution of this protocol, please refer to Chen et al. (2020).

Modulation of Methamphetamine-Related Attention Bias by Intermittent Theta-Burst Stimulation on Left Dorsolateral Prefrontal Cortex.

BACKGROUND: Previous studies have identified the treatment effect of repetitive transcranial magnetic stimulation (rTMS) on cravings of patients with methamphetamine use disorder (MUD). However, the mechanism underlying the treatment effect remains largely unknown. A potential candidate mechanism could be that rTMS over the dorsolateral prefrontal cortex (DLPFC) modulates the attention bias to methamphetamine-related cues. The purpose of this study is therefore to determine the modulation of rTMS on methamphetamine-related attention bias and the corresponding electrophysiological changes. METHODS: Forty-nine patients with severe MUD were included for analysis. The subjects were randomized to receive the active intermittent theta-burst stimulation (iTBS) or sham iTBS targeting DLPFC for 20 sessions. Participants performed the Addiction Stroop Task before and after the treatment while being recorded by a 64-channel electroencephalogram. Baseline characteristics were collected through the Addiction Severity Index. RESULTS: Post-treatment evaluations showed a reduced error rate in discriminating the color of methamphetamine words in the active iTBS group compared with the sham iTBS group. Following rTMS treatment, we found the significant time-by-group effect for the N1 amplitude (methamphetamine words > neutral words) and P3 latency (methamphetamine words > neutral words). The change of N1 amplitude was positively correlated with cravings in the active group. Moreover, reduced power of neural oscillation in the beta band, manifesting at frontal central areas, was also found in the active group. CONCLUSION: This study suggests that attention bias and the beta oscillation during the attentional processing of methamphetamine words in patients with MUD could be modulated by iTBS applied to left DLPFC.

Nature of glutamate alterations in substance dependence: A systematic review and meta-analysis of proton magnetic resonance spectroscopy studies.

Animal studies have reported the brain glutamatergic dysfunction in substance dependence. However, proton magnetic resonance spectroscopy (1H-MRS) studies of glutamate in substance-dependent patients published contradicting results. In order to investigate the characteristics of brain glutamatergic alterations in substance-dependent patients, we conducted systematic reviews and meta-analyses of 1H-MRS studies that have investigated the glutamate, glutamine, and Glx (glutamate + glutamine) concentration in substance-dependent patients. Multiple databases were searched until Sep 10, 2020. Twenty-nine studies comprising 982 patients and 787 controls were included. There was significantly decreased glutamate level in dorsolateral prefrontal cortex in patients compared with controls. Higher glutamate levels in medial prefrontal cortex and basal ganglia region were also demonstrated in patients compared with controls. Subgroup analyses based on the substance type and abstinence period (short vs medium-term abstinence period) were performed. The results revealed Glx and glutamate concentrations in all investigated brain regions were not different in patients with any types of substance dependence compared with controls. The abstinence period had no effect on the glutamate levels. In summary, substance dependence is associated with glutamatergic dysfunction of prefrontal cortex and basal ganglia. Present findings partially support the hypothesis that addiction is associated with abnormal brain glutamatergic neurotransmission.

The Potential Regulatory Network of Glutamate Metabolic Pathway Disturbance in Chinese Han Withdrawal Methamphetamine Abusers.

OBJECTS: To explore the long-term influence of methamphetamine abuse on metabolomics character, with gas chromatography-mass spectrometry (GS-MS) technology, and the potential regulatory network using the bioinformatics method. METHODS: Forty withdrawal methamphetamine abusers (WMA) were recruited from Shanghai Gaojing Forced Isolation Detoxification Institute. Forty healthy controls (HC) were recruited from society. GS-MS technology was used to detect metabolic products in serum. A bioinformatics method was used to build a regulatory network. Q-PCR was used to detect the candidate gene expressions, and ELISA was used to detect the regulatory enzyme expressions. RESULTS: Four pathways were significantly changed in the MA compared to the HC: (1) the arginine synthesis pathway, (2) alanine, aspartic acid and glutamate metabolic pathway, (3) cysteine and methionine metabolic pathway, and (4) the ascorbate and aldarate pathway (enrichment analysis p < 0.05, Impactor factor > 0.2). When focusing on the 'Alanine, aspartate, and glutamate metabolism' pathway, a regulatory network was established, and the expression of candidate regulatory genes and enzymes was verified. It was found that the expression of DLG2 (Discs large MAGUK scaffold protein 2), PLA2G4 (Phospholipase A2 group IVE), PDE4D (Phosphodiesterase 4D), PDE4B (Phosphodiesterase 4B), and EPHB2 (Ephrin type-B receptor 2) were significantly different between the two groups (p < 0.05), However, after adjusting for age and BMI, only DLG2, PLA2G4, and EPHB2 remained significant (p < 0.05). The expression of enzymes was not significantly different (p > 0.05). CONCLUSION: Methamphetamine abuse influences the metabolic process in the long term, and DLG2, PLA2G4, and EPHB2 may regulate the glutamate metabolism pathway.

The transcranial direct current stimulation over prefrontal cortex combined with the cognitive training reduced the cue-induced craving in female individuals with methamphetamine use disorder: A randomized controlled trial.

BACKGROUND: Craving and cognitive deficits are potential treatment targets for methamphetamine use disorder (MUD). Previous studies implied that transcranial direct current stimulation (tDCS) and cognitive training respectively improve these symptoms, but the combined effect is unknown. In this study, we investigated the combined effects of tDCS over dorsolateral prefrontal cortex (DLPFC) and computerized cognitive addiction therapy (CCAT) on cue-induced craving and cognitive functions among female individuals with MUD. METHODS: Seventy-five patients with MUD were randomly assigned to three groups: CCAT + tDCS group, CCAT + sham tDCS group and the control group. The former two groups received 20 sessions of cognitive training combined 1.5 mA active/sham tDCS over DLPFC (20min/session, 5times/week), while the control group received usual care which includes routine medical care, health education, physical exercises and psychological support related to relapse prevention. The cue-induced craving and cognitive functions were tested at the baseline, the end of 2nd week and 4th week. RESULTS: The CCAT + tDCS group showed a significant reduction in cue-induced craving after 4-week intervention. Moreover, the craving score of the real CCAT + tDCS group was significantly lower than that of the CCAT + sham tDCS group and that of the control group at the end of 4th week. A significant improvement in accuracy of TWOB task was only observed in the CCAT + tDCS group at the end of 4th week when compared to baseline. Unexpectedly, participants who received CCAT plus active or sham tDCS did not change their discounting, whereas those in the control group performed more impulsively over time. CONCLUSIONS: The study found that the intervention of tDCS over DLPFC combined with CCAT may have potential benefit in improving treatment outcome in patients with MUD. More research is needed to explore the underlying mechanism.