P300 event-related potential in abstinent methamphetamine-dependent patients

Identification of Methamphetamine Abusers Can Be Supported by EEG-Based Wavelet Transform and BiLSTM Networks

Methamphetamine (MA) is a neurological drug, which is harmful to the overall brain cognitive function when abused. Based on this property of MA, people can be divided into those with MA abuse and healthy people. However, few studies to date have investigated automatic detection of MA abusers based on the neural activity. For this reason, the purpose of this research was to investigate the difference in the neural activity between MA abusers and healthy persons and accordingly discriminate MA abusers. First, we performed event-related potential (ERP) analysis to determine the time range of P300. Then, the wavelet coefficients of the P300 component were extracted as the main features, along with the time and frequency domain features within the selected P300 range to classify. To optimize the feature set, F_score was used to remove features below the average score. Finally, a Bidirectional Long Short-term Memory (BiLSTM) network was performed for classification. The experimental result showed that the detection accuracy of BiLSTM could reach 83.85%. In conclusion, the P300 component of EEG signals of MA abusers is different from that in normal persons. Based on this difference, this study proposes a novel way for the prevention and diagnosis of MA abuse.

Conflict monitoring and emotional processing in 3,4-methylenedioxymethamphetamine (MDMA) and methamphetamine users - A comparative neurophysiological study

In stimulant use and addiction, conflict control processes are crucial for regulating substance use and sustaining abstinence, which can be particularly challenging in social-affective situations. Users of methamphetamine (METH, "Ice") and 3,4-methylenedioxymethamphetamine (MDMA, "Ecstasy") both experience impulse control deficits, but display different social-affective and addictive profiles. We thus aimed to compare the effects of chronic use of the substituted amphetamines METH and MDMA on conflict control processes in different social-affective contexts (i.e., anger and happiness) and investigate their underlying neurophysiological mechanisms. For this purpose, chronic but recently abstinent users of METH (n = 38) and MDMA (n = 42), as well as amphetamine-naïve healthy controls (n = 83) performed an emotional face-word Stroop paradigm, while event-related potentials (ERPs) were recorded. Instead of substance-specific differences, both MDMA and METH users showed smaller behavioral effects of cognitive-emotional conflict processing (independently of emotional valence) and selective deficits in emotional processing of anger content. Both effects were underpinned by stronger P3 ERP modulations suggesting that users of substituted amphetamines employ altered stimulus-response mapping and decision-making. Given that these processes are modulated by noradrenaline and that both MDMA and METH use may be associated with noradrenergic dysfunctions, the noradrenaline system may underlie the observed substance-related similarities. Better understanding the functional relevance of this currently still under-researched neurotransmitter and its functional changes in chronic users of substituted amphetamines is thus an important avenue for future research.

An electroencephalographic signature predicts craving for methamphetamine

Craving is central to methamphetamine use disorder (MUD) and both characterizes the disease and predicts relapse. However, there is currently a lack of robust and reliable biomarkers for monitoring craving and diagnosing MUD. Here, we seek to identify a neurobiological signature of craving based on individual-level functional connectivity pattern differences between healthy control and MUD subjects. We train high-density electroencephalography (EEG)-based models using data recorded during the resting state and then calculate imaginary coherence features between the band-limited time series across different brain regions of interest. Our prediction model demonstrates that eyes-open beta functional connectivity networks have significant predictive value for craving at the individual level and can also identify individuals with MUD. These findings advance the neurobiological understanding of craving through an EEG-tailored computational model of the brain connectome. Dissecting neurophysiological features provides a clinical avenue for personalized treatment of MUD.

Neural basis of the attention bias during addiction stroop task in methamphetamine-dependent patients with and without a history of psychosis: an ERP study

Background

Attentional bias plays an important role in sustaining various types of drug addiction. No prior studies examined methamphetamine (MA)-associated psychosis (MAP) relationships between ERP time course and performance on an addiction Stroop task in MA abusers. The aim of the present study was to determine whether MA abusers with (MAP+) or without (MAP-) psychosis exhibit alterations of the ERP during the addiction Stroop task.

Methods

Thirty-one healthy controls (CTRL), 14 MAP-, and 24 MAP+ participants were recruited and completed the addiction Stroop task during EEG recording using 32 electrodes. Group variations were compared on measures of behavioral task performance and event-related potentials (ERP) of performance monitoring (N200, P300, N450). The Barratt impulsiveness scores were analyzed to investigate correlations with ERP changes.

Results

MA-related word stimulus elicited a more negative N200 amplitude over left-anterior electrodes in MAP- abusers; furthermore, a positive association between the N200 amplitude and Barratt attentional scores and non-planning scores was observed, while no such differences were found in MAP+ abusers. There were no significant differences in reaction time (RT) and error rate between each group.

Conclusion

This is the first study to examine psychosis relationships between ERP time course and performance on an addiction Stroop task in MA abusers with or without psychosis. These findings support the association between attentional bias measured by the MA addiction Stroop task and N200 component as well as indicate the possibility of using this cognitive task in combination with ERP technology to detect psychosis factors among abstinent MA abusers.

An automated drug dependence detection system based on EEG

OBJECTIVE

Substance abuse causes damage to the brain structure and function. This research aim is to design an automated drug dependence detection system based on EEG signals in a Multidrug (MD) abuser.

METHODS

EEG signals were recorded from participants categorized into MD-dependents (n = 10) and Healthy Control (HC) (n = 12). The Recurrence Plot investigates the dynamic characteristics of the EEG signal. The entropy index (ENTR) measured from the Recurrence Quantification Analysis was considered the complexity index of the delta, theta, alpha, beta, gamma, and all-band EEG signals. Statistical analysis was performed by t-test. The support vector machine technique was used for the data classification.

RESULTS

The results show decreased ENTR indices in the delta, alpha, beta, gamma, and all-band EEG signal and increased theta band in MD abusers compared to the HC group. That indicated the reduction of complexity in the delta, alpha, beta, gamma, and all-band EEG signals in the MD group. Additionally, the SVM classifier distinguished the MD group from the HC group with 90% accuracy, 89.36% sensitivity, 90.7% specificity, and 89.8% F1 score.

CONCLUSIONS AND SIGNIFICANCE

The nonlinear analysis of brain data was used to build an automatic diagnostic aid system that could identify HC people apart from those who abuse MD.

Does chronic use of amphetamine-type stimulants impair interference control? - A meta-analysis

In substance use and addiction, inhibitory control is key to ignoring triggers, withstanding craving and maintaining abstinence. In amphetamine-type stimulant (ATS) users, most research focused on behavioral inhibition, but largely neglected the equally important subdomain of cognitive interference control. Given its crucial role in managing consumption, we investigated the relationship between interference control and chronic ATS use in adults. A database search (Pubmed & Web of Science) and relevant reviews were used to identify eligible studies. Effect sizes were estimated with random effects models. Subgroup, meta-regression, and sensitivity analyses explored heterogeneity in effect sizes. We identified 61 studies (53 datasets) assessing interference control in 1873 ATS users and 1905 controls. Findings revealed robust small effect sizes for ATS-related deficits in interference control, which were mainly seen in methamphetamine, as compared to MDMA users. The differential effects are likely due to tolerance-induced dopaminergic deficiencies (presumably most pronounced in methamphetamine users). Similarities between different ATS could be due to noradrenergic deficiencies; but elucidating their functional role in ATS users requires further/more research.

Electroencephalogram pattern association with drug-related cues in a long-duration virtual reality environment in patients with methamphetamine use disorder

The cognitive processing of drug-related cues and the subsequent dysregulation of behaviour play a central role in the pathophysiology of substance use disorders. Prior studies are limited by small sample sizes and a lack of immersion in stimulus presentation. In the present study, we recruited patients with methamphetamine use disorder (MUD; N = 1099) from four compulsory isolated detoxification centres and healthy control participants (N = 305). With a 12-min-long virtual reality (VR) protocol stimulus, we discovered that patients showed a decrease in electroencephalogram (EEG) power across alpha to gamma bands in anterior scalp regions under methamphetamine-related VR stimuli (e.g. a glass pipe and medical tubing) compared with the control stimuli (e.g. balls and cubes). Analysis of variance (ANOVA) showed that the interaction effects of stimuli type and group were significant in five EEG bands. Using generalised linear models, we classified the stimuli type (i.e. drug-related vs. drug-unrelated cues) in MUD patients with an f1 score of 90% on an out-of-sample testing set. The decreases of EEG between drug-related cues and drug-unrelated cues in delta, theta and alpha frequency bands are more frequently seen in patients than in healthy controls, perhaps reflecting general arousal and attenuated impulsive control. Our results suggest that EEG responses elicited by long-duration methamphetamine-related VR cues showed a specific signature, which may have future clinical implications.

A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD.

Neurophysiological correlate of incubation of craving in individuals with methamphetamine use disorder

Previous studies both in laboratory animals and humans have reported that abstinence induces incubation of cue-induced drug craving for nicotine, alcohol, cocaine, and methamphetamine. However, current experimental procedures utilized to study incubation of methamphetamine craving do not incorporate the temporal dynamics of neuropsychological measures and electrophysiological activities associated with this incubation process. This study utilized the high-density electroencephalogram (EEG) signals as a rapid, inexpensive, and noninvasive measure of cue-induced craving potential. A total of 156 male individuals with methamphetamine use disorder (MUD) enrolled in this multisite, cross-sectional study. Structured clinical interview data, self-report questionnaires (cued craving, quality of sleep, impulsivity, anxiety, and depression) and resting-state, eye-closed 128 high-density channel EEG signals were collected at 5 abstinence duration time points (<1, 1-3, 3-6, 6-12, and 12-24 months) to track the neuropsychological and neurophysiological signatures. Cue-induced craving was higher after 1-3 months than after the other time points. This incubation effect was also observed for sleep quality but not for anxiety, depression, and impulsivity symptoms, along with exhibited decreased power spectrum for theta (5.5-8 Hz) and alpha (8-13 Hz), and increased in beta (16.5-26.5 Hz) frequency band. Source reconstructed resting-state EEG analysis showed increased synchronization of medial prefrontal cortex (MPFC) for the beta frequency band in 1-3 months abstinent MUD group, and associated with the incubation of craving. Remarkably, the robust incubation-related abnormalities may be driven by beta-band source space connectivity between MPFC and bilateral orbital gyrus (ORB). Our findings suggest the enhancement of beta activity in the incubation period most likely originates from a dysfunction involving frontal brain regions. This neurophysiological signature of incubation of craving can be used to identify individuals who might be most susceptible to relapse, providing a potential insight into future therapeutic interventions for MUD via neuromodulation of beta activity.

Electrophysiological indexes for impaired response inhibition and salience attribution in substance (stimulants and depressants) use disorders: A meta-analysis

The impairment of inhibitory control and reward system is the core feature underlying substance use disorder (SUD). Previous studies suggested that it can be regarded as impaired response inhibition and salience attribution syndrome (iRISA). The neural substrates of the two deficit functions were widely investigated in neuroimaging studies, and the impaired prefrontal cortex, limbic-orbitofrontal network, and fronto-insular-parietal network were observed. Previous Event-related potential (ERP) studies were also conducted to explore EEG indexes related to abnormal brain function. In the current meta-analysis, we aimed to explore the consistency of ERP indexes that can reflect the two aberrant processes: P300/slow potential (SP) for salience attribution and Error-related negativity (ERN)/Nogo-N200/Nogo-P300 for inhibitory control and conflict monitoring. Subgroup analyses for drug type and drug use conditions were also conducted. According to the 60 research studies, we found significantly enhanced drug-cue-induced P300 amplitude and attenuated Nogo-N200 amplitude in SUD individuals relative to Healthy control (HC), which supports the dual model. Moreover, the drug-cue-induced P300 displayed time-dependence recovery, suggesting a potential index for treatment evaluation. In conclusion, drug-cue-induced P300 and Nogo-N200 demonstrated high consistency, and the drug-cue-induced P300 can be used to track the changes of functional recovery for SUD. The integration of the two ERP components could be regarded as a potential biomarker for SUD, which may provide a new insight for clinical treatment and investigation.

Four-week Tai Chi intervention decreases attention bias to drug cues in individuals with methamphetamine use disorder

Background: Mind-body exercise is used for the rehabilitation of individuals with methamphetamine use disorder (MUD). Attention bias to substances is an important index of MUD. However, whether a mind-body exercise intervention can decrease attention bias is unclear.Objective: This study aimed to test the effect of a four-week Tai Chi (a Chinese traditional mind-body exercise) exercise program on the attention bias of individuals with MUD.Methods: Thirty-two men with MUD and without Tai Chi practice experience were recruited and randomly assigned to either a Tai Chi exercise group or a control group. The Tai Chi group received four-week Tai Chi training, while the control group engaged in daily exercise (including radio gymnastics and Jianxincao, two kinds of free-hand exercises). During a drug-related Stroop task, participants were instructed to respond to the color of the word ignoring the word type (drug-related or neutral words). The reaction time and d' (the index of sensitivity) were measured.Results: The participants showed attention bias to substance cues; the reaction time was slower for drug-related words than for neutral words (p < .05). After the Tai Chi intervention, the Tai Chi group showed a faster reaction time (ps < .05) and a smaller d' (ps < .05) than the baseline across all the word types. In contrast, the control group showed no differences (ps > .05).Conclusion: Four-week Tai Chi intervention reduced sensitivity and attentional bias to drug-related cues in individuals with MUD, suggesting that mind-body exercise might enhance recovery from MUD via attention control.

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.

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

BACKGROUND

Dysfunction in brain network dynamics has been found to correlate with many psychiatric disorders. However, there is limited research regarding resting electroencephalogram (EEG) brain network and its association with cognitive process for patients with methamphetamine use disorder (MUD). This study aimed at using EEG microstate analysis to determine whether brain network dynamics in patients with MUD differ from those of healthy controls (HC).

METHODS

A total of 55 MUD patients and 27 matched healthy controls were included for analysis. The resting brain activity was recorded by 64-channel electroencephalography. EEG microstate parameters and intracerebral current sources of each EEG microstate were compared between the two groups. Generalized linear regression model was used to explore the correlation between significant microstates with drug history and cognitive functions.

RESULTS

MUD patients showed lower mean durations of the microstate classes A and B, and a higher global explained variance of the microstate class C. Besides, MUD patients presented with different current density power in microstates A, B, and C relative to the HC. The generalized linear model showed that MA use frequency is negatively correlated with the MMD of class A. Further, the generalized linear model showed that MA use frequency, scores of Two-back task, and the error rate of MA word are correlated with the MMD and GEV of class B, respectively.

CONCLUSIONS

Intracranial current source densities of resting EEG microstates are disrupted in MUD patients, hence causing temporal changes in microstate topographies, which are correlated with attention bias and history of drug use.

Biomarkers and neuromodulation techniques in substance use disorders

Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders.

Bouncing back: Brain rehabilitation amid opioid and stimulant epidemics

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Frontoparietal event related potentials predict/track recovery.

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Frontostriatal functional magnetic resonance imaging signals predict/track recovery.

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Transcranial magnetic left prefrontal stimulation reduces craving and drug use.

Recent methamphetamine and opioid use epidemics are a major public health concern. Chronic stimulant and opioid use are characterized by significant psychosocial, physical and mental health costs, repeated relapse, and heightened risk of early death. Neuroimaging research highlights deficits in brain processes and circuitry that are linked to responsivity to drug cues over natural rewards as well as suboptimal goal-directed decision-making. Despite the need for interventions, little is known about (1) how the brain changes with prolonged abstinence or as a function of various treatments; and (2) how symptoms change as a result of neuromodulation. This review focuses on the question: What do we know about changes in brain function during recovery from opioids and stimulants such as methamphetamine and cocaine? We provide a detailed overview and critique of published research employing a wide array of neuroimaging methods – functional and structural magnetic resonance imaging, electroencephalography, event-related potentials, diffusion tensor imaging, and multiple brain stimulation technologies along with neurofeedback – to track or induce changes in drug craving, abstinence, and treatment success in stimulant and opioid users. Despite the surge of methamphetamine and opioid use in recent years, most of the research on neuroimaging techniques for recovery focuses on cocaine use. This review highlights two main findings: (1) interventions can lead to improvements in brain function, particularly in frontal regions implicated in goal-directed behavior and cognitive control, paired with reduced drug urges/craving; and (2) the targeting of striatal mechanisms implicated in drug reward may not be as cost-effective as prefrontal mechanisms, given that deep brain stimulation methods require surgery and months of intervention to produce effects. Overall, more studies are needed to replicate and confirm findings, particularly for individuals with opioid and methamphetamine use disorders.

A Newly Designed Mobile-Based Computerized Cognitive Addiction Therapy App for the Improvement of Cognition Impairments and Risk Decision Making in Methamphetamine Use Disorder: Randomized Controlled Trial

Background

Cognitive rehabilitation therapy has been found to improve cognitive deficits and impulse control problems in methamphetamine use disorder (MUD). However, there is limited research regarding this therapy’s feasibility when using mobile-based health technologies in supporting recovery from MUD in China.

Objective

The main aim of this study was to test whether 4 weeks of a newly designed computerized cognitive addiction therapy (CCAT) app can improve cognitive impairments, eliminate drug-related attention bias, and attenuate risk decision-making behaviors in participants with MUD.

Methods

Forty MUD participants were assigned randomly to either the CCAT group (n=20), who received 4 weeks of CCAT plus regular detoxification treatment as usual, or the control group (n=20), who only received the regular detoxification treatment as usual, in drug rehabilitation centers in Shanghai. The CCAT was designed by combine methamphetamine use-related picture stimuli with cognitive training with the aim of improving cognitive function and eliminating drug-related attention bias. The CogState Battery, Delay Discounting Task (DDT), Iowa Gambling Task (IGT), and Balloon Analog Risk Task (BART) were administered face-to-face to all participants before and after CCAT interventions.

Results

Forty male patients were recruited. The mean age was 32.70 (SD 5.27) years in the CCAT group and mean 35.05 (SD 8.02) years in the control group. Compared to the control group, CCAT improved working memory in the CCAT group (P=.01). Group×time interactions were observed among DDT, IGT, and BART tasks, with rates of discounting delayed rewards, IGT, and BART scores (P<.001) being reduced among those who received CCAT, whereas no changes were found in the control group.

Conclusions

The newly designed CCAT can help to improve cognitive impairment and impulsive control in MUD. Further study is needed to understand the underlying brain mechanisms of the cognitive therapy.

Trial Registration

ClinicalTrials.gov NCT03318081; https://clinicaltrials.gov/ct2/show/NCT03318081 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT03318081)

Persistent Microstructural Deficits of Internal Capsule in One-Year Abstinent Male Methamphetamine Users: a Longitudinal Diffusion Tensor Imaging Study

White matter (WM) alterations have been reported in methamphetamine (MA) users. However, knowledge about longitudinal changes in WM during abstinence from MA remains unknown. The present study aimed to examine how WM changes in long-term MA abstinent, in particular, whether the WM deficits would recover as the duration of abstinence extended. Twenty male MA dependent individuals and 19 healthy controls (HCs) were recruited and participated in both clinical assessments and diffusion tensor imaging (DTI) scans. The MA group underwent two DTI scans, a baseline scan with a duration of abstinence of 6.4 months and and a follow-up scan with a duration of abstinence of 13.0 months. Tract-Based Spatial Statistics was utilized to conduct baseline DTI analysis of MA group compared with HCs. The clusters with significant group differences of factional anisotropy (FA) were extracted as region of interests (ROIs). Mean values of DTI measurements (FA, mean diffusivity, axial diffusivity and radial diffusivity) were calculated within the ROIs in each subject's native space at baseline and follow-up. The MA group showed significant lower FA in the right internal capsule and superior corona radiate than HCs. The deficits did not recover when the duration of abstinence from MA reached 13 months. No significant correlations were found between FA and clinical measurements. Our results suggested persistent microstructure deficits of WM tracts surrounding the basal ganglia in MA dependent individuals.