Changes in resting EEG following methadone treatment in opiate addicts

Disrupted resting-state functional connectivity of frontal network in opium use disorder

Opioid use disorder (OUD) as a chronic relapsing disorder is initially driven by dysfunction of brain reward networks and associated with several psychiatric disorders. Resting-state EEG was recorded in 24 healthy participants as well as 31 patients with OUD. Healthy participants do not meet OUD criteria. After pre-processing of the raw EEG, functional connectivity in the frontal network using eLORETA and all networks using graph analysis method were calculated. Patients with OUD had higher electrical neuronal activity compared to healthy participants in higher frequency bands. The statistical analysis revealed that patients with OUD had significantly decreased phase synchronization in β1 and β2 frequency bands compared with the healthy group in the frontal network. Regarding global network topology, we found a significant decrease in the characteristic path length and an increase in global efficiency, clustering coefficient, and transitivity in patients compared with the healthy group. These changes indicated that local specialization and global integration of the brain were disrupted in OUD and it suggests a tendency toward random network configuration of functional brain networks in patients with OUD. Disturbances in EEG-based brain network indices might reflect an altered cortical functional network in OUD. These findings might provide useful biomarkers to understand cortical brain pathology in opium use disorder.

Emotion Regulation Choice in Internet Addiction: Less Reappraisal, Lower Frontal Alpha Asymmetry

Individuals with internet addiction (IA) show difficulties in emotion regulation. However, they could effectively employ emotion regulation strategies when instructed. We speculate that this discrepancy might be caused by maladaptive emotion regulation choices. Recent studies indicated that decreased activity of the left frontal cortex could be a neural marker of reappraisal use. To address this problem, individuals with IA (n = 17, IA group) and healthy individuals (n = 23, healthy control [HC] group) were required to choose an emotion regulation strategy between reappraisal and distraction to regulate their emotions varying in emotional intensity and valence. We also compared the resting state frontal alpha asymmetry (FAA) of these 2 groups. The results replicated more choices of reappraisal in low- versus high-intensity emotional contexts across groups. More importantly, the IA group chose reappraisal less frequently compared with the HC group, irrespective of emotional intensity. Furthermore, we found individuals with IA have lower FAA than healthy controls, and FAA shows a positive correlation with the use of reappraisal. These findings suggest that IA alters individuals' patterns of emotion regulation choice and impairs frontal activities, causing difficulties in emotion regulation.

Resting-state EEG, Substance use and Abstinence After Chronic use: A Systematic Review

Resting-state EEG reflects intrinsic brain activity and its alteration represents changes in cognition that are related to neuropathology. Thereby, it provides a way of revealing the neurocognitive mechanisms underpinning chronic substance use. In addition, it is documented that some neurocognitive functions can recover following sustained abstinence. We present a systematic review to synthesize how chronic substance use is associated with resting-state EEG alterations and whether these spontaneously recover from abstinence. A literature search in Medline, PsycINFO, Embase, CINAHL, Web of Science, and Scopus resulted in 4088 articles, of which 57 were included for evaluation. It covered the substance of alcohol (18), tobacco (14), cannabis (8), cocaine (6), opioids (4), methamphetamine (4), and ecstasy (4). EEG analysis methods included spectral power, functional connectivity, and network analyses. It was found that long-term substance use with or without substance use disorder diagnosis was associated with broad intrinsic neural activity alterations, which were usually expressed as neural hyperactivation and decreased neural communication between brain regions. Some studies found the use of alcohol, tobacco, cocaine, cannabis, and methamphetamine was positively correlated with these changes. These alterations can partly recover from abstinence, which differed between drugs and may reflect their neurotoxic degree. Moderating factors that may explain results inconsistency are discussed. In sum, resting-state EEG may act as a potential biomarker of neurotoxic effects of chronic substance use. Recovery effects awaits replication in larger samples with prolonged abstinence. Balanced sex ratio, enlarged sample size, advanced EEG analysis methods, and transparent reporting are recommended for future studies.

Using Bilateral tDCS to Modulate EEG Amplitude and Coherence of Men With Opioid Use Disorder Under Methadone Therapy: A Sham-controlled Clinical Trial

Objective. This study aimed to investigate the effect of bilateral transcranial direct current stimulation (tDCS) on the electroencephalography (EEG) amplitude and coherence in male patients with opioid use disorder (OUD), who were under methadone therapy. It compares the effects of active versus sham tDCS. Methods. This is a double-blind sham-controlled clinical trial. Participants were 30 male patients with OUD; they were divided into 3 groups of left anode/right cathode tDCS, right anode/left cathode tDCS, and sham tDCS. Their brainwave activity was measured by quantitative EEG before study and then active groups underwent tDCS (2 mA, 20 min) applied over their right/left dorsolateral prefrontal cortex (DLPFC) for 10 consecutive days. After stimulation, they were re-assessed. The collected data were analyzed in SPSS, MATLAB, and NeuroGuide v.2 applications. Results. After active tDCS, a significant decrease in amplitude of slow brain waves (delta, theta, and alpha) in prefrontal, frontal, occipital, and parietal areas, and an increase in the coherence of beta, delta, and theta frequency bands in the parietal, central, and temporal regions of addicts were reported. In the sham group, there was a significant decrease in the amplitude of the alpha wave and in the coherence of delta and theta waves. Conclusion. The active tDCS over the right/left DLPFC, as a noninvasive and complementary treatment, can modulate the amplitude and coherence of brainwaves in patients with OUD.

Resting State EEG Activity Related to Impulsivity in People with Prescription Opioid Use Disorder

Previous studies on EEG activity in prescription opioid use disorder (OUD) have reported neuronal dysfunction related to heroin use, most consistently reflected by increases in β-brain oscillations. As similar research has yet to examine EEG associated with non-medical use of prescription opioid and as inhibitory deficits are associated with OUD, this pilot study compared quantitative EEGs of 18 patients with prescription OUD and 18 healthy volunteers and assessed relationships between oscillatory activity and impulsivity with the Barratt Impulsiveness Scale (BIS-11). Spectral EEGs showed greater amplitude density in β₁, β₂, and β₃ frequencies across frontal, temporal-central and posterior recording areas in patients. Similar abnormal amplitude density increases were seen in δ but not in θ or α frequency bands. Patients exhibited greater scores (impaired impulse control) on BIS-11 subscales (attention, motor, self-control) and impairment of these impulsive subtypes was associated with increases in β and δ oscillations. In patients, β1, β2, and δ activity was positively associated with disorder severity. Taken together, the results suggest that altered brain oscillations in persons with prescription OUD show some similarities with reported oscillatory changes in heroin use and may indicate a chronic state of imbalance in neuronal networks regulating impulsive and inhibitory control systems.

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.

The effect of bilateral tDCS over dorsolateral prefrontal cortex on the cognitive abilities of men with opioid use disorder under methadone therapy: A sham-controlled clinical trial

Background/aim

Opioid use disorder (OUD) can have negative impact on cognitive functions. This study aims to evaluate the effect of bilateral transcranial direct-current stimulation (tDCS) over the right/left dorsolateral prefrontal cortex (DLPFC) on the cognitive abilities of OUD men.

Methods

This study is a double-blind sham-controlled randomized clinical trial with a pretest/posttest design. Participants were 31 men with OUD living in Zanjan, Iran, assigned to three groups of left anode/right cathode tDCS, right anode/left cathode tDCS, and sham tDCS. The two active groups received tDCS (2 mA) at 10 sessions each for 10–20 min. The Cognitive Abilities Questionnaire (CAQ) in Persian was used to measure their cognitive abilities before and after intervention. Collected data were analyzed in SPSS v.22 software.

Results

Bilateral DLPFC stimulation resulted in a significant improvement in cognitive flexibility, planning, decision making, inhibitory control/selective attention, and memory of patients in the two active tDCS groups, while the sham tDCS had no significant effect on their cognitive abilities.

Conclusion

Bilateral tDCS over DLPFC, as an effective and complementary treatment, can improve the cognitive abilities of men with OUD.

Trial registration: This study is a double-blind sham-controlled clinical trial (Parallel, IRCT20170513033946N5. Registered 19 Jan 2019, https://en.irct.ir/trial/36081).

Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders

Electroencephalography (EEG) likely reflects activity of cortical neurocircuits, making it an insightful estimation for mental health in patients with substance use disorder (SUD). EEG signals are recorded as sinusoidal waves, containing spectral amplitudes across several frequency bands with high spatio-temporal resolution. Prior work on EEG signal analysis has been made mainly at individual electrodes. These signals can be evaluated from advanced aspects, including sub-regional and hemispheric analyses. Due to limitation of computational techniques, few studies in earlier work could conduct data analyses from these aspects. Therefore, EEG in patients with SUD is not fully understood. In the present retrospective study, spectral powers from a data house containing opioid (OUD), methamphetamine/stimulants (MUD), and alcohol use disorder (AUD) were extracted, and then converted into five distinct topographic data (i.e., electrode-based, cortical subregion-based, left-right hemispheric, anterior-posterior based, and total cortex-based analyses). We found that data conversion and reorganization in the topographic way had an impact on EEG spectral powers in patients with OUD significantly different from those with MUD or AUD. Differential changes were observed from multiple perspectives, including individual electrodes, subregions, hemispheres, anterior-posterior cortices, and across the cortex as a whole. Understanding the differential changes in EEG signals may be useful for future work with machine learning and artificial intelligence (AI), not only for diagnostic but also for prognostic purposes in patients with SUD.

Effects of exercise programs on neuroelectric dynamics in drug addiction

Exercise interventions have been considered to be an effective treatment for drug addiction. However, there is little dirct evidence that exercise affects brain activity in individuals afftected by drug addiction. Therefore, the aim of the present study was to investigate the effects of different exercise programs on detoxification. Cognitive recovery with 64-channel electroencephalography (EEG) recordings was obtained before and after three months of daily aerobic and anaerobic exercise. A total of 63 subjects with methamphetamine addiction were recruited and randomly divided into three groups for cognitive study in four behavioral states: an anaerobic resistance treatment group, an aerobic cycling treatment group and a control group. In addition, four behavioral states were examined: eyes-closed and eyes-open resting states, and exploratory behavior states following either drug- or neutral-cue exposure. Over a 12-week period,the alpha block ratio in the control group showed a slight decrease, while clear increases were observed in the resistance exercise and cycling treatment groups, particularly under the frontal and temporal regions in the eyes-open and drug-cue conditions. The major EEG activity frequency in the resistance treatment group during the drug-cue behavior task decreased compared with the frequencies of the cycling exercise and control groups. Meanwhile, the power of higher brain rhythms in the resistance treatment group was increased. Finally, the brain alpha wave left-lateralization index from EEG recording sites, F1-F2, in the resistance and cycling treatment groups under the eyes-closed condition positively decreased, while the control groups only showed slight decreases. Taken together, these results suggest that different types of exercise may induce distince and different positive therapeutic effects to facilitate detoxification.

Computer-aided classifying and characterizing of methamphetamine use disorder using resting-state EEG

Methamphetamine (meth) is potently addictive and is closely linked to high crime rates in the world. Since meth withdrawal is very painful and difficult, most abusers relapse to abuse in traditional treatments. Therefore, developing accurate data-driven methods based on brain functional connectivity could be helpful in classifying and characterizing the neural features of meth dependence to optimize the treatments. Accordingly, in this study, computation of functional connectivity using resting-state EEG was used to classify meth dependence. Firstly, brain functional connectivity networks (FCNs) of 36 meth dependent individuals and 24 normal controls were constructed by weighted phase lag index, in six frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-15 Hz), beta (15-30 Hz), gamma (30-45 Hz) and wideband (1-45 Hz).Then, significant differences in graph metrics and connectivity values of the FCNs were used to distinguish the two groups. Support vector machine classifier had the best performance with 93% accuracy, 100% sensitivity, 83% specificity and 0.94 F-score for differentiating between MDIs and NCs. The best performance yielded when selected features were the combination of connectivity values and graph metrics in the beta frequency band.

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.

Estimating Mental Health Conditions of Patients with Opioid Use Disorder

Objectives

Noninvasive estimation of cortical activity aberrance may be a challenge but gives valuable clues of mental health in patients. The goal of the present study was to characterize specificity of electroencephalogram (EEG) electrodes used to assess spectral powers associated with mental health conditions of patients with opioid use disorder.

Methods

This retrospective study included 16 patients who had been diagnosed with opioid use disorder in comparison with 16 sex- and age-matched healthy controls. EEG electrodes were placed in the frontal (FP1, FP2, F3, F4, F7, F8, and Fz), central (C3, C4, and Cz), temporal (T3, T4, T5, and T6), parietal (P3, P4, and Pz), and occipital scalp (O1 and O2). Spectral powers of δ, θ, α, β, and γ oscillations were determined, and their distribution was topographically mapped with those electrodes on the scalp.

Results

Compared to healthy controls, the spectral powers at low frequencies (<8 Hz; δ and θ) were increased in most electrodes across the scalp, while powers at the high frequencies (>12 Hz; β and γ) were selectively increased only at electrodes located in the frontal and central scalp. Among 19 electrodes, F3, F4, Fz, and Cz were highly specific in detecting increases in δ, θ, β, and γ powers of patients with opioid use disorders.

Conclusion

Results of the present study demonstrate that spectral powers are topographically distributed across the scalp, which can be quantitatively characterized. Electrodes located at F3, F4, Fz, and Cz could be specifically utilized to assess mental health in patients with opioid use disorders. Mechanisms responsible for neuroplasticity involving cortical pyramidal neurons and μ-opioid receptor regulations are discussed within the context of changes in EEG microstates.

Personalised modelling with spiking neural networks integrating temporal and static information

This paper proposes a new personalised prognostic/diagnostic system that supports classification, prediction and pattern recognition when both static and dynamic/spatiotemporal features are presented in a dataset. The system is based on a proposed clustering method (named d2WKNN) for optimal selection of neighbouring samples to an individual with respect to the integration of both static (vector-based) and temporal individual data. The most relevant samples to an individual are selected to train a Personalised Spiking Neural Network (PSNN) that learns from sets of streaming data to capture the space and time association patterns. The generated time-dependant patterns resulted in a higher accuracy of classification/prediction (80% to 93%) when compared with global modelling and conventional methods. In addition, the PSNN models can support interpretability by creating personalised profiling of an individual. This contributes to a better understanding of the interactions between features. Therefore, an end-user can comprehend what interactions in the model have led to a certain decision (outcome). The proposed PSNN model is an analytical tool, applicable to several real-life health applications, where different data domains describe a person's health condition. The system was applied to two case studies: (1) classification of spatiotemporal neuroimaging data for the investigation of individual response to treatment and (2) prediction of risk of stroke with respect to temporal environmental data. For both datasets, besides the temporal data, static health data were also available. The hyper-parameters of the proposed system, including the PSNN models and the d2WKNN clustering parameters, are optimised for each individual.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Acute effects of methadone on EEG power spectrum and event-related potentials among heroin dependents

Methadone as the most prevalent opioid substitution medication has been shown to influence the neurophysiological functions among heroin addicts. However, there is no firm conclusion on acute neuroelectrophysiological changes among methadone-treated subjects as well as the effectiveness of methadone in restoring brain electrical abnormalities among heroin addicts. This study aims to investigate the acute and short-term effects of methadone administration on the brain's electrophysiological properties before and after daily methadone intake over 10 weeks of treatment among heroin addicts. EEG spectral analysis and single-trial event-related potential (ERP) measurements were used to investigate possible alterations in the brain's electrical activities, as well as the cognitive attributes associated with MMN and P3. The results confirmed abnormal brain activities predominantly in the beta band and diminished information processing ability including lower amplitude and prolonged latency of cognitive responses among heroin addicts compared to healthy controls. In addition, the alteration of EEG activities in the frontal and central regions was found to be associated with the withdrawal symptoms of drug users. Certain brain regions were found to be influenced significantly by methadone intake; acute effects of methadone induction appeared to be associative to its dosage. The findings suggest that methadone administration affects cognitive performance and activates the cortical neuronal networks, resulting in cognitive responses enhancement which may be influential in reorganizing cognitive dysfunctions among heroin addicts. This study also supports the notion that the brain's oscillation powers and ERPs can be utilized as neurophysiological indices for assessing the addiction treatment traits.

Electrophysiological activity is associated with vulnerability of Internet addiction in non-clinical population

This study investigated the electrophysiological activity associated with vulnerability of problematic Internet use in non-clinical population. The resting EEG spectrum of alpha (8-13 Hz) rhythm was measured in 22 healthy subjects who have used the Internet for recreational purpose. The vulnerability of Internet addiction was assessed using Young's Internet Addiction Test (IAT) and Assessment for Computer and Internet Addiction-Screener (AICA-S) respectively. Depression and impulsivity were also measured with Beck Depression Inventory (BDI) and Barratt Impulsiveness Scale 11(BIS-11) respectively. The IAT was positively correlated with alpha power obtained during eyes closed (EC, r = 0.50, p = 0.02) but not during eyes open (EO). This was further supported by a negative correlation (r = -0.48, p = 0.02) between IAT scores and alpha desynchronization (EO-EC). These relationships remained significant following correction for multiple comparisons. Furthermore, The BDI score showed positive correlation with alpha asymmetry at mid-lateral (r = 0.54, p = 0.01) and mid-frontal (r = 0.46, p = 0.03) regions during EC, and at mid-frontal (r = 0.53, p = 0.01) region during EO. The current findings suggest that there are associations between neural activity and the vulnerability of problematic Internet use. Understanding of the neurobiological mechanisms underlying problematic Internet use would contribute to improved early intervention and treatment.

Effects of alkaloid-rich extract from Mitragyna speciosa (Korth.) Havil. on naloxone-precipitated morphine withdrawal symptoms and local field potential in the nucleus accumbens of mice

ETHNOPHARMACOLOGICAL RELEVANCE

Mitragyna speciosa (Korth.) Havil. (M. speciosa) is among the most well-known plants used in ethnic practice of Southeast Asia. It has gained increasing attention as a plant with potential to substitute morphine in addiction treatment program. However, its action on the central nervous system is controversial.

AIM OF THE STUDY

This study investigated the effects of M. speciosa alkaloid extract on naloxone-precipitated morphine withdrawal and neural signaling in the nucleus accumbens (NAc, brain reward center) of mice.

MATERIALS AND METHODS

The effects of M. speciosa alkaloid extract and mitragynine, a pure major constituent, on naloxone-precipitated morphine withdrawal were examined. Male Swiss Albino (ICR) mice were rendered dependent on morphine before injection with naloxone, a nonspecific opioid antagonist, to induce morphine withdrawal symptoms. The intensity of naloxone-precipitated morphine withdrawal was assessed from jumping behavior and diarrhea induced during a period of morphine withdrawal. To test possible addictive effect of M. speciosa alkaloid extract, mice were implanted with intracranial electrode into the NAc for local field potential (LFP) recording. Following M. speciosa alkaloid extract (80mg/kg) and morphine (15mg/kg) treatment, LFP power spectra and spontaneous motor activity were analyzed in comparison to control levels.

RESULTS

One-way ANOVA and multiple comparisons revealed that M. speciosa alkaloid extract (80 and 100mg/kg) significantly decreased the number of jumping behavior induced by morphine withdrawal whereas mitragynine did not. Additionally, M. speciosa alkaloid extract significantly decreased dry and wet fecal excretions induced by morphine withdrawal. LFP analysis revealed that morphine significantly decreased alpha (9.7-12Hz) and increased low gamma (30.3-44.9Hz) and high gamma (60.5-95.7Hz) powers in the NAc whereas M. speciosa alkaloid extract did not. Spontaneous motor activity was significantly increased by morphine but not M. speciosa alkaloid extract.

CONCLUSIONS

Taken together, M. speciosa alkaloid extract, but not mitragynine, attenuated the severity of naloxone-precipitated morphine withdrawal symptoms. Neural signaling in the NAc and spontaneous motor activity were sensitive to morphine but not M. speciosa alkaloid extract. Therefore, treatment with the M. speciosa alkaloid extract may be useful for opiate addiction treatment program.

Associations between prospective symptom changes and slow-wave activity in patients with Internet gaming disorder: A resting-state EEG study

The identification of the predictive factors and biological markers associated with treatment-related changes in the symptoms of Internet gaming disorder (IGD) may provide a better understanding of the pathophysiology underlying this condition. Thus, the present study aimed to identify neurophysiological markers associated with symptom changes in IGD patients and to identify factors that may predict symptom improvements following outpatient treatment with pharmacotherapy. The present study included 20 IGD patients (mean age: 22.71 ± 5.47 years) and 29 healthy control subjects (mean age: 23.97 ± 4.36 years); all IGD patients completed a 6-month outpatient management program that included pharmacotherapy with selective serotonin reuptake inhibitors. Resting-state electroencephalography scans were acquired prior to and after treatment, and the primary treatment outcome was changes in scores on Young's Internet Addiction Test (IAT) from pre- to posttreatment. IGD patients showed increased resting-state electroencephalography activity in the delta and theta bands at baseline, but the increased delta band activity was normalized after 6 months of treatment and was significantly correlated with improvements in IGD symptoms. Additionally, higher absolute theta activity at baseline predicted a greater possibility of improvement in addiction symptoms following treatment, even after adjusting for the effects of depressive or anxiety symptoms. The present findings demonstrated that increased slow-wave activity represented a state neurophysiological marker in IGD patients and suggested that increased theta activity at baseline may be a favorable prognostic marker for this population.

Quantitative EEG and Low-Resolution Electromagnetic Tomography (LORETA) Imaging of Patients Undergoing Methadone Treatment for Opiate Addiction

Methadone maintenance treatment (MMT) has been used as a treatment for opiate dependence since the mid-1960s. Evidence suggests that methadone binds to mu opiate receptors as do other opiates and induces changes in neurophysiological function. However, little is known, about how neural activity within the higher frequency gamma band (>30 Hz) while at rest changes in those stabilized on MMT despite its association with the excitation-inhibition balance within pyramidal-interneuron networks. Our study investigated differences in resting gamma power (37-41 Hz) between patients undergoing MMT for opiate dependence, illicit opiate users, and healthy controls subjects. Electroencephalographic data were recorded from 26 sites according to the international 10-20 system. Compared with the healthy controls subjects, people either undergoing MMT (mean difference [MD] = 0.32, 95% CI = 0.09-0.55, P < .01) or currently using illicit opiates (MD = 0.31, 95% CI = 0.06-0.56, P = .01) exhibited significant increased gamma power. The sLORETA (standardized low-resolution electromagnetic tomography) between-group comparison revealed dysfunctional neuronal activity in the occipital, parietal, and frontal lobes in the patients undergoing MMT. A more severe profile of dysfunction was observed in those using illicit opiates. Our findings suggest that long-term exposure to opioids is associated with disrupted resting state network, which may be reduced after MMT.

Resting EEG and ERPs findings in methadone-substituted opiate users: a review

Methadone has been used to treat opiate dependence since the mid-1960s. Despite its clinical effectiveness there is evidence from neuropsychological studies demonstrating that its long-term use might have negative effects on cognition. Nevertheless, it remains uncertain whether the observed cognitive impairments in patients undertaking methadone maintenance treatment (MMT) are solely attributable to the pharmacological effects of methadone, as suggested by some researchers. Determining the effects of MMT on neuropsychological function using electroencephalography (EEG) combined with event-related potentials (ERP) has been used infrequently. However EEG and ERP provide a means of closely examining information processing to determine whether MMT induces any deficits. The purpose of this review was to investigate whether psychophysiological evidence supports cognitive impairment in association with MMT by focusing on research using EEG and ERPs. The findings of EEG studies to date appear not support the notion that cognitive impairments are attributable to the specific pharmacological effects of methadone suggested by some neuropsychological studies. However, due to the methodological deficits and limited number of the studies, any conclusion based on the findings of the existing EEG studies should be avoided.