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

Relapse risk revealed by degree centrality and cluster analysis in heroin addicts undergoing methadone maintenance treatment

BACKGROUND

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

METHODS

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

RESULTS

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical-striatal-thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

CONCLUSION

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

Altered functional connectivity and oscillatory dynamics in polysubstance and cannabis only users during visuospatial processing

RATIONALE AND OBJECTIVES

Cannabis use is often associated with the use of other psychoactive substances, which is subsequently linked to an increased risk for addiction. While there is a growing body of neuroimaging literature investigating the cognitive effect of long-term cannabis use, very little is known about the potential additive effects of cannabis polysubstance use.

METHODS

Fifty-six adults composed of 18 polysubstance users (i.e., cannabis plus at least one other illicit substance), 19 cannabis-only users, and 19 nonusers completed a visuospatial attention task while undergoing magnetoencephalography. A data-driven approach was used to identify oscillatory neural responses, which were imaged using a beamforming approach. The resulting cortical regions were probed for group differences and used as seeds for whole-brain connectivity analysis.

RESULTS

Participants exhibited robust theta, alpha, beta, and gamma responses during visuospatial processing. Statistical analyses indicated that the cannabis-only group had weaker occipital theta relative to the nonusers, and that both polysubstance and cannabis-only users had reduced spontaneous gamma in the occipital cortices during the pre-stimulus baseline period relative to nonusers. Finally, functional connectivity analyses revealed that polysubstance users had sharply reduced beta connectivity between occipital and prefrontal, as well as occipital and left temporal cortices.

CONCLUSIONS

Cannabis use should be considered in a polysubstance context, as our correlational design suggests differences in functional connectivity among those who reported cannabis-only versus polysubstance use in occipital to prefrontal pathways critical to visuospatial processing and attention function. Future work should distinguish the effect of different polysubstance combinations and use more causal designs.

Exploring of cardiac autonomic activity with heart rate variability in long-term kratom (Mitragyna speciosa Korth.) users: a preliminary study

Background

Kratom is a psychoactive plant used to enhance productivity among laborers in Southeast Asian countries. Previous findings from in vitro research of mitragynine, a major component of kratom, suggested a possible risk of heart function abnormality. However, the cardiac autonomic function in long-term kratom users with chewing forms has never been studied. This study aimed to investigate heart rate variability (HRV) indices of cardiac autonomic function in long-term kratom chewers (LKC), compared to the control levels, and also to examine the correlation between HRV indices and relevant kratom use factors.

Method

A total number of 50 participants consisted of LKC (n = 31) who regularly chewed fresh kratom leaves for at least 2 years and demographically matched control subjects (n = 19). Resting electrocardiogram (ECG) signals were recorded from subjects for 3 min to analyze the ultrashort HRV in the frequency domain. The normalized low frequency (LFn) and high frequency (HFn) were chosen to be the HRV indices to evaluate cardiac autonomic function. The comparison of HRV indices between groups and the correlation between HRV indices and duration and quantity of kratom use was further conducted in statistical analysis.

Results

The LKC significantly increased LFn together with enhanced HFn compared to the control group tested, indicating that LKC changed cardiac autonomic function with parasympathetic dominance. Furthermore, no significant correlation between the HRV indices and the duration and quantity of kratom use was found, suggesting that the HRV indices were not relevant to these factors. The present study provided scientific-based evidence of cardiac autonomic modulation in long-term kratom chewers. LFn and HFn may be promising cardiac autonomic indicators for monitoring health outcomes in LKC.

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.

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.

Endogenous Opiates and Behavior: 2016

This paper is the thirty-ninth consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2016 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior, and the roles of these opioid peptides and receptors in pain and analgesia, stress and social status, tolerance and dependence, learning and memory, eating and drinking, drug abuse and alcohol, sexual activity and hormones, pregnancy, development and endocrinology, mental illness and mood, seizures and neurologic disorders, electrical-related activity and neurophysiology, general activity and locomotion, gastrointestinal, renal and hepatic functions, cardiovascular responses, respiration and thermoregulation, and immunological responses.