Resting-state Abnormalities in Heroin-dependent Individuals

Assessment of rTMS treatment effects for methamphetamine use disorder based on EEG microstates

Microstates have been proposed as topographical maps representing large-scale resting-state networks and have recently been suggested as markers for methamphetamine use disorder (MUD). However, it is unknown whether and how they change after repetitive transcranial magnetic stimulation (rTMS) intervention. This study included a comprehensive subject population to investigate the effect of rTMS on MUD microstates. 34 patients with MUD underwent a 4-week randomized, double-blind rTMS intervention (active=17, sham=17). Two resting-state EEG recordings and VAS evaluations were conducted before and after the intervention period. Additionally, 17 healthy individuals were included as baseline controls. The modified k-means clustering method was used to calculate four microstates (MS-A∼MS-D) of EEG, and the FC network was also analyzed. The differences in microstate indicators between groups and within groups were compared. The durations of MS-A and MS-B microstates in patients with MUD were significantly lower than that in HC but showed significant improvements after rTMS intervention. Changes in microstate indicators were found to be significantly correlated with changes in craving level. Furthermore, selective modulation of the resting-state network by rTMS was observed in the FC network. The findings indicate that changes in microstates in patients with MUD are associated with craving level improvement following rTMS, suggesting they may serve as valuable evaluation markers.

Chronic Morphine Leaves a Durable Fingerprint on Whole-Brain Functional Connectivity

BACKGROUND

Opioid use disorder is a chronic relapsing disorder. The brain adapts to opioids that are taken for pain treatment or recreational use so that abstinence becomes a true challenge for individuals with opioid use disorder. Studying brain dysfunction at this stage is difficult, and human neuroimaging has provided highly heterogeneous information.

METHODS

Here, we took advantage of an established mouse model of morphine abstinence together with functional magnetic resonance imaging to investigate whole-brain functional connectivity (FC) first at rest and then in response to an acute morphine challenge during image acquisition.

RESULTS

Hierarchical clustering of seed pair correlation coefficients showed modified FC in abstinent animals, brainwide and regardless of the condition. Seed-to-voxel analysis and random forest classification, performed on data at rest, indicated that the retrosplenial cortex (a core component of the default mode network) and the amygdala (a major aversion center) are the best markers of abstinence, thus validating the translatability of the study. Seed pair network clustering confirmed disruption of a retrosplenial cortex-centered network, reflecting major reorganization of brain FC. The latter analysis also identified a persistent but unreported morphine signature in abstinent mice at rest, which involves cortical and midbrain components and characterizes the enduring morphine footprint. Finally, dynamic FC analysis revealed that the intrascanner acute morphine challenge modified FC faster and more broadly in abstinent animals, demonstrating brainwide adaptations of FC reactivity to an acute opioid challenge.

CONCLUSIONS

This study used a unique experimental design to demonstrate that a prior history of chronic opioid exposure leaves a durable pharmacological signature on brain communication, with implications for pain management and recovery from opioid use disorder.

Brain circuits for maternal sensitivity and pain involving anterior cingulate cortex among mothers receiving buprenorphine treatment for opioid use disorder

Opioid-induced deficits in maternal behaviors are well-characterized in rodent models. Amid the current epidemic of opioid use disorder (OUD), prevalence among pregnant women has risen sharply. Yet, the roles of buprenorphine replacement treatment for OUD (BT/OUD) in the brain functions of postpartum mothers are unclear. Using functional magnetic resonance imaging (fMRI), we have developed an evolutionarily conserved maternal behavior neurocircuit (MBN) model to study human maternal care versus defensive/aggressive behaviors critical to mother-child bonding. The anterior cingulate gyrus (ACC) is not only involved in the MBN for mother-child bonding and attachment, but also part of an opioid sensitive "pain-matrix". The literature suggests that prescription opioids produce physical and emotional "analgesic" effects by disrupting specific resting-state functional connectivity (rs-FC) of ACC to regions related to MBN. Thus, in this longitudinal study, we report findings of overlapping MBN and pain matrix circuits, for mothers with chronic exposure of BT/OUD. A total of 32 mothers were studied with 6 min rs-FC at 1 month (T1) and 4 months postpartum (T2), including seven on BT/OUD and 25 non-BT/OUD mothers as a comparison group. We analyzed rs-FC between the insula, putamen, and the dorsal anterior cingulate cortex (DACC) and rostral ACC (RACC), as the regions of interest that mediate opioid analgesia. BT/OUD mothers, as compared to non-BT/OUD mothers, showed less left insula-RACC rs-FC but greater right putamen-DACC rs-FC at T1, with these between-group differences diminished at T2. Some of these rs-FC results were correlated with the scores of postpartum parental bonding questionnaire. We found time-by-treatment interaction effects on DACC and RACC-dependent rs-FC, potentially identifying brain mechanisms for beneficial effects of BT, normalizing dysfunction of maternal brain and behavior over the first four months postpartum. This study complements recent studies to ascertain how BT/OUD affects maternal behaviors, mother-child bonding, and intersubjectivity and reveals potential MBN/pain-matrix targets for novel interventions.

Internet gaming disorder and tobacco use disorder share neural connectivity patterns between the subcortical and the motor network

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are globally common, non-substance-related disorders and substance-related disorders worldwide, respectively. Recognizing the commonalities between IGD and TUD will deepen understanding of the underlying mechanisms of addictive behavior and excessive online gaming. Using node strength, 141 resting-state data were collected in this study to compute network homogeneity. The participants included participants with IGD (PIGD: n = 34, male = 29, age: 15-25 years), participants with TUD (PTUD: n = 33, male = 33, age: 19-42 years), and matched healthy controls (control-for-IGD: n = 41, male = 38, age: 17-32 years; control-for-TUD: n = 33, age: 21-27 years). PIGD and PTUD exhibited common enhanced node strength between the subcortical and motor networks. Additionally, a common enhanced resting-state functional connectivity (RSFC) was found between the right thalamus and right postcentral gyrus in PIGD and PTUD. Node strength and RSFC were used to distinguish PIGD and PTUD from their respective healthy controls. Interestingly, models trained on PIGD versus controls could classify PTUD versus controls and vice versa, suggesting that these disorders share common neurological patterns. Enhanced connectivity may indicate a greater association between rewards and behaviors, inducing addiction behaviors without flexible and complex regulation. This study discovered that the connectivity between the subcortical and motor networks is a potential biological target for developing addiction treatment in the future.

The effect of repetitive transcranial magnetic stimulation on electroencephalography microstates of patients with heroin-addiction

The effects of transcranial magnetic stimulation in treating substance use disorders are gaining attention; however, most existing studies used subjective measures to examine the treatment effects. Objective electroencephalography (EEG)-based microstate analysis is important for measuring the efficacy of transcranial magnetic stimulation in patients with heroin addiction. We investigated dynamic brain activity changes in individuals with heroin addiction after transcranial magnetic stimulation using microstate indicators. Thirty-two patients received intermittent theta-burst stimulation (iTBS) over the left dorsolateral prefrontal cortex. Resting-state EEG data were collected pre-intervention and 10 days post-intervention. The feature values of the significantly different microstate classes were computed using a K-means clustering algorithm. Four EEG microstate classes (A-D) were noted. There were significant increases in the duration, occurrence, and contribution of microstate class A after the iTBS intervention. K-means classification accuracy reached 81.5%. The EEG microstate is an effective improvement indicator in patients with heroin addiction treated with iTBS. Microstates were examined using machine learning; this method effectively classified the pre- and post-intervention cohorts among patients with heroin addiction and healthy individuals. Using EEG microstate to measure heroin addiction and further exploring the effect of iTBS in patients with heroin addiction merit clinical investigation.

Abnormal resting-state functional connectome in methamphetamine-dependent patients and its application in machine-learning-based classification

Brain resting-state functional connectivity (rsFC) has been widely analyzed in substance use disorders (SUDs), including methamphetamine (MA) dependence. Most of these studies utilized Pearson correlation analysis to assess rsFC, which cannot determine whether two brain regions are connected by direct or indirect pathways. Moreover, few studies have reported the application of rsFC-based graph theory in MA dependence. We evaluated alterations in Tikhonov regularization-based rsFC and rsFC-based topological attributes in 46 MA-dependent patients, as well as the correlations between topological attributes and clinical variables. Moreover, the topological attributes selected by least absolute shrinkage and selection operator (LASSO) were used to construct a support vector machine (SVM)-based classifier for MA dependence. The MA group presented a subnetwork with increased rsFC, indicating overactivation of the reward circuit that makes patients very sensitive to drug-related visual cues, and a subnetwork with decreased rsFC suggesting aberrant synchronized spontaneous activity in subregions within the orbitofrontal cortex (OFC) system. The MA group demonstrated a significantly decreased area under the curve (AUC) for the clustering coefficient (Cp) (Pperm < 0.001), shortest path length (Lp) (Pperm = 0.007), modularity (Pperm = 0.006), and small-worldness (σ, Pperm = 0.004), as well as an increased AUC for global efficiency (E.glob) (Pperm = 0.009), network strength (Sp) (Pperm = 0.009), and small-worldness (ω, Pperm < 0.001), implying a shift toward random networks. MA-related increased nodal efficiency (E.nodal) and altered betweenness centrality were also discovered in several brain regions. The AUC for ω was significantly positively associated with psychiatric symptoms. An SVM classifier trained by 36 features selected by LASSO from all topological attributes achieved excellent performance, cross-validated prediction area under the receiver operating characteristics curve, accuracy, sensitivity, specificity, and kappa of 99.03 ± 1.79, 94.00 ± 5.78, 93.46 ± 8.82, 94.52 ± 8.11, and 87.99 ± 11.57%, respectively (Pperm < 0.001), indicating that rsFC-based topological attributes can provide promising features for constructing a high-efficacy classifier for MA dependence.

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.

Assessing brain activity in male heroin-dependent individuals under methadone maintenance treatment: A resting-state fMRI study

Methadone maintenance treatment (MMT) is recognized as an effective and mainstream alternative treatment for heroin addiction. However, the effect of long-term MMT on the local and global brain activity of heroin-dependent individuals during resting state remains unknown. Twenty-five heroin-dependent individuals under MMT, 26 heroin-dependent individuals after short-term abstinence (HA) and 42 healthy controls (HC) were included in the resting-state functional magnetic resonance imaging study. The craving before and after heroin cue exposure were evaluated among HA and MMT subjects. The difference in craving, regional homogeneity (ReHo) and related functional connectivity were analyzed among the three groups. We found that the craving before and after heroin cue exposure of MMT group was significantly lower than that of HA group. Compared with HA group, the MMT group showed higher ReHo value in the right orbitofrontal cortex and bilateral posterior central cortex. No significant difference in global brain connectivity based on differential ReHo regions was found among the three groups. This study demonstrated the long-term MMT could improve the local activity of executive control and somatosensory brain regions in heroin-dependent individuals. It suggested that MMT might be beneficial to restoring executive control and somatosensory function in the direction towards that of healthy controls.

Repeated blast mild traumatic brain injury and oxycodone self-administration produce interactive effects on neuroimaging outcomes

Traumatic brain injury (TBI) and drug addiction are common comorbidities, but it is unknown if the neurological sequelae of TBI contribute to this relationship. We have previously reported elevated oxycodone seeking after drug self-administration in rats that received repeated blast TBI (rbTBI). TBI and exposure to drugs of abuse can each change structural and functional neuroimaging outcomes, but it is unknown if there are interactive effects of injury and drug exposure. To determine the effects of TBI and oxycodone exposure, we subjected rats to rbTBI and oxycodone self-administration and measured drug seeking and several neuroimaging measures. We found interactive effects of rbTBI and oxycodone on fractional anisotropy (FA) in the nucleus accumbens (NAc) and that FA in the medial prefrontal cortex (mPFC) was correlated with drug seeking. We also found an interactive effect of injury and drug on widespread functional connectivity and regional homogeneity of the blood oxygen level dependent (BOLD) response, and that intra-hemispheric functional connectivity in the infralimbic medial prefrontal cortex positively correlated with drug seeking. In conclusion, rbTBI and oxycodone self-administration had interactive effects on structural and functional magnetic resonance imaging (MRI) measures, and correlational effects were found between some of these measures and drug seeking. These data support the hypothesis that TBI and opioid exposure produce neuroadaptations that contribute to addiction liability.

Neurofeedback and neural self-regulation: a new perspective based on allostasis

The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired ("set") state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.

Early Life Stress and Risks for Opioid Misuse: Review of Data Supporting Neurobiological Underpinnings

A robust body of research has shown that traumatic experiences occurring during critical developmental periods of childhood when neuronal plasticity is high increase risks for a spectrum of physical and mental health problems in adulthood, including substance use disorders. However, until recently, relatively few studies had specifically examined the relationships between early life stress (ELS) and opioid use disorder (OUD). Associations with opioid use initiation, injection drug use, overdose, and poor treatment outcome have now been demonstrated. In rodents, ELS has also been shown to increase the euphoric and decrease antinociceptive effects of opioids, but little is known about these processes in humans or about the neurobiological mechanisms that may underlie these relationships. This review aims to establish a theoretical model that highlights the mechanisms by which ELS may alter opioid sensitivity, thereby contributing to future risks for OUD. Alterations induced by ELS in mesocorticolimbic brain circuits, and endogenous opioid and dopamine neurotransmitter systems are described. The limited but provocative evidence linking these alterations with opioid sensitivity and risks for OUD is presented. Overall, the findings suggest that better understanding of these mechanisms holds promise for reducing vulnerability, improving prevention strategies, and prescribing guidelines for high-risk individuals.

Functional connectivity of posterior cingulate gyrus in heroin dependents treated by methadone maintenance and protracted abstinence measures: an event-related fMRI study

Protracted abstinence (PA) and Methadone maintenance treatment (MMT) are two main types of heroin addiction treatment, however, the effects of both measures on the functional connectivity (FC) of the brain in heroin dependents in the drug cue event-related response are unclear. Functional magnetic resonance imaging (fMRI) based drug cue-reactivity task has been widely used in addiction research, which may provide a new way to understand the change of brain function during a certain period of treatment. The default function network (DMN) with posterior cingulate cortex (PCC) as the core is generally involved in the process of addiction. The aim of the present study was to explore the brain response of FC in patients with heroin-dependent during PA, MMT treatment under task-fMRI. Twenty-two heroin-dependent patients during PA, 18 heroin-dependent patients during MMT and 16 healthy control (HC) individuals were included to conduct the heroin cue-reactivity task during fMRI. The MMT and PA patients' subjective craving for heroin was evaluated. The psychophysiological interaction (PPI) analysis of SPM12 was used to get FC during the task state. There was a significant difference on FC between PCC and the right medial Prefrontal Cortex (mPFC) in three groups. The post-hoc analysis showed that there was a significant difference of brain regions between the MMT and the PA group. The FC of PCC-mPFC in the MMT group was significantly stronger than that in the PA group. Compared with the PA group, the FC of the DMN in the MMT group was significantly increased under drug cue response. Therefore, PA is more beneficial for the heroin-dependent patients to lower the salience value of drug related cues, in turn to reduce relapse risks. It also reflected the important role of PCC-mPFC pathway in heroin dependents induced by heroin cues.

The molecular neurobiology and neuropathology of opioid use disorder

The number of people diagnosed with opioid use disorder has skyrocketed as a consequence of the opioid epidemic and the increased prescribing of opioid drugs for chronic pain relief. Opioid use disorder is characterized by loss of control of drug taking, continued drug use in the presence of adverse consequences, and repeated relapses to drug taking even after long periods of abstinence. Patients who suffer from opioid use disorder often present with cognitive deficits that are potentially secondary to structural brain abnormalities that vary according to the chemical composition of the abused opioid. This review details the neurobiological effects of oxycodone, morphine, heroin, methadone, and fentanyl on brain neurocircuitries by presenting the acute and chronic effects of these drugs on the human brain. In addition, we review results of neuroimaging in opioid use disorder patients and/or histological studies from brains of patients who had expired after acute intoxication following long-term use of these drugs. Moreover, we include relevant discussions of the neurobiological mechanisms involved in promoting abnormalities in the brains of opioid-exposed patients. Finally, we discuss how novel strategies could be used to provide pharmacological treatment against opioid use disorder.

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Brain abnormalities caused by opioid intoxication.

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Intoxication of opioids leads to defects in brain neurocircuitries.

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Insight into the molecular mechanisms associated with craving in heroin addicts.

Alterations in resting-state functional connectivity in substance use disorders and treatment implications

Substance use disorders (SUD) are diseases of the brain, characterized by aberrant functioning in the neural circuitry of the brain. Resting state functional connectivity (rsFC) can illuminate these functional changes by measuring the temporal coherence of low-frequency fluctuations of the blood oxygenation level-dependent magnetic resonance imaging signal in contiguous or non-contiguous regions of the brain. Because this data is easy to obtain and analyze, and therefore fairly inexpensive, it holds promise for defining biological treatment targets in SUD, which could help maximize the efficacy of existing clinical interventions and develop new ones. In an effort to identify the most likely "treatment targets" obtainable with rsFC we summarize existing research in SUD focused on 1) the relationships between rsFC and functionality within important psychological domains which are believed to underlie relapse vulnerability 2) changes in rsFC from satiety to deprived or abstinent states 3) baseline rsFC correlates of treatment outcome and 4) changes in rsFC induced by treatment interventions which improve clinical outcomes and reduce relapse risk. Converging evidence indicates that likely "treatment target" candidates, emerging consistently in all four sections, are reduced connectivity within executive control network (ECN) and between ECN and salience network (SN). Other potential treatment targets also show promise, but the literature is sparse and more research is needed. Future research directions include data-driven prediction analyses and rsFC analyses with longitudinal datasets that incorporate time since last use into analysis to account for drug withdrawal. Once the most reliable biological markers are identified, they can be used for treatment matching, during preliminary testing of new pharmacological compounds to establish clinical potential ("target engagement") prior to carrying out costly clinical trials, and for generating hypotheses for medication repurposing.

Can neuroimaging help combat the opioid epidemic? A systematic review of clinical and pharmacological challenge fMRI studies with recommendations for future research

The current opioid epidemic is an urgent public health problem, with enormous individual, societal, and healthcare costs. Despite effective, evidence-based treatments, there is significant individual variability in treatment responses and relapse rates are high. In addition, the neurobiology of opioid-use disorder (OUD) and its treatment is not well understood. This review synthesizes published fMRI literature relevant to OUD, with an emphasis on findings related to opioid medications and treatment, and proposes areas for further research. We conducted a systematic literature review of Medline and Psychinfo to identify (i) fMRI studies comparing OUD and control participants; (ii) studies related to medication, treatment, abstinence or withdrawal effects in OUD; and (iii) studies involving manipulation of the opioid system in healthy individuals. Following application of exclusionary criteria (e.g., insufficient sample size), 45 studies were retained comprising data from ~1400 individuals. We found convergent evidence that individuals with OUD display widespread heightened neural activation to heroin cues. This pattern is potentiated by heroin, attenuated by medication-assisted treatments for opioids, predicts treatment response, and is reduced following extended abstinence. Nonetheless, there is a paucity of literature examining neural characteristics of OUD and its treatment. We discuss limitations of extant research and identify critical areas for future neuroimaging studies, including the urgent need for studies examining prescription opioid users, assessing sex differences and utilizing a wider range of clinically relevant task-based fMRI paradigms across different stages of addiction.

Exploring the Neuroplastic Effects of Biofeedback Training on Smokers

Smoking and stress cooccur in different stages of a nicotine addiction cycle, affecting brain function and showing additive impact on different physiological responses. Resting-state functional connectivity has shown potential in identifying these alterations. Nicotine addiction has been associated with detrimental effects on functional integrity of the central nervous system, including the organization of resting-state networks. Prolonged stress may result in enhanced activation of the default mode network (DMN). Considering that biofeedback has shown promise in alleviating physiological manifestations of stress, we aimed to explore the possible neuroplastic effects of biofeedback training on smokers. Clinical, behavioral, and neurophysiological (resting-state EEG) data were collected from twenty-seven subjects before and after five sessions of skin temperature training. DMN functional cortical connectivity was investigated. While clinical status remained unaltered, the degree of nicotine dependence and psychiatric symptoms were significantly improved. Significant changes in DMN organization and network properties were not observed, except for a significant increase of information flow from the right ventrolateral prefrontal cortex and right temporal pole cortex towards other DMN components. Biofeedback aiming at stress alleviation in smokers could play a protective role against maladaptive plasticity of connectivity. Multiple sessions, individualized interventions and more suitable methods to promote brain plasticity, such as neurofeedback training, should be considered.

Decision-making, somatic markers and emotion processing in opiate users

RATIONALE

Opiate use is associated with deficits in decision-making. A possible explanation for these deficits is provided by the somatic marker hypothesis, which suggests that substance users may experience abnormal emotional responses during decision-making involving reward and punishment. This in turn may interfere with the brief physiological arousal, i.e. somatic markers that normally occur in anticipation of risky decisions. To date, the applicability of the somatic marker hypothesis to explain decision-making deficits has not been investigated in opiate users.

OBJECTIVES

This study assessed whether decision-making deficits in opiate users were related to abnormal emotional responses and reduced somatic markers.

METHODS

Opiate users enrolled in an opiate substitute treatment program (n = 28) and healthy controls (n = 32) completed the Iowa Gambling Task (IGT) while their skin conductance responses (SCRs) were recorded. Participants' emotional responses to emotion-eliciting videos were also recorded using SCRs and subjective ratings.

RESULTS

Opiate users displayed poorer decision-making on the IGT than did controls. However, there were no differences between the groups in SCRs; both groups displayed stronger SCRs following punishment than following reward, and both groups displayed stronger anticipatory SCRs prior to disadvantageous decisions than advantageous decisions. There were no group differences in objective or subjective measures of emotional responses to the videos.

CONCLUSIONS

The results suggest that deficits in emotional responsiveness are not apparent in opiate users who are receiving pharmacological treatment. Thus, the somatic marker hypothesis does not provide a good explanation for the decision-making deficits in this group.