Dysfunctional Default Mode Network in Methadone Treated Patients Who Have a Higher Heroin Relapse Risk

Neuroimaging of opioid effects in humans across conditions of acute administration, chronic pain therapy, and opioid use disorder

Evidence of central nervous system (CNS) exogenous opioid effects in humans has been primarily gained through neuroimaging of three participant populations: individuals after acute opioid administration, those with opioid use disorder (OUD), and those with chronic pain receiving opioid therapy. In both the brain and spinal cord, opioids alter processes of pain, cognition, and reward. Opioid-related CNS effects may persist and accumulate with longer opioid use duration. Meanwhile, opioid-induced benefits versus risks to brain health remain unclear. This review article highlights recent accumulating evidence for how exogenous opioids impact the CNS in humans. While investigation of CNS opioid effects has remained largely disparate across contexts of opioid acute administration, OUD, and chronic pain opioid therapy, integration across these contexts may enable advancement toward effective interventions.

Investigating brain dynamics and their association with cognitive control in opioid use disorder using naturalistic and drug cue paradigms

Objectives

Opioid use disorder (OUD) impacts millions of people worldwide. The prevalence and debilitating effects of OUD present a pressing need to understand its neural mechanisms to provide more targeted interventions. Prior studies have linked altered functioning in large-scale brain networks with clinical symptoms and outcomes in OUD. However, these investigations often do not consider how brain responses change over time. Time-varying brain network engagement can convey clinically relevant information not captured by static brain measures.

Methods

We investigated brain dynamic alterations in individuals with OUD by applying a new multivariate computational framework to movie-watching (i.e., naturalistic; N=76) and task-based (N=70) fMRI. We further probed the associations between cognitive control and brain dynamics during a separate drug cue paradigm in individuals with OUD.

Results

Compared to healthy controls (N=97), individuals with OUD showed decreased variability in the engagement of recurring brain states during movie-watching. We also found that worse cognitive control was linked to decreased variability during the rest period when no opioid-related stimuli were present.

Conclusions

These findings suggest that individuals with OUD may experience greater difficulty in effectively engaging brain networks in response to evolving internal or external demands. Such inflexibility may contribute to aberrant response inhibition and biased attention toward opioid-related stimuli, two hallmark characteristics of OUD. By incorporating temporal information, the current study introduces novel information about how brain dynamics are altered in individuals with OUD and their behavioral implications.

Glymphatic-System Function Is Associated with Addiction and Relapse in Heroin Dependents Undergoing Methadone Maintenance Treatment

This study investigates the impact of methadone maintenance treatment (MMT) on the brain glymphatic system (GS) in opioid addiction in China. A total of 51 male MMT patients, 48 demographically matched healthy controls (HCs), and 20 heroin dependents (HDs) were recruited for this study. The GS functioning was assessed using diffusion-tensor-imaging analysis along perivascular spaces (DTI-ALPS index) and the bilateral ALPS divergency (DivALPS). Group differences were analyzed utilizing ANOVA and two-sample t-tests. The relationship between DivALPS and relapse rate was explored using regression analysis. The DTI-ALPS index was significantly higher for the left-side brain than the right side in all three groups. There was a significant difference for the right side (p = 0.0098) between the groups. The MMT and HD groups showed significantly higher DTI-ALPS than the HC group (p = 0.018 and 0.016, respectively). The DivALPS varied significantly among the three groups (p = 0.04), with the HD group showing the lowest and the HC group the highest values. Significant negative relationships were found between relapse count, DivALPS (p < 0.0001, Exp(B) = 0.6047), and age (p < 0.0001, Exp(B) = 0.9142). The findings suggest that MMT may contribute to promoting brain GS recovery in heroin addicts, and modulation of the GS may serve as a potential biomarker for relapse risk, providing insights into novel therapeutic strategies.

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.

Default mode network mechanisms of repeated transcranial magnetic stimulation in heroin addiction

Repetitive transcranial magnetic stimulation (rTMS) over the left dorsolateral prefrontal cortex (DLPFC) has been shown to reduce cravings in heroin-dependent (HD) individuals, but the mechanisms underlying the anti-craving effects of rTMS are unknown. Abnormalities in the default mode network (DMN) are known to be consistent findings in HD individuals and are involved in cravings. We assessed the effect of rTMS on DMN activity and its relationship to the treatment response. Thirty HD individuals were included in this self-controlled study, and all HD participants received 10-Hz rTMS 7-session during a week. Data for cravings and withdrawal symptoms and resting-state functional magnetic resonance imaging data were collected before and after rTMS treatment. Thirty demographically matched healthy individuals who did not receive rTMS were included as controls. We focused on changes in coupling seeded from the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), and bilateral inferior parietal lobe (IPL), which are the core regions of the DMN. The craving and withdrawal symptom score of HD individuals decreased significantly after rTMS treatment. The left IPL-left middle frontal gyrus coupling and the left IPL-right inferior occipital gyrus coupling decreased significantly, and the changes in the left IPL-left middle frontal gyrus coupling were positively correlated with changes in drug-cue induced cravings. rTMS could modulate the coupling between the DMN and executive control network (ECN). Alterations of the left IPL-left middle frontal gyrus coupling may play an important mechanistic role in reducing drug cue-induced cravings.

Repetitive transcranial magnetic stimulation modulates coupling among large-scale brain networks in heroin-dependent individuals: A randomized resting-state functional magnetic resonance imaging study

The abnormal interactions of three key large-scale brain networks (default mode [DMN], salience and executive control [ECN]) were showed underlie dysfunctions in heroin addiction. Repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (DLPFC) is a potential treatment for heroin addiction. It is unclear whether impaired coupling among the large-scale brain networks would be improved by rTMS in treated heroin-dependent individuals. Thirty-five heroin-dependent individuals were included in this sham-controlled, randomized study. The patients received either active or sham rTMS for 1 week. The craving for heroin and resting-state functional magnetic resonance imaging data were collected before and after 1-week rTMS. Twenty-two healthy subjects were included as controls not receiving rTMS. After 1-week rTMS, only the active rTMS group showed a significant decrease in spontaneous and heroin cue-induced craving. The coupling between left DLPFC (a key node of left ECN) and left parahippocampal gyrus (PHG, included in DMN) significantly increased for the active group with a tendency towards that of controls. The coupling between the right precentral gyrus and three key regions included in DMN (posterior cingulate cortex/precuneus and bilateral inferior parietal cortex) significantly decreased for the active group with a tendency towards that of healthy controls. For the active rTMS individuals, the left DLPFC-PHG coupling negatively correlated with the spontaneous craving and the drug cue-induced craving. It suggested that the rTMS could reduce heroin craving, which might be related to the modulation of ECN-DMN coupling. This finding might shed light on the mechanism of rTMS for heroin addiction treatment.

Impact of binge drinking during college on resting state functional connectivity

AIM

The current study examined the longitudinal effects of standard binge drinking (4+/5+ drinks for females/males in 2 hours) and extreme binge drinking (8+/10+ drinks for females/males in 2 hours) on resting-state functional connectivity.

METHOD

119 college students (61 males) were recruited in groups of distinct bingeing patterns at baseline: non-bingeing controls, standard and extreme bingers. Resting-state scans were first obtained when participants were freshmen/sophomores and again approximately two years later. Associations between longitudinal bingeing (reported during this two-year gap) and network connectivity were examined. Network connectivity was calculated by aggregating all edges affiliated with the same network (an edge is a functional connection between two brain regions). The relationship between longitudinal bingeing and connectivity edges was also studied using connectome-based predictive modeling (CPM).

RESULTS

Greater standard bingeing was negatively associated with change in connectivity between Default Mode Network and Ventral Attention Network (DMN-VAN; False Discovery Rate corrected), controlling for initial binge groups, longitudinal network changes, motions, scanner, SES, sex, and age. The correlations between change in DMN-VAN connectivity and change in cognitive performance (Stroop, Digit Span, Letter Fluency, and Trail Making) were also tested, but the results were not significant. Lastly, CPM failed to identify a generalizable predictive model of longitudinal bingeing from change in connectivity edges.

CONCLUSIONS

Binge drinking is associated with abnormality in networks implicated in attention and self-focused processes, which, in turn, have been implicated in rumination, craving, and relapse. More extensive alterations in functional connectivity might be observed with heavier or longer binge drinking pattern.

Assessing effect of long-term abstinence on coupling of three core brain networks in male heroin addicts: A resting-state functional magnetic resonance imaging study

Abstinence is one of the important measures for heroin addiction. However, it is unknown whether long-term abstinence (LA) would improve the coupling among three core brain networks (salience, default mode, and executive control) and decrease craving in treated heroin addicts. Forty-three heroin addicts with LA, 27 heroin addicts with short-term abstinence (SA), and 46 demographically matched healthy controls (HC) participated in the resting-state functional magnetic resonance imaging study. The authors compared the functional connectivity among the three groups and examined how the coupling among salience, default mode, and executive control networks related to duration of abstinence and craving before and after drug cue exposure among heroin addicts. Compared with the SA group, with a tendency toward the HC group, the LA group showed lower drug cue-induced craving, stronger connectivity between the dorsal anterior cingulate cortex (a key node of salience network) and left dorsolateral prefrontal cortex and right posterior parietal cortex (key nodes of executive control network), and stronger connectivity between the right dorsolateral prefrontal cortex and precuneus (a key node of default mode network). Meanwhile, the right dorsolateral prefrontal cortex-precuneus connectivity positively correlated with duration of abstinence. The LA and SA groups demonstrated lower connectivity between the left anterior insula (a key node of salience network) and dorsolateral prefrontal cortex and lower connectivity within the left dorsolateral prefrontal cortex, compared with the HC group. Our findings revealed that LA is associated with lower drug cue induced craving and improve the coupling among the three core brain networks in heroin addicts.

Altered brain intrinsic functional hubs and connectivity associated with relapse risk in heroin dependents undergoing methadone maintenance treatment: A resting-state fMRI study

BACKGROUND

The neural substrates underlying the relapse behavior of heroin dependents (HD) who received long-term methadone maintenance treatment (MMT) have yet to be thoroughly expounded. This study investigated the relapse-related intrinsic functional hubs of HD and their functional integration feature at whole brain network level.

METHODS

57 male HD receiving MMT and 49 matched healthy controls (HC) were enrolled. All of the subjects received resting-state functional magnetic resonance imaging scan. And the 57 patients were assigned a 26-month follow-up for collecting illegal drug use information. Of them, 11 were non-relapsers and 46 relapsers. We analyzed the voxel-based degree centrality (DC) to reveal the differences in nodule centrality between HD and HC, conducted Pearson partial-correlation analysis to confirm the relationship between relapse frequency and DC value of the nodes with significant intergroup differences, and finally compared the functional connectivity (FC) of the relapse-related hubs between non-relapsers and relapsers.

RESULTS

We found the DC values of right insula and left nucleus accumbens (NAc) were negatively correlated with relapse frequency. Compared with the non-relapsers, the relapsers had a significant decreased FC between left NAc and inhibitory control circuitry, including left dorsolateral prefrontal cortex, left inferior frontal gyrus and motor regions.

CONCLUSIONS

These findings suggest that the neural substrates of relapse vulnerability in HD undergoing MMT are the intrinsic functional hubs of introceptive and reward systems and the latter modulates relapse behavior via interaction with inhibitory control circuit.

Proposing FDA consideration for the treatment and prophylaxis of opioid and psychostimulant abuse to incorporate the induction of DNA guided dopamine homeostasis: Anti-reward deficiency restoration solution (ARDS)

BACKGROUND

In face of an American opioid/psychostimulant crisis with overdose fatalities, due, in part, to the COVOD 19 pandemic, we are proposing a paradigm shift in response. Currently, The FDA has approved pharmaceuticals for the treatment of opioids, alcohol, and nicotine but not for psychostimulants or even cannabis.

PROPOSITION

To respond to the deadly overdose issue globally, we are proposing that the FDA embrace, for the treatment and prophylaxis of opioid and psychostimulant abuse, induction of DNA-guided, dopamine homeostasis. We refer to this novel therapeutic target as the Anti-Reward Deficiency Restoration Solution (ARDS).

EXPERT OPINION

This futuristic proposal regarding the FDA will provide important information that may ultimately lead to significant improvement in the recovery of individuals with opioid/psychostimulant and polydrug abuse issues, especially, those with genetically-induced dopamine deficiency.

CONCLUSION

With large populations supporting these initial results, and possibly even additional candidate genes and single nucleotide polymorphisms, the neuroscience and neurological community may eventually have the clinical ability to classify addiction severity, according to genotype and possession of risk alleles. A promising goal is the identification of high risk vulnerability, along with the provision of a safe, non-addicting ARDS natural nutrigenomic, involving a therapeutic model that potentially up-regulates instead of down-regulates dopaminergic receptors, preferably, the D2 subtype, is one laudable goal.

Temporal Dynamics of Large-Scale Networks Predict Neural Cue Reactivity and Cue-Induced Craving

BACKGROUND

Cue reactivity, a core characteristic of substance use disorders, commonly recruits brain regions that are key nodes in neurocognitive networks, including the default mode network (DMN) and salience network (SN). Whether resting-state temporal dynamic properties of these networks relate to subsequent cue reactivity and cue-induced craving is unknown.

METHODS

The resting-state data of 46 nicotine-dependent participants were assessed to define temporal dynamic properties of DMN and SN states. Temporal dynamics focused on the total time across the scan session that brain activity resides in these specific states. Using regression models, we examined how the total time in each state related to neural reactivity to smoking cues within key DMN (posterior cingulate cortex, medial prefrontal cortex) or SN (anterior insula, dorsal anterior cingulate cortex) nodes. Mediation analyses were subsequently conducted to study how neural cue reactivity mediates the relationship between total time in state at rest and subjective cue-induced craving.

RESULTS

Increased time spent in the DMN state and decreased time spent in the SN state predicted subsequent cue-induced increases in the anterior insula and dorsal anterior cingulate cortex, respectively. Cue-induced anterior insula and dorsal anterior cingulate cortex activity significantly mediated the relationship between time spent in DMN/SN and cue-induced subjective craving.

CONCLUSIONS

Our findings showed a significant relationship between resting-state dynamics of the DMN/SN and task-activated SN nodes that together predicted cue-induced craving changes in nicotine-dependent individuals. These findings propose a neurobiological pathway for cue-induced craving that begins with resting-state temporal dynamics, suggesting that brain responding to external stimuli is driven by resting temporal dynamics.

The role of catecholamines in modulating responses to stress: Sex-specific patterns, implications, and therapeutic potential for post-traumatic stress disorder and opiate withdrawal

Emotional arousal is one of several factors that determine the strength of a memory and how efficiently it may be retrieved. The systems at play are multifaceted; on one hand, the dopaminergic mesocorticolimbic system evaluates the rewarding or reinforcing potential of a stimulus, while on the other, the noradrenergic stress response system evaluates the risk of threat, commanding attention, and engaging emotional and physical behavioral responses. Sex-specific patterns in the anatomy and function of the arousal system suggest that sexually divergent therapeutic approaches may be advantageous for neurological disorders involving arousal, learning, and memory. From the lens of the triple network model of psychopathology, we argue that post-traumatic stress disorder and opiate substance use disorder arise from maladaptive learning responses that are perpetuated by hyperarousal of the salience network. We present evidence that catecholamine-modulated learning and stress-responsive circuitry exerts substantial influence over the salience network and its dysfunction in stress-related psychiatric disorders, and between the sexes. We discuss the therapeutic potential of targeting the endogenous cannabinoid system; a ubiquitous neuromodulator that influences learning, memory, and responsivity to stress by influencing catecholamine, excitatory, and inhibitory synaptic transmission. Relevant preclinical data in male and female rodents are integrated with clinical data in men and women in an effort to understand how ideal treatment modalities between the sexes may be different.

Resting-state brain network topological properties and the correlation with neuropsychological assessment in adolescent narcolepsy

Study Objectives

To evaluate functional connectivity and topological properties of brain networks, and to investigate the association between brain topological properties and neuropsychiatric behaviors in adolescent narcolepsy.

Methods

Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment were applied in 26 adolescent narcolepsy patients and 30 healthy controls. fMRI data were analyzed in three ways: group independent component analysis and a graph theoretical method were applied to evaluate topological properties within the whole brain. Lastly, network-based statistics was utilized for group comparisons in region-to-region connectivity. The relationship between topological properties and neuropsychiatric behaviors was analyzed with correlation analyses.

Results

In addition to sleepiness, depressive symptoms and impulsivity were detected in adolescent narcolepsy. In adolescent narcolepsy, functional connectivity was decreased between regions of the limbic system and the default mode network (DMN), and increased in the visual network. Adolescent narcolepsy patients exhibited disrupted small-world network properties. Regional alterations in the caudate nucleus (CAU) and posterior cingulate gyrus were associated with subjective sleepiness and regional alterations in the CAU and inferior occipital gyrus were associated with impulsiveness. Remodeling within the salience network and the DMN was associated with sleepiness, depressive feelings, and impulsive behaviors in narcolepsy.

Conclusions

Alterations in brain connectivity and regional topological properties in narcoleptic adolescents were associated with their sleepiness, depressive feelings, and impulsive behaviors.

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.

Independent Component Analysis and Graph Theoretical Analysis in Patients with Narcolepsy

The present study was aimed to evaluate resting-state functional connectivity and topological properties of brain networks in narcolepsy patients compared with healthy controls. Resting-state fMRI was performed in 26 adult narcolepsy patients and 30 matched healthy controls. MRI data were first analyzed by group independent component analysis, then a graph theoretical method was applied to evaluate the topological properties in the whole brain. Small-world network parameters and nodal topological properties were measured. Altered topological properties in brain areas between groups were selected as region-of-interest seeds, then the functional connectivity among these seeds was compared between groups. Partial correlation analysis was performed to evaluate the relationship between the severity of sleepiness and functional connectivity or topological properties in the narcolepsy patients. Twenty-one independent components out of 48 were obtained. Compared with healthy controls, the narcolepsy patients exhibited significantly decreased functional connectivity within the executive and salience networks, along with increased functional connectivity in the bilateral frontal lobes within the executive network. There were no differences in small-world network properties between patients and controls. The altered brain areas in nodal topological properties between groups were mainly in the inferior frontal cortex, basal ganglia, anterior cingulate, sensory cortex, supplementary motor cortex, and visual cortex. In the partial correlation analysis, nodal topological properties in the putamen, anterior cingulate, and sensory cortex as well as functional connectivity between these regions were correlated with the severity of sleepiness (sleep latency, REM sleep latency, and Epworth sleepiness score) among narcolepsy patients. Altered connectivity within the executive and salience networks was found in narcolepsy patients. Functional connection changes between the left frontal cortex and left caudate nucleus may be one of the parameters describing the severity of narcolepsy. Changes in the nodal topological properties in the left putamen and left posterior cingulate, changes in functional connectivity between the left supplementary motor area and right occipital as well as in functional connectivity between the left anterior cingulate gyrus and bilateral postcentral gyrus can be considered as a specific indicator for evaluating the severity of narcolepsy.

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.

Current understanding of the neurobiology of opioid use disorder: An overview

PURPOSE OF REVIEW

This review provides an overview of the neurobiological mechanisms underlying opioid use disorder (OUD) drawing from genetic, functional and structural magnetic resonance imaging (MRI) research.

RECENT FINDINGS

Preliminary evidence suggests an association between OUD and specific variants of the DRD2, δ-opioid receptor 1 (OPRD1) and μ-opioid receptor 1 (OPRM1) genes. Additionally, MRI research indicates functional and structural alterations in striatal and corticolimbic brain regions and pathways underlying reward, emotion/stress and cognitive control processes among individuals with OUD.

SUMMARY

Individual differences in genetic and functional and structural brain-based features are correlated with differences in OUD severity and treatment outcomes, and therefore may potentially one day be used to inform OUD treatment selection. However, given the heterogeneous findings reported, further longitudinal research across different stages of opioid addiction is needed to yield a convergent characterization of OUD and improve treatment and prevention.

Functional Correlates of Resting-State Connectivity in the Default Mode Network of Heroin Users on Methadone Treatment and Medication-Free Therapeutic Community Program

The treatment of heroin addiction is a complex process involving changes in addictive behavior and brain functioning. The goal of this study was to explore the brain default mode network (DMN) functional connectivity using resting-state functional magnetic resonance imaging (rs-fMRI) and decision-making performance based on the Cambridge gambling task in heroin-dependent individuals undergoing methadone treatment (MT, n = 11) and medication-free faith-based therapeutic community program (TC, n = 11). The DMN involved the medial prefrontal cortex (mPFC), left inferior parietal lobe (IPL_L), right inferior parietal lobe (IPL_R), and posterior cingulate cortex (PCC) subregions for all participants in both the MT and TC groups. Compared with MT, TC had an increased functional connectivity in IPL_L-IPL_R and IPL_R-PCC and decreased functional connectivity in mPFC-IPL_L and IPL_L-PCC. Both groups exhibited no significant difference in the regional rs-fMRI metric [i.e., amplitude of low-frequency fluctuation (ALFF)]. In the analysis of the neural correlates for decision-making performance, risk adjustment was positively associated with ALFF in IPL_L for all participants considering the group effects. The involvement of IPL in decision-making performance and treatment response among heroin-dependent patients warrants further investigation.

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.

Disrupted coupling of large-scale networks is associated with relapse behaviour in heroin-dependent men

BACKGROUND

It is unknown whether impaired coupling among 3 core large-scale brain networks (salience [SN], default mode [DMN] and executive control networks [ECN]) is associated with relapse behaviour in treated heroin-dependent patients.

METHODS

We conducted a prospective resting-state functional MRI study comparing the functional connectivity strength among healthy controls and heroin-dependent men who had either relapsed or were in early remission. Men were considered to be either relapsed or in early remission based on urine drug screens during a 3-month follow-up period. We also examined how the coupling of large-scale networks correlated with relapse behaviour among heroin-dependent men.

RESULTS

We included 20 controls and 50 heroin-dependent men (26 relapsed and 24 early remission) in our analyses. The relapsed men showed greater connectivity than the early remission and control groups between the dorsal anterior cingulate cortex (key node of the SN) and the dorsomedial prefrontal cortex (included in the DMN). The relapsed men and controls showed lower connectivity than the early remission group between the left dorsolateral prefrontal cortex (key node of the left ECN) and the dorsomedial prefrontal cortex. The percentage of positive urine drug screens positively correlated with the coupling between the dorsal anterior cingulate cortex and dorsomedial prefrontal cortex, but negatively correlated with the coupling between the left dorsolateral prefrontal cortex and dorsomedial prefrontal cortex.

LIMITATIONS

We examined deficits in only 3 core networks leading to relapse behaviour. Other networks may also contribute to relapse.

CONCLUSION

Greater coupling between the SN and DMN and lower coupling between the left ECN and DMN is associated with relapse behaviour. These findings may shed light on the development of new treatments for heroin addiction.

Fifty Years in the Development of a Glutaminergic-Dopaminergic Optimization Complex (KB220) to Balance Brain Reward Circuitry in Reward Deficiency Syndrome: A Pictorial

Dopamine along with other chemical messengers like serotonin, cannabinoids, endorphins and glutamine, play significant roles in brain reward processing. There is a devastating opiate/opioid epidemicin the United States. According to the Centers for Disease Control and Prevention (CDC), at least 127 people, young and old, are dying every day due to narcotic overdose and alarmingly heroin overdose is on the rise. The Food and Drug Administration (FDA) has approved some Medication-Assisted Treatments (MATs) for alcoholism, opiate and nicotine dependence, but nothing for psychostimulant and cannabis abuse. While these pharmaceuticals are essential for the short-term induction of "psychological extinction," in the long-term caution is necessary because their use favors blocking dopaminergic function indispensable for achieving normal satisfaction in life. The two institutions devoted to alcoholism and drug dependence (NIAAA & NIDA) realize that MATs are not optimal and continue to seek better treatment options. We review, herein, the history of the development of a glutaminergic-dopaminergic optimization complex called KB220 to provide for the possible eventual balancing of the brain reward system and the induction of "dopamine homeostasis." This complex may provide substantial clinical benefit to the victims of Reward Deficiency Syndrome (RDS) and assist in recovery from iatrogenically induced addiction to unwanted opiates/opioids and other addictive behaviors.