Resting state functional connectivity in addiction: Lessons learned and a road ahead

Influence of binge drinking on the resting state functional connectivity of university Students: A follow-up study

Binge Drinking (BD) is characterized by consuming large amounts of alcohol on one occasion, posing risks to brain function. Nonetheless, it remains the most prevalent consumption pattern among students. Cross-sectional studies have explored the relationship between BD and anomalies in resting-state functional connectivity (RS-FC), but the medium/long-term consequences of BD on RS-FC during developmental periods remain relatively unexplored. In this two-year follow-up study, the impact of sustained BD on RS-FC was investigated in 44 college students (16 binge-drinkers) via two fMRI sessions at ages 18-19 and 20-21. Using a seed-to-voxel approach, RS-FC differences were examined in nodes of the main brain functional networks vulnerable to alcohol misuse, according to previous studies. Group differences in RS-FC were observed in four of the explored brain regions. Binge drinkers, compared to the control group, exhibited, at the second assessment, decreased connectivity between the right SFG (executive control network) and right precentral gyrus, the ACC (salience network) and right postcentral gyrus, and the left amygdala (emotional network) and medial frontal gyrus/dorsal ACC. Conversely, binge drinkers showed increased connectivity between the right Nacc (reward network) and four clusters comprising bilateral middle frontal gyrus (MFG), right middle cingulate cortex, and right MFG extending to SFG. Maintaining a BD pattern during critical neurodevelopmental years impacts RS-FC, indicating mid-to-long-term alterations in functional brain organization. This study provides new insights into the neurotoxic effects of adolescent alcohol misuse, emphasizing the need for longitudinal studies addressing the lasting consequences on brain functional connectivity.

Efficacy of non-invasive brain stimulation in reducing craving in patients with alcohol use disorder: systematic review and meta-analysis

BACKGROUND

Craving plays a central role in reinforcing alcohol use disorder (AUD), and non-invasive brain stimulation (NIBS) has shown potential as a therapeutic intervention in AUD. We aim to evaluate the efficacy and safety following the application of NIBS in patients with AUD.

METHODS

A search of the PubMed, EMBASE, Cochrane Library and PsycINFO databases for articles published up to June 30, 2024 using predefined search terms identified a total of 20 randomized controlled trials (RCTs) and 22 units. The primary outcome of this study was the change in craving severity. The secondary outcome was the rate of adverse events.

RESULTS

Comparing the effect of alcohol craving severity reduction between the NIBS group and the sham group, the NIBS group showed a significant reduction in alcohol craving severity compared to the sham group (SMD = -0.211; 95% CI = -0.379 to -0.042). The I2 value was 22.2%, indicating a low level of heterogeneity (p = 0.17). Regarding safety, the NIBS group had an increased rate of adverse events compared to the sham group, but this was not significant (OR = 1.494; 95% CI = 0.834 to 2.675). In a subgroup analysis based on the types of NIBS, only transcranial direct current stimulation showed a significant effect (SMD = -0.214; 95% CI = -0.427 to -0.002). Subgroup analyses of stimulation parameters in NIBS showed that a significant reduction in craving severity was observed when NIBS was applied to the dorsolateral prefrontal cortex (SMD = -0.200; 95% CI = -0.381 to -0.019) and when multiple sessions were administered (SMD = -0.388; 95% CI = -0.620 to -0.156). In addition, a significant reduction in craving severity due to delayed effects was observed even 4 weeks after the last stimulation (SMD = -0.553; 95% CI = -0.979 to -0.126), but this finding should be interpreted with caution.

CONCLUSIONS

NIBS is effective in reducing the severity of craving in patients with AUD. This study provides the latest evidence on the effect of NIBS in reducing craving severity in AUD patients.

Tobacco Smoking Functional Networks: A Whole-Brain Connectome Analysis in 24 539 Individuals

INTRODUCTION

Nicotine addiction, a multifaceted neuropsychiatric disorder, profoundly impacts brain functions through interactions with neural pathways. Despite its significance, the impact of tobacco smoking on the whole-brain functional connectome remains largely unexplored.

AIMS AND METHODS

We conducted a whole-brain analysis on 24 539 adults aged 40 and above from the United Kingdom Biobank cohort. Subjects were categorized into individuals who use nicotine and those who do not use nicotine based on current and chronic tobacco smoking information. Functional connectivity was assessed using resting-state functional magnetic resonance imaging. We employed a network analysis method to assess the systematic effects of tobacco smoking on brain connectome by identifying subnetworks that show nicotine-use-related differences.

RESULTS

Our analyses revealed two nicotine-use-related subnetworks with distinct network structure (permutation p < .001). In the first network, there is a significant decrease in resting-state functional connectivity (rsFC) between the basal ganglia regions (eg, nucleus accumbens) and 73% of the remaining brain regions, emphasizing the central hub role of basal ganglia in addictive smoking behaviors. Additionally, a data-driven subnetwork, mainly involving regions from frontal and occipital lobes, showed reduced rsFC among individuals who use nicotine.

CONCLUSIONS

The results suggest significant alterations in the communication and coordination among the basal ganglia and the broader network of brain regions. The observed changes in rsFC indicate a widespread disruption in the connectivity patterns associated with nicotine use.

IMPLICATIONS

This study identifies rsFC subnetworks related to chronic nicotine use through whole-brain connectome analysis. The findings confirm that widespread alterations in rsFC are centered around hub nodes within the basal ganglia, including bilateral nucleus accumbens, putamen, caudate, and globus pallidus. In addition, our analysis found a clique-forming subnetwork vulnerable to tobacco smoking consisting of regions from the visual, dorsal/ventral attention, and frontoparietal networks.

Differential large-scale network functional connectivity in cocaine-use disorder associates with drug-use outcomes

Cocaine-use disorder (CUD) affects both structure and function of the brain. A triple network model of large-scale brain networks has been useful for identifying aberrant resting-state functional connectivity (rsFC) associated with mental health disorders including addiction. The present study investigated differences between people with CUD vs. controls (CONs) and whether putative differences were associated with drug-use outcomes. Participants with CUD (n = 38) and CONs (n = 34) completed a resting functional magnetic resonance imaging (fMRI) scan. Participants with CUD completed several mental health measures and participated in an 8-week, drug-use outcomes phase. A classification framework based on the triple network model was built, and triple networks (salience [SN], executive control [ECN], default mode [DMN]) and subcortical (striatum [ST], hippocampus/amygdala) regions were identified with the algorithm of group-information-guided independent components analysis (GIG-ICA) and subsequent support-vector machines. This classifier achieved 77.1% accuracy, 73.8% sensitivity, and 80.0% specificity, with an area under the curve of 0.87 for distinguishing CUD vs. CON. The two groups differed in SN-anterior DMN (aDMN) and ECN-aDMN rsFC, with the CUD group exhibiting stronger rsFC compared to CONs. They also differed in rsFC between several subcortical and triple networks, with CUD generally showing a lack of rsFC. Within the CUD group, ST-aDMN and ST-rECN rsFC were associated with differential drug-use outcomes. Exploratory results suggested SN-aDMN rsFC was associated with anxiety symptoms. These results add to the growing literature showing aberrant triple network and subcortical rsFC associated with substance use disorders. They suggest the aDMN specifically may underlie important differences between people with CUD and CONs and may be a potential target for intervention.

Altered resting-state network connectivity in internet gaming disorder

BACKGROUND

The growing popularity of internet gaming among adolescents and young adults has driven an increase in both casual and excessive gaming behavior. Nevertheless, it remains unclear how progressive increases in internet gaming engagement led to changes within and between brain networks. This study aims to investigate these connectivity alterations across varying levels of gaming involvement.

METHODS

In this cross-sectional study, 231 participants were recruited and classified into three groups according to Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for Internet Gaming Disorder (IGD): IGD group, highly engaged gaming(HEG) group, and lowly engaged gaming (LEG) group. Resting-state fMRI data from 217 participants (143 males, 74 females) were included in the final analysis. Independent component analysis was used to examine differences in intra- and inter-network functional connectivity (FC)across the three groups.

RESULTS

No significant differences were found in intra-network FC across the three groups. However, significant inter-network differences between the dorsal attention network(dAN)and the visual network (VN) among the three groups were observed. The HEG group exhibited significantly higher dAN-VN functional network connectivity (FNC) compared to the LEG group. Linear correlation analyses showed no significant correlation between the dAN-VN FNC values and IGD-20T scores.

CONCLUSION

Throughout the development of IGD, increasing levels of engagement are associated with a rise and subsequent decline in FNC of DAN-VN. This pattern may reflect top-down attentional regulation in the early stages of addiction, followed by attentional bias as addiction progresses.

Central Executive Network drives delta-9-tetrahydrocannabinol (THC)-induced nonlinear changes in large-scale functional connectivity in adolescent nonhuman primates

Adolescent cannabinoid exposure has been implicated in enduring modifications to adult brain circuitry; however, well-controlled, systematic analyses investigating dose-dependent effects of chronic delta-9-tetrahydrocannabinol (THC) exposure on brain connectivity are lacking. It is hypothesized that large-scale intrinsic networks, such as default mode (DMN), central executive (CEN), and salience networks (SN), are critically involved in vulnerability to deficits in cognitive processing often associated with adolescent cannabis use. The present study aimed to elucidate the effects of chronic THC exposure on functional connectivity (FC) of these putative large-scale networks in nonhuman primates. Separate groups of adolescent squirrel monkeys (aged 2.0-yrs [female] and 2.5-yrs [male]) were administered intramuscular injections of vehicle or THC daily (0.32 or 3.2mg/kg) for 6-months during adolescence. Resting state functional connectivity from scans conducted in awake subjects was measured before dosing, at 6-months of chronic dosing, and 60-days following discontinuation of daily THC exposure. Utilizing two distinct analytical methodologies, we observed a non-linear, dosage-dependent alteration in DMN-CEN FC across scan intervals. Specifically, exposure to a low THC dosage increased FC during chronic exposure compared to both the pre-dosing and discontinuation periods. This pattern, however, was not observed in either the vehicle or high THC dosage groups. Dual-regression unveiled a similar non-linear effect within the CEN, but not DMN, suggesting the effect on DMN-CEN FC may be driven by modifications within the CEN. Taken together, these results suggest adolescent THC exposure differentially affects large-scale brain networks and contributes to a nuanced understanding of CEN's role in disrupting brain connectivity following chronic THC exposure.

New Insights in the Treatment of Substance Use Disorders Thanks to Electrophysiological Tools

Objective: Substance use disorders (SUD) still represent a huge worldwide health problem, as, despite withdrawal, medication, social support and psychotherapy, the relapse rate (around 80% at one year following treatment) remains tremendously high. Therefore, an important challenge consists in finding new complementary add-on tools to enhance quality of care. Methods and Results: In this report we focus on new insights reported through the use of three electrophysiological tools (quantitative electroencephalography (EEG), QEEG; cognitive event-related potentials, ERPs; and neurofeedback) suggesting that their use might be helpful at the clinical level in the management of various forms of SUDs. Empirical evidence were presented. Conclusion: In light of encouraging results obtained highlighting how these electrophysiological tools may be used in the treatment of SUDs, further studies are needed in order to facilitate the implementation of such procedures in clinical care units.

Correspondence between thalamic injury-induced changes in resting-state fMRI of monkeys and their sensorimotor behaviors and neural activities

Resting state functional MRI (rsfMRI) exploits variations in blood-oxygenation-level-dependent (BOLD) signals to infer resting state functional connectivity (FC) within and between brain networks. However, there have been few reports quantifying and validating the results of rsfMRI analyses with other metrics of brain circuits. We measured longitudinal changes in FC both within and between brain networks in three squirrel monkeys after focal lesions of the thalamic ventroposterior lateral nucleus (VPL) that were intended to disrupt the input to somatosensory cortex and impair manual dexterity. Local field potential signals were recorded to assess electrophysiological changes during each animal's recovery, and behavioral performances were measured longitudinally using a sugar-pellet grasping task. Finally, end-point histological evaluations were performed on brain tissue slices to quantify the VPL damage. The rsfMRI data analysis showed significant decrease in FC measures both within and between networks immediately post-injury, which started to recover at different time-points for each animal. The trajectories of FC recovery for each animal mirrored their individual behavioral recovery time-courses. Electrophysiological measurements of inter-electrode coherences and end-point histological measures also aligned well with the graded injury effects measured using rsfMRI-based FC. A simple algorithm employing FC measures from the somatosensory network could accurately predict each monkeys' behavioral recovery timeframe after four weeks post-injury. Whole brain between-network FC measures further revealed that the injury effects were not limited to thalamocortical connections but were rather more widespread. Overall, this study provides evidence of the validity of rsfMRI based FC measures as indicators of the functional integrity and behavioral relevance following an injury to a specific brain circuit.

Relating Functional Connectivity and Alcohol Use Disorder: A Systematic Review and Derivation of Relevance Maps for Regions and Connections

Alcohol Use Disorder (AUD), a prevalent and potentially severe psychiatric condition, is one of the leading causes of morbidity and mortality. This systematic review investigates the relationship between AUD and resting-state functional connectivity (rsFC) derived from functional magnetic resonance imaging data. Following the PRISMA guidelines, a comprehensive search yielded 248 papers, and a screening process identified 39 studies with 73 relevant analyses. Using the automated anatomical labeling atlas for whole-brain parcellation, relevance maps were generated to quantify associations between brain regions and their connections with AUD. These outcomes are based on the frequency with which significant findings are reported in the literature, to deal with the challenge of methodological diversity between analyses, including sample sizes, types of independent rsFC features, and AUD measures. The analysis focuses on whole-brain studies to mitigate selection biases associated with seed-based approaches. The most frequently reported regions include the middle and superior frontal gyri, the anterior cingulate cortex, and the insula. The generated relevance maps can serve as a valuable tool for formulating hypotheses and advancing our understanding of AUD's neural correlates in the future. This work also provides a template on how to quantitatively summarize a diverse literature, which could be applied to more specific aspects of AUD, including craving, relapse, binge drinking, or other diseases.

Functional connectivity changes in males with nicotine addiction: A triple network model study

BACKGROUND

Nicotine addiction (NA) is recognized as a significant neurobehavioral disorder that affects both individuals and society. It is suggested that alterations in functional network connectivity (FNC) within specific brain networks underlie its neurobiological basis.

METHODS

The default mode network (DMN), executive control network (ECN), and salience network (SN) are identified using data from the Human Connectome Project. The study includes 47 individuals with NA and 35 normal controls (NC), all of whom undergo resting-state fMRI alongside smoking-related clinical assessments. A sliding window analysis is employed to assess connectivity metrics, including static functional network connectivity (FNC), standard deviation (SD), and coefficient of variation (CV), to compare information integration between the groups. Participants with NA are classified based on longitudinal changes in Fagerström Test for Nicotine Dependence (FTND) scores over six years into three categories: addiction tendency (AT), withdrawal tendency (WT), and stable tendency (ST). Correlation analyses are conducted to explore relationships between FNC abnormalities and clinical assessments.

RESULTS

Individuals with NA exhibit reduced static FNC (p_FDR = 0.029) between the dorsal DMN and the right ECN, accompanied by increased SD (p_FDR = 0.029) and CV (p_FDR = 0.029). A significant increase in SD (p_FDR = 0.049) is also observed in the dorsal DMN and left ECN. Correlations indicate that the SD of the dorsal DMN and right ECN relates to the pharmacological dimension of the Russell Smoking Reasons Questionnaire (RRSQ) scale (r = 0.416, p_FDR = 0.044), while CV correlates with changes in the FTND over six years (r = -0.391, p_FDR = 0.044) and the pharmacological dimension of the RRSQ scale (r = 0.402, p_FDR = 0.044). Post-hoc subgroup analyses reveal that these FNC intensity changes are present among WT patients (p_FDR < 0.05).

CONCLUSIONS

Alterations in brain network function within the DMN and ECN are suggested to precede behavioral changes in NA. These findings are interpreted as potential neurobiological markers of nicotine addiction.

Resting State Functional Connectivity of the Default Mode Network During Opioid Use and Cessation in Treatment-Seeking Persons

Resting-state functional connectivity analyses have been used to examine synchrony in neural networks in substance use disorders (SUDs), with the default mode network (DMN) one of the most studied. Prior research has generally found less DMN synchrony during use and greater synchrony during cessation, although little research has utilized this method with opioid use. This study examined resting brain activity in treatment-seeking persons who use opioids at two points-when using opioids and when opioid-free-to determine whether the DMN exhibits different levels of connectivity during opioid use and cessation and whether differences in connectivity predict subsequent relapse. The sample included 11 participants who met DSM-5 criteria for opioid use disorder and initiated buprenorphine treatment following fMRI scans that were approximately 3 days apart. Results showed greater functional connectivity in the DMN and the rIFG of the salience network (SN) when participants were abstaining than when actively using opioids. These changes in connectivity predicted 76.2% of the variance in withdrawal symptom severity, with the DMN nodes accounting for an additional 30.9%. Findings warrant further longitudinal exploration of the role of DMN connectivity and its interactions with other networks in relation to abstinence and withdrawal status and examination of its utility as a prognostic marker of cessation or relapse.

The Limbic System in Co-Occurring Substance Use and Anxiety Disorders: A Narrative Review Using the RDoC Framework

Substance use disorders (SUDs) and anxiety disorders (ADs) are highly comorbid, a co-occurrence linked to worse clinical outcomes than either condition alone. While the neurobiological mechanisms involved in SUDs and anxiety disorders are intensively studied separately, the mechanisms underlying their comorbidity remain an emerging area of interest. This narrative review explores the neurobiological processes underlying this comorbidity, using the Research Domain Criteria (RDoC) framework to map disruptions in positive valence, negative valence, and cognitive systems across the three stages of the addiction cycle: binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation. Anxiety and substance use play a reciprocal role at each stage of addiction, marked by significant psychosocial impairment and dysregulation in the brain. A more thorough understanding of the neural underpinnings involved in comorbid SUDs and anxiety disorders will contribute to more tailored and effective therapeutic interventions and assessments.

Connectivity Changes Following Episodic Future Thinking in Alcohol Use Disorder

Introduction: Recent addiction and obesity-related research suggests that episodic future thinking (EFT) can serve as a promising intervention to promote healthy decision-making. We used data from a pilot study to investigate the acute neural effects of EFT in alcohol use disorder (AUD). Because of the limitations of those data, we additionally used data from a previously published functional MRI (fMRI) study in which participants had not received any intervention for their AUD. Methods: In an out-of-scanner, guided interview, participants (n = 24; median age = 37.3 years; median AUDIT = 22.5) generated scenarios and cues about their future (EFT intervention, n = 15) or recent past (control episodic thinking [CET] control intervention, n = 9). Then, they performed both resting-state and task-based (delay discounting [DD]) fMRI. We used nodes from the default mode network and salience networks as well as the hippocampus to perform seed-based analyses of the resting-state data. The results then guided psychophysiological interaction analyses in the DD task. In addition, we used data from a larger, previously reported study as a "no intervention" group of AUD participants (n = 50; median age = 43.3; median Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) alcohol dependence score = 7) to reproduce and aid in interpreting our key findings. Results: EFT, but not CET, participants showed statistically improved DD rates-a behavioral marker for addiction. Resting-state analyses of the left hippocampus revealed connectivity differences in the frontal poles. The directionality of this difference suggested that EFT may reduce a hypo-connectivity relationship between these regions in AUD. We also found resting-state connectivity differences between the salience network and the right dorsolateral prefrontal cortex (R DLPFC), which then led us to discover R-to-L DLPFC psychophysiological interaction differences during DD. Moreover, the resting-state salience-to-DLPFC functional connectivity showed an inverse relationship to DD rate while hyperconnectivity between left and right DLPFC reflected slower reaction times during DD trials. Discussion: These findings suggest that previously noted benefits of EFT such as the improved DD replicated here might coincide with changes in neural connectivity patterns in AUD. The alterations in connectivity highlight potential mechanisms underlying the effectiveness of EFT in improving decision-making in AUD. Understanding these neural effects may contribute to the further development of targeted interventions for AUD and related disorders.

Resting state functional connectivity in adolescents with substance use disorder and their unaffected siblings

We aimed to examine resting-state functional connectivity (rsFC) in adolescents with substance use disorder (SUD) and their unaffected biological siblings (SIB), relative to typically-developing controls (TDC) in order to identify alterations in functional network organization that may be associated with the familial risk for SUD. Resting-state functional magnetic resonance imaging analysis included 20 adolescents with SUD, 20 SIB, and 18 TDC. Network-based analysis revealed that adolescents with SUD had significantly both weaker and higher rsFC compared to TDC mainly within the default-mode network (DMN) and between the DMN, fronto-parietal (FPN) and salience networks. In addition, adolescents with SUD showed lower rsFC between the visual network and other functional networks. Although the SIB group did not differ from TDC in the whole brain analysis, they showed lower rsFC within DMN and also between the visual network and other large-scale networks as well as higher rsFC between DMN and FPN compared to TDC in connections found to be abnormal in SUD group. Our results suggest that lower rsFC within DMN and higher rsFC between the DMN with FPN which were evident both in SUD and in SIB groups, and might be related to the familial predisposition for SUD.

Functional Connectivity Alterations in Cocaine Use Disorder: Insights from the Triple Network Model and the Addictions Neuroclinical Assessment Framework

Cocaine use disorder (CUD) disrupts functional connectivity within key brain networks, specifically the default mode network (DMN), salience network (SN), and central executive network (CEN). While the triple network model has been proposed to explain various psychiatric disorders, its applicability to CUD requires further exploration. In the present study, we built machine learning classifiers based on different combinations of DMN/SN/CEN to distinguish cocaine-use disorder (CUD) subjects from healthy control (HC) subjects. Among them, the combination of the SN and the CEN results in a remarkably high accuracy of 73.4% (sensitivity/specificity: 69.6%/78.6%, AUC: 0.78), outperforming the model based on the full triple network. This supports the hypothesis that during the binge/intoxication stage of addiction, the SN and the CEN play a more critical role than the DMN, consistent with the Addictions Neuroclinical Assessment (ANA) framework. Functional connectivity analysis revealed decreased connectivity within the DMN and the SN and increased connectivity within the CEN in CUD patients, suggesting that alterations in these networks could serve as biomarkers for addiction severity.

Assessment of rTMS treatment effects for methamphetamine addiction based on EEG functional connectivity

Methamphetamine (MA) addiction leads to impairment of neural communication functions in the brain, and functional connectivity (FC) may be a valid indicator. However, it is unclear how FC in the brain changes in methamphetamine use disorder (MUD) after treatment with repetitive transcranial magnetic stimulation (rTMS). Thirty-four patients with MUD participated in this study. The subjects were randomized to receive the active or sham rTMS for four weeks. Subjects performed electroencephalography (EEG) examinations and visual analogue scale (VAS) assessments before and after the treatment. The FC networks were constructed and visualized, and then the graph theory analysis was carried out. Finally, machine learning was used to classify FC networks before and after rTMS. The results showed that (1) the active group showed a significant enhancement in connectivity in the beta band; (2) the global efficiency, local efficiency, and aggregation coefficient of the active group in the beta band decreased significantly; (3) the LDA algorithm combined with the beta band FC matrix achieved an average accuracy of 82.5% in distinguishing before and after treatment. This study demonstrated that brain FC could effectively assess the therapeutic effect of rTMS, among which the beta band was the most sensitive and effective frequency band.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10097-x.

Aberrance in default mode and executive network activity underlie working memory deficits in addictive disorders: A preliminary, exploratory case-control study

BACKGROUND

Addiction can alter neural processes during rest and cognitive performance. Subjects with addictive disorders exhibit preoccupation and anticipation for the psychoactive substance when idle and cognitive deficits, during tasks.

METHODS

128 channel EEG was recorded in sixty subjects (30, with alcohol, opioid and internet addiction; 30 controls) during rest and while performing working memory task to ascertain underlying differences in cortical activity between the groups while at rest and during performance of the task. Artifactually clean data was then subjected to source analysis using sLORETA software in both the groups.

RESULTS

EEG cortical source analysis in subjects with addictive disorders showed significant activation of areas of Default Mode Network (DMN) and reduced activation in dorsolateral prefrontal cortices (DLPFC), an area known to be involved in executive function, during performance of task. However, control subjects demonstrated significantly reduced activation in areas of DMN; and increased activation of DLPFC during task performance.

CONCLUSION

Inability to suppress DMN inhibits reallocation of neural resources to areas of executive functioning leading to working memory deficits in subjects with addictive disorder.

Intrinsic connectivity demonstrates a shared role of the posterior cingulate for cue reactivity in both gambling and cocaine use disorders

Cue reactivity is relevant across addictive disorders as a process relevant to maintenance, relapse, and craving. Understanding the neurobiological foundations of cue reactivity across substance and behavioral addictions has important implications for intervention development. The present study used intrinsic connectivity distribution methods to examine functional connectivity during a cue-exposure fMRI task involving gambling, cocaine and sad videos in 22 subjects with gambling disorder, 24 with cocaine use disorder, and 40 healthy comparison subjects. Intrinsic connectivity distribution implicated the posterior cingulate cortex (PCC) at a stringent whole-brain threshold. Post-hoc analyses investigating the nature of the findings indicated that individuals with gambling disorder and cocaine use disorder exhibited decreased connectivity in the posterior cingulate during gambling and cocaine cues, respectively, as compared to other cues and compared to other groups. Brain-related cue reactivity in substance and behavioral addictions involve PCC connectivity in a content-to-disorder specific fashion. The findings suggesting that PCC-related circuitry underlies cue reactivity across substance and behavioral addictions suggests a potential biomarker for targeting in intervention development.

Triple network resting-state functional connectivity patterns of alcohol heavy drinking

AIMS

Previous neuroimaging research in alcohol use disorder (AUD) has found altered functional connectivity in the brain's salience, default mode, and central executive (CEN) networks (i.e. the triple network model), though their specific associations with AUD severity and heavy drinking remains unclear. This study utilized resting-state fMRI to examine functional connectivity in these networks and measures of alcohol misuse.

METHODS

Seventy-six adult heavy drinkers completed a 7-min resting-state functional MRI scan during visual fixation. Linear regression models tested if connectivity in the three target networks was associated with past 12-month AUD symptoms and number of heavy drinking days in the past 30 days. Exploratory analyses examined correlations between connectivity clusters and impulsivity and psychopathology measures.

RESULTS

Functional connectivity within the CEN network (right and left lateral prefrontal cortex [LPFC] seeds co-activating with 13 and 15 clusters, respectively) was significantly associated with AUD symptoms (right LPFC: β = .337, p-FDR = .016; left LPFC: β = .291, p-FDR = .028) but not heavy drinking (p-FDR > .749). Post-hoc tests revealed six clusters co-activating with the CEN network were associated with AUD symptoms-right middle frontal gyrus, right inferior parietal gyrus, left middle temporal gyrus, and left and right cerebellum. Neither the default mode nor the salience network was significantly associated with alcohol variables. Connectivity in the left LPFC was correlated with monetary delay discounting (r = .25, p = .03).

CONCLUSIONS

These findings support previous associations between connectivity within the CEN network and AUD severity, providing additional specificity to the relevance of the triple network model to AUD.

Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study

In recent years, electronic cigarettes (e-cigs) have gained popularity as stylish, safe, and effective smoking cessation aids, leading to widespread consumer acceptance. Although previous research has explored the acute effects of combustible cigarettes or nicotine replacement therapy on brain functional activities, studies on e-cigs have been limited. Using fNIRS, we conducted graph theory analysis on the resting-state functional connectivity of 61 male abstinent smokers both before and after vaping e-cigs. And we performed Pearson correlation analysis to investigate the relationship between alterations in network metrics and changes in craving. E-cig use resulted in increased degree centrality, nodal efficiency, and local efficiency within the executive control network (ECN), while causing a decrease in these properties within the default model network (DMN). These alterations were found to be correlated with reductions in craving, indicating a relationship between differing network topologies in the ECN and DMN and decreased craving. These findings suggest that the impact of e-cig usage on network topologies observed in male smokers resembles the effects observed with traditional cigarettes and other forms of nicotine delivery, providing valuable insights into their addictive potential and effectiveness as aids for smoking cessation.

Solving the Global Opioid Crisis: Incorporating Genetic Addiction Risk Assessment with Personalized Dopaminergic Homeostatic Therapy and Awareness Integration Therapy

Objectives

The opioid crisis in the last few decades has mounted to a global level, impacting all areas of socioeconomic, demographic, geographic, and cultural boundaries. Traditional treatments have not been deemed to show the degree of efficacy necessary to address the crisis. The authors of this review paper have set forth an unprecedented and in-depth look into multi-factorial determinants that have contributed to the opioid crisis becoming global and multi-faceted.

Methods

For this narrative review/opinion article, we searched PsychINFO, PubMed, Google Scholar, and Web of Science databases to identify relevant articles on topics including the "opioid crisis," "opioid mechanisms," "genetics and epigenetics," "neuropharmacology," and "clinical aspects of opioid treatment and prevention." Since this was not a systematic review the articles selected could represent unitential bias.

Results

Despite some success achieved through Opioid Substitution Therapy (OST) in harm reduction, the annual mortality toll in the US alone surpasses 106,699 individuals, a figure expected to climb to 165,000 by 2025. Data from the Substance Abuse and Mental Health Services Administration's (SAMHSA) National Survey on Drug Abuse and Health (NSDUH) reveals that approximately 21.4% of individuals in the US engaged in illicit drug use in 2020, with 40.3 million individuals aged 12 or older experiencing a Substance Use Disorder (SUD). Provisional figures from the Centers for Disease Control and Prevention (CDC) indicate a troubling 15% increase in overdose deaths in 2021, rising from 93,655 in 2020 to 107,622, with opioids accounting for roughly 80,816 of these deaths.

Conclusions

We advocate reevaluating the "standard of care" and shifting towards inducing dopamine homeostasis by manipulating key neurotransmitter systems within the brain's reward cascade. We propose a paradigm shift towards a novel "standard of care" that begins with incorporating Genetic Addiction Risk Severity (GARS) testing to assess pre-addiction risk and vulnerability to opioid-induced addiction; emphasis should be placed on inducing dopamine homeostasis through safe and non-addictive alternatives like KB220, and comprehensive treatment approaches that address psychological, spiritual, and societal aspects of addiction through Awareness Integration Therapy (AIT).

The mediating role of trait impulsivity in the relation between cue-induced craving and functional connectivity within the salience network among abstinent patients with methamphetamine use disorder

Given the widespread use and relapse of methamphetamine (METH), it has caused serious public health burdens globally. However, the neurobiological basis of METH addiction remains poorly understood. Therefore, this study aimed to use magnetic resonance imaging (MRI) to investigate changes in brain networks and their connection to impulsivity and drug craving in abstinent individuals with METH use disorder (MUDs). A total of 110 MUDs and 55 age- and gender-matched healthy controls (HCs) underwent resting-state functional MRI and T1-weighted imaging scans, and completed impulsivity and cue-induced craving measurements. We applied independent component analysis to construct functional brain networks and multivariate analysis of covariance to investigate group differences in network connectivity. Mediation analyses were conducted to explore the relationships among brain-network functional connectivity (FC), impulsivity, and drug craving in the patients. MUDs showed increased connectivity in the salience network (SN) and decreased connectivity in the default mode network compared to HCs. Impulsivity was positively correlated with FC within the SN and played a completely mediating role between METH craving and FC within the SN in MUDs. These findings suggest alterations in functional brain networks underlying METH dependence, with SN potentially acting as a core neural substrate for impulse control disorders.

Data-driven connectivity profiles relate to smoking cessation outcomes

At a group level, nicotine dependence is linked to differences in resting-state functional connectivity (rs-FC) within and between three large-scale brain networks: the salience network (SN), default mode network (DMN), and frontoparietal network (FPN). Yet, individuals may display distinct patterns of rs-FC that impact treatment outcomes. This study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt. We used GIMME to identify group, subgroup, and individual-level networks of SN, DMN, and FPN connectivity. Regression models assessed whether within- and between-network connectivity of individual rs-FC models was associated with baseline cue-induced craving, and craving and use of regular cigarettes (i.e., "slips") during cessation. As a group, participants displayed shared patterns of connectivity within all three networks, and connectivity between the SN-FPN and DMN-SN. However, there was substantial heterogeneity across individuals. Individuals with greater within-network SN connectivity experienced more slips during treatment, while individuals with greater DMN-FPN connectivity experienced fewer slips. Individuals with more anticorrelated DMN-SN connectivity reported lower craving during treatment, while SN-FPN connectivity was linked to higher craving. In conclusion, in nicotine-dependent adults, GIMME identified substantial heterogeneity within and between the large-scale brain networks. Individuals with greater SN connectivity may be at increased risk for relapse during treatment, while a greater positive DMN-FPN and negative DMN-SN connectivity may be protective for individuals during smoking cessation treatment.

Altered functional brain networks in problematic smartphone and social media use: resting-state fMRI study

Nowadays, the limitless availability to the World Wide Web can lead to general Internet misuse and dependence. Currently, smartphone and social media use belong to the most prevalent Internet-related behavioral addiction forms. However, the neurobiological background of these Internet-related behavioral addictions is not sufficiently explored. In this study, these addiction forms were assessed with self-reported questionnaires. Resting-state functional magnetic resonance imaging was acquired for all participants (n = 59, 29 males) to examine functional brain networks. The resting-state networks that were discovered using independent component analysis were analyzed to estimate within network differences. Significant negative associations with social media addiction and smartphone addiction were found in the language network, the lateral visual networks, the auditory network, the sensorimotor network, the executive network and the frontoparietal network. These results suggest that problematic smartphone and social media use are associated with sensory processing and higher cognitive functioning.

Neurofeedback for alcohol addiction: Changes in resting state network activity✰

Alcohol dependence continues to be a major global burden despite significant research progress and treatment development. The aim of this study was to investigate whether neurofeedback training can alter resting state fMRI activity in brain regions that play a crucial role in addiction disorders in patients with alcohol dependence. For this purpose, a total of 52 patients were recruited for the present study, randomized, and divided into an active and a sham group. Patients in the active group received three sessions of neurofeedback training. We compared the resting state data in the active group as part of the NF training on six measurement days. When comparing the results of the active group from neurofeedback day 3 with baseline 1, a significant reduction in activated voxels in the ventral attention network area was seen. This suggests that reduced activity over the course of therapy in subjects may lead to greater independence from external stimuli. Overall, a global decrease in activated voxels within all three analysed networks compared to baseline was observed in the study. The use of resting-state data as potential biomarkers, as activity changes within these networks, may be to help restore cognitive processes and alcohol abuse-related craving and emotions.

Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders

BACKGROUND

Magnetic resonance imaging provides noninvasive tools to investigate alcohol use disorder (AUD) and nicotine use disorder (NUD) and neural phenotypes for genetic studies. A data-driven transdiagnostic approach could provide a new perspective on the neurobiology of AUD and NUD.

METHODS

Using samples of individuals with AUD (n = 140), individuals with NUD (n = 249), and healthy control participants (n = 461) from the UK Biobank, we integrated clinical, neuroimaging, and genetic markers to identify biotypes of AUD and NUD. We partitioned participants with AUD and NUD based on resting-state functional connectivity (FC) features associated with clinical metrics. A multitask artificial neural network was trained to evaluate the cluster-defined biotypes and jointly infer AUD and NUD diagnoses.

RESULTS

Three biotypes-primary NUD, mixed NUD/AUD with depression and anxiety, and mixed AUD/NUD-were identified. Multitask classifiers incorporating biotype knowledge achieved higher area under the curve (AUD: 0.76, NUD: 0.74) than single-task classifiers without biotype differentiation (AUD: 0.61, NUD: 0.64). Cerebellar FC features were important in distinguishing the 3 biotypes. The biotype of mixed NUD/AUD with depression and anxiety demonstrated the largest number of FC features (n = 5), all related to the visual cortex, that significantly differed from healthy control participants and were validated in a replication sample (p < .05). A polymorphism in TNRC6A was associated with the mixed AUD/NUD biotype in both the discovery (p = 7.3 × 10-5) and replication (p = 4.2 × 10-2) sets.

CONCLUSIONS

Biotyping and multitask learning using FC features can characterize the clinical and genetic profiles of AUD and NUD and help identify cerebellar and visual circuit markers to differentiate the AUD/NUD group from the healthy control group. These markers support a new growing body of literature.

Intrinsic Functional Connectivity between the Anterior Insular and Retrosplenial Cortex as a Moderator and Consequence of Cocaine Self-Administration in Rats

While functional brain imaging studies in humans suggest that chronic cocaine use alters functional connectivity (FC) within and between key large-scale brain networks, including the default mode network (DMN), the salience network (SN), and the central executive network (CEN), cross-sectional studies in humans are challenging to obtain brain FC prior to cocaine use. Such information is critical to reveal the relationship between individual's brain FC and the subsequent development of cocaine dependence and brain changes during abstinence. Here, we performed a longitudinal study examining functional magnetic resonance imaging (fMRI) data in male rats (n = 7), acquired before cocaine self-administration (baseline), on 1 d of abstinence following 10 d of cocaine self-administration, and again after 30 d of experimenter-imposed abstinence. Using repeated-measures analysis of variance (ANOVA) with network-based statistics (NBS), significant connectivity changes were found between anterior insular cortex (AI) of the SN, retrosplenial cortex (RSC) of the DMN, somatosensory cortex, and caudate-putamen (CPu), with AI-RSC FC showing the most robust changes between baseline and 1 d of abstinence. Additionally, the level of escalated cocaine intake is associated with AI-RSC and AI-CPu FC changes between 1 d and 30 d of abstinence; further, the subjects' AI-RSC FC prior to cocaine intake is a significant moderator for the AI-RSC changes during abstinence. These results provide novel insights into the roles of AI-RSC FC before and after cocaine intake and suggest this circuit to be a potential target to modulate large-scale network and associated behavioral changes in cocaine use disorders.

Similarity and difference in large-scale functional network alternations between behavioral addictions and substance use disorder: a comparative meta-analysis

Behavioral addiction (BA) and substance use disorder (SUD) share similarities and differences in clinical symptoms, cognitive functions, and behavioral attributes. However, little is known about whether and how functional networks in the human brain manifest commonalities and differences between BA and SUD. Voxel-wise meta-analyses of resting-state functional connectivity (rs-FC) were conducted in BA and SUD separately, followed by quantitative conjunction analyses to identify the common and distinct alterations across both the BA and SUD groups. A total of 92 datasets with 2444 addicted patients and 2712 healthy controls (HCs) were eligible for the meta-analysis. Our findings demonstrated that BA and SUD exhibited common alterations in rs-FC between frontoparietal network (FPN) and other high-level neurocognitive networks (i.e. default mode network (DMN), affective network (AN), and salience network (SN)) as well as hyperconnectivity between SN seeds and the Rolandic operculum in SSN. In addition, compared with BA, SUD exhibited several distinct within- and between-network rs-FC alterations mainly involved in the DMN and FPN. Further, altered within- and between-network rs-FC showed significant association with clinical characteristics such as the severity of addiction in BA and duration of substance usage in SUD. The common rs-FC alterations in BA and SUD exhibited the relationship with consistent aberrant behaviors in both addiction groups, such as impaired inhibition control and salience attribution. By contrast, the distinct rs-FC alterations might suggest specific substance effects on the brain neural transmitter systems in SUD.

Translational In Vivo Assays in Behavioral Biology

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Reconfigurations of Dynamic Functional Network Connectivity in Large-scale Brain Network after Prolonged Abstinence in Heroin Users

BACKGROUND

Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users.

OBJECTIVE

The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs).

METHODS

The 10-month longitudinal design was carried out for 40 HUs. The 40 healthy controls (HCs) were also enrolled. Group independent component analysis (GICA) and dFNC analysis were employed to detect the different dFNC patterns of addiction-related ICNs between HUs and HCs. The temporal properties and the graph-theoretical properties were calculated. Whether the abnormalities would be reconfigured in HUs after prolonged abstinence was then investigated.

RESULTS

Based on eight functional networks extracted from GICA, four states were identified by the dFNC analysis. Lower mean dwell time and fraction rate in state4 were found for HUs, which were increased toward HCs after prolonged abstinence. In this state, HUs at baseline showed higher dFNC of RECN-aSN, aSN- aSN and dDMN-pSN, which decreased after protracted abstinence. A similar recovery phenomenon was found for the global efficiency and path length in abstinence HUs. Mean while, the abnormal dFNC strength was correlated with craving both at baseline and after abstinence.

CONCLUSION

Our longitudinal study observed the large-scale brain network reconfiguration from the dynamic perspective in HUs after prolonged abstinence and improved the understanding of the neurobiology of prolonged abstinence in HUs.

Are We Getting High Cause the Thrill is Gone?

In the USA alone, opioid use disorder (OUD) affects approximately 27 million people. While the number of prescriptions may be declining due to increased CDC guidance and prescriber education, fatalities due to fentanyl-laced street heroin are still rising. Our laboratory has extended the overall concept of both substance and non-substance addictive behaviors, calling it "Reward Deficiency Syndrome (RDS)." Who are its victims, and how do we get this unwanted disorder? Is RDS caused by genes (Nature), environment (Neuro-epigenetics, Nurture), or both? Recent research identifies resting-state functional connectivity in the brain reward circuitry as a crucial factor. Analogously, it is of importance to acknowledge that the cumulative discharge of dopamine, governed by the nucleus accumbens (NAc) and modulated by an array of additional neurotransmitters, constitutes a cornerstone of an individual's overall well-being. Neuroimaging reveals that high-risk individuals exhibit a blunted response to stimuli, potentially due to DNA polymorphisms or epigenetic alterations. This discovery has given rise to the idea of a diminished 'thrill,' though we must consider whether this 'thrill' may have been absent from birth due to high-risk genetic predispositions for addiction. This article reviews this issue and suggests the general concept of the importance of "induction of dopamine homeostasis." We suggest coupling a validated genetic assessment (e.g., GARS) with pro-dopamine regulation (KB220) as one possible frontline modality in place of prescribing potent addictive opioids for OUD except for short time harm reduction. Could gene editing offer a 'cure' for this undesirable genetic modification at birth, influenced by the environment and carried over generations, leading to impaired dopamine and other neurotransmitter imbalances, as seen in RDS? Through dedicated global scientific exploration, we hope for a future where individuals are liberated from pain and disease, achieving an optimal state of well-being akin to the proverbial 'Garden of Eden'.

Brain and cortisol responses to smoking cues are linked in tobacco-smoking individuals

Cues associated with smoking can induce relapse, which is likely driven by cue-induced neurobiological and physiological mechanisms. For instance, greater relapse vulnerability is associated with increases in cue-induced insula activation and heightened cortisol concentrations. Determining if there is a link between such cue-induced responses is critical given the need for biomarkers that can be easily measured in clinical settings and used to drive targeted treatment. Further, comprehensively characterising biological reactions to cues promises to aid in the development of therapies that address this specific relapse risk factor. To determine whether brain and cortisol responses to smoking cues are linked, this study recruited 27 nicotine-dependent tobacco-smoking individuals and acquired whole-brain functional activation during a cue reactivity task; salivary cortisol was measured before and after scanning. The results showed that increases in blood-oxygen-level-dependent activation in the right anterior insula and right dorsolateral prefrontal cortex (DLPFC) when viewing smoking versus neutral cues were positively correlated with a post-scan rise in salivary cortisol concentrations. These brain regions have been previously implicated in substance use disorders for their role in salience, interoception and executive processes. These findings show that those who have a rise in cortisol following smoking cue exposure also have a related rise in cue-induced brain reactivity, in brain regions previously linked with heightened relapse vulnerability. This is clinically relevant as measuring cue-induced cortisol responses is a more accessible proxy for assessing the engagement of cue-induced neurobiological processes associated with the maintenance of nicotine dependence.

Aberrant functional brain network organization is associated with relapse during 1-year follow-up in alcohol-dependent patients

Alcohol dependence (AD) is a debilitating disease associated with high relapse rates even after long periods of abstinence. Thus, elucidating neurobiological substrates of relapse risk is fundamental for the development of novel targeted interventions that could promote long-lasting abstinence. In the present study, we analysed resting-state functional magnetic resonance imaging (rsfMRI) data from a sample of recently detoxified patients with AD (n = 93) who were followed up for 12 months after rsfMRI assessment. Specifically, we employed graph theoretic analyses to compare functional brain network topology and functional connectivity between future relapsers (REL, n = 59), future abstainers (ABS, n = 28) and age- and gender-matched controls (CON, n = 83). Our results suggest increased whole-brain network segregation, decreased global network integration and overall blunted connectivity strength in REL compared with CON. Conversely, we found evidence for a comparable network architecture in ABS relative to CON. At the nodal level, REL exhibited decreased integration and decoupling between multiple brain systems compared with CON, encompassing regions associated with higher-order executive functions, sensory and reward processing. Among patients with AD, increased coupling between nodes implicated in reward valuation and salience attribution constitutes a particular risk factor for future relapse. Importantly, aberrant network organization in REL was consistently associated with shorter abstinence duration during follow-up, portending to a putative neural signature of relapse risk in AD. Future research should further evaluate the potential diagnostic value of the identified changes in network topology and functional connectivity for relapse prediction at the individual subject level.

Resting-State Functional Connectivity of the Dorsal and Ventral Striatum, Impulsivity, and Severity of Use in Recently Abstinent Cocaine-Dependent Individuals

BACKGROUND

Previous studies have focused on both ventral striatum (VS) and dorsal striatum (DS) in characterizing dopaminergic deficits in addiction. Animal studies suggest VS and DS dysfunction each in association with impulsive and compulsive cocaine use during early and later stages of addiction. However, few human studies have aimed to distinguish the roles of VS and DS dysfunction in cocaine misuse.

METHODS

We examined VS and DS resting-state functional connectivity (rsFC) of 122 recently abstinent cocaine-dependent individuals (CDs) and 122 healthy controls (HCs) in 2 separate cohorts. We followed published routines in imaging data analyses and evaluated the results at a corrected threshold with age, sex, years of drinking, and smoking accounted for.

RESULTS

CDs relative to HCs showed higher VS rsFC with the left inferior frontal cortex (IFC), lower VS rsFC with the hippocampus, and higher DS rsFC with the left orbitofrontal cortex. Region-of-interest analyses confirmed the findings in the 2 cohorts examined separately. In CDs, VS-left IFC and VS-hippocampus connectivity was positively and negatively correlated with average monthly cocaine use in the prior year, respectively. In the second cohort where participants were assessed with the Barratt Impulsivity Scale (BIS-11), VS-left IFC and VS-hippocampus connectivity was also positively and negatively correlated with BIS-11 scores in CDs. In contrast, DS-orbitofrontal cortex connectivity did not relate significantly to cocaine use metrics or BIS-11 scores.

CONCLUSION

These findings associate VS rsFC with impulsivity and the severity of recent cocaine use. How DS connectivity partakes in cocaine misuse remains to be investigated.

Detection and characterization of resting state functional networks in squirrel monkey brain

Resting-state fMRI based on analyzing BOLD signals is widely used to derive functional networks in the brain and how they alter during disease or injury conditions. Resting-state networks can also be used to study brain functional connectomes across species, which provides insights into brain evolution. The squirrel monkey (SM) is a non-human primate (NHP) that is widely used as a preclinical model for experimental manipulations to understand the organization and functioning of the brain. We derived resting-state networks from the whole brain of anesthetized SMs using Independent Component Analysis of BOLD acquisitions. We detected 15 anatomically constrained resting-state networks localized in the cortical and subcortical regions as well as in the white-matter. Networks encompassing visual, somatosensory, executive control, sensorimotor, salience and default mode regions, and subcortical networks including the Hippocampus-Amygdala, thalamus, basal-ganglia and brainstem region correspond well with previously detected networks in humans and NHPs. The connectivity pattern between the networks also agrees well with previously reported seed-based resting-state connectivity of SM brain. This study demonstrates that SMs share remarkable homologous network organization with humans and other NHPs, thereby providing strong support for their suitability as a translational animal model for research and additional insight into brain evolution across species.

Mood Variability, Craving, and Substance Use Disorders: From Intrinsic Brain Network Connectivity to Daily Life Experience

BACKGROUND

Substance use disorders (SUDs) are major contributors to morbidity and mortality rates worldwide, and this global burden is attributable in large part to the chronic nature of these conditions. Increased mood variability might represent a form of emotional dysregulation that may have particular significance for the risk of relapse in SUD, independent of mood severity or diagnostic status. However, the neural biomarkers that underlie mood variability remain poorly understood.

METHODS

Ecological momentary assessment was used to assess mood variability, craving, and substance use in real time in 54 patients treated for addiction to alcohol, cannabis, or nicotine and 30 healthy control subjects. Such data were jointly examined relative to spectral dynamic causal modeling of effective brain connectivity within 4 networks involved in emotion generation and regulation.

RESULTS

Differences in effective connectivity were related to daily life variability of emotional states experienced by persons with SUD, and mood variability was associated with craving intensity. Relative to the control participants, effective connectivity was decreased for patients in the prefrontal control networks and increased in the emotion generation networks. Findings revealed that effective connectivity within the patient group was modulated by mood variability.

CONCLUSIONS

The intrinsic causal dynamics in large-scale neural networks underlying emotion regulation play a predictive role in a patient's susceptibility to experiencing mood variability (and, subsequently, craving) in daily life. The findings represent an important step toward informing interventional research through biomarkers of factors that increase the risk of relapse in persons with SUD.

Non-Opioid Anesthetics Addiction: A Review of Current Situation and Mechanism

Drug addiction is one of the major worldwide health problems, which will have serious adverse consequences on human health and significantly burden the social economy and public health. Drug abuse is more common in anesthesiologists than in the general population because of their easier access to controlled substances. Although opioids have been generally considered the most commonly abused drugs among anesthesiologists and nurse anesthetists, the abuse of non-opioid anesthetics has been increasingly severe in recent years. The purpose of this review is to provide an overview of the clinical situation and potential molecular mechanisms of non-opioid anesthetics addiction. This review incorporates the clinical and biomolecular evidence supporting the abuse potential of non-opioid anesthetics and the foreseeable mechanism causing the non-opioid anesthetics addiction phenotypes, promoting a better understanding of its pathogenesis and helping to find effective preventive and curative strategies.

Psychedelic therapy in the treatment of addiction: the past, present and future

Psychedelic therapy has witnessed a resurgence in interest in the last decade from the scientific and medical communities with evidence now building for its safety and efficacy in treating a range of psychiatric disorders including addiction. In this review we will chart the research investigating the role of these interventions in individuals with addiction beginning with an overview of the current socioeconomic impact of addiction, treatment options, and outcomes. We will start by examining historical studies from the first psychedelic research era of the mid-late 1900s, followed by an overview of the available real-world evidence gathered from naturalistic, observational, and survey-based studies. We will then cover modern-day clinical trials of psychedelic therapies in addiction from first-in-human to phase II clinical trials. Finally, we will provide an overview of the different translational human neuropsychopharmacology techniques, including functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), that can be applied to foster a mechanistic understanding of therapeutic mechanisms. A more granular understanding of the treatment effects of psychedelics will facilitate the optimisation of the psychedelic therapy drug development landscape, and ultimately improve patient outcomes.

Disrupted Dynamic Interactions Between Large-Scale Brain Networks in Cocaine Users Are Associated With Dependence Severity

BACKGROUND

Substance use disorder is conceptualized as a neuropsychiatric disease with multifaceted phenotypic manifestations including disrupted interactions between brain networks. While the current understanding of brain network interactions is mostly based on static functional connectivity, accumulating evidence suggests that temporal dynamics of these network interactions may better reflect brain function and disease-related dysfunction. We thus investigated brain dynamics in cocaine use disorder and assessed their relationship with cocaine dependence severity.

METHODS

Using a time frame analytical approach on resting-state functional magnetic resonance imaging data of 54 cocaine users and 54 age- and sex-matched healthy control participants, we identified temporally recurring brain network configuration patterns, termed brain states. With Menon's triple network model as a guide, we characterized these state dynamics by quantifying their occurrence rate and transition probability. Group differences in the state dynamics and their association with cocaine dependence were assessed.

RESULTS

Three recurrent brain states with spatial patterns resembling the default mode, salience, and executive control networks were identified. Compared with healthy control subjects, cocaine users showed a higher default mode state occurrence rate and higher probability of transitioning from the salience state to the default mode state, with the former being attributed to the latter. A composite state transition probability negatively correlated with cocaine dependence severity.

CONCLUSIONS

Our results provide novel evidence supporting the triple network model. While confirming hyperactivity of default mode network in cocaine users, our findings indicate the failure of salience network in toggling between default mode and executive control networks in cocaine use disorder.

Connecting Circuits with Networks in Addiction Neuroscience: A Salience Network Perspective

Human neuroimaging has demonstrated the existence of large-scale functional networks in the cerebral cortex consisting of topographically distant brain regions with functionally correlated activity. The salience network (SN), which is involved in detecting salient stimuli and mediating inter-network communication, is a crucial functional network that is disrupted in addiction. Individuals with addiction display dysfunctional structural and functional connectivity of the SN. Furthermore, while there is a growing body of evidence regarding the SN, addiction, and the relationship between the two, there are still many unknowns, and there are fundamental limitations to human neuroimaging studies. At the same time, advances in molecular and systems neuroscience techniques allow researchers to manipulate neural circuits in nonhuman animals with increasing precision. Here, we describe attempts to translate human functional networks to nonhuman animals to uncover circuit-level mechanisms. To do this, we review the structural and functional connections of the salience network and its homology across species. We then describe the existing literature in which circuit-specific perturbation of the SN sheds light on how functional cortical networks operate, both within and outside the context of addiction. Finally, we highlight key outstanding opportunities for mechanistic studies of the SN.

Resting state connectivity in people living with HIV before and after stopping heavy drinking

Background

Heavy alcohol use in people living with HIV (PLWH) has widespread negative effects on neural functioning. It remains unclear whether experimentally-induced reduction in alcohol use could reverse these effects. We sought to determine the effects of 30-days drinking cessation/reduction on resting state functional connectivity in people with and without HIV.

Methods

Thirty-five participants (48.6% PLWH) demonstrating heavy alcohol use attempted to stop drinking for 30 days via contingency management (CM). MRI was acquired at baseline and after thirty days, and functional connectivity across five resting-state fMRI (rsfMRI) networks was calculated with the Conn toolbox for Matlab and examined in relation to transdermal alcohol concentration (TAC) recorded by the ankle-worn secure continuous remote alcohol monitor (SCRAM) and self-reported alcohol use (timeline follow-back; TLFB). Associations between alcohol use and reduction, HIV status, functional connectivity, and change in functional connectivity across five major rsfMRI networks were determined relative to the pre- and post-CM timepoints.

Results

Baseline resting-state functional connectivity was not significantly associated with average TAC-AUC during the pre-CM period, though higher self-reported alcohol use over the preceding 30 days was significantly associated with higher baseline connectivity within the Dorsal Attention Network (DAN; p-FDR < 0.05). Baseline connectivity within the Salience network was significantly negatively related to objective drinking reduction after intervention (DAN; p-FDR < 0.05), whereas baseline connectivity within the Limbic network was positively associated with self-reported drinking reduction (p-FDR < 0.05). Change in between-networks functional connectivity after intervention was significantly positively associated with biosensor-confirmed drinking reduction such that higher reduction was associated with stronger connectivity between the limbic and fronto-parietal control networks (p-FDR < 0.05). PLWH with lower DAN connectivity at baseline demonstrated poorer alcohol reduction than those with higher DAN connectivity at baseline.

Discussion

Lower resting-state functional connectivity of the Salience network significantly predicted stronger drinking reduction across all participants, suggesting a potential biomarker for reduced susceptibility to the environmental and social cues that often make alcohol use reduction attempts unsuccessful. Increased between-networks connectivity was observed in participants with higher alcohol reduction after CM, suggesting a positive benefit to brain connectivity associated with reduced drinking. PLWH with lower baseline DAN connectivity may not benefit as greatly from CM for alcohol reduction.

Nicotine dependence and insula subregions: functional connectivity and cue-induced activation

Nicotine dependence is a major predictor of relapse in people with Tobacco Use Disorder (TUD). Accordingly, therapies that reduce nicotine dependence may promote sustained abstinence from smoking. The insular cortex has been identified as a promising target in brain-based therapies for TUD, and has three major sub-regions (ventral anterior, dorsal anterior, and posterior) that serve distinct functional networks. How these subregions and associated networks contribute to nicotine dependence is not well understood, and therefore was the focus of this study. Sixty individuals (28 women; 18-45 years old), who smoked cigarettes daily, rated their level of nicotine dependence (on the Fagerström Test for Nicotine Dependence) and, after abstaining from smoking overnight (~12 h), underwent functional magnetic resonance imaging (fMRI) in a resting state. A subset of these participants (N = 48) also completing a cue-induced craving task during fMRI. Correlations between nicotine dependence and resting-state functional connectivity (RSFC) and cue-induced activation of the major insular sub-regions were evaluated. Nicotine dependence was negatively correlated with connectivity of the left and right dorsal, and left ventral anterior insula with regions within the superior parietal lobule (SPL), including the left precuneus. No relationship between posterior insula connectivity and nicotine dependence was found. Cue-induced activation in the left dorsal anterior insula was positively associated with nicotine dependence and negatively associated with RSFC of the same region with SPL, suggesting that craving-related responsivity in this subregion was greater among participants who were more dependent. These results may inform therapeutic approaches, such as brain stimulation, which may elicit differential clinical outcomes (e.g., dependence, craving) depending on the insular subnetwork that is targeted.

Subtypes in addiction and their neurobehavioral profiles across three functional domains

Rates of return to use in addiction treatment remain high. We argue that the development of improved treatment options will require advanced understanding of individual heterogeneity in Substance Use Disorders (SUDs). We hypothesized that considerable individual differences exist in the three functional domains underlying addiction-approach-related behavior, executive function, and negative emotionality. We included N = 593 participants from the enhanced Nathan Kline Institute-Rockland Sample community sample (ages 18-59, 67% female) that included N = 420 Controls and N = 173 with past SUDs [54% female; N = 75 Alcohol Use Disorder (AUD) only, N = 30 Cannabis Use Disorder (CUD) only, and N = 68 Multiple SUDs]. To test our a priori hypothesis that distinct neuro-behavioral subtypes exist within individuals with past SUDs, we conducted a latent profile analysis with all available phenotypic data as input (74 subscales from 18 measures), and then characterized resting-state brain function for each discovered subtype. Three subtypes with distinct neurobehavioral profiles were recovered (p < 0.05, Cohen's D: 0.4-2.8): a "Reward type" with higher approach-related behavior (N = 69); a "Cognitive type" with lower executive function (N = 70); and a "Relief type" with high negative emotionality (N = 34). For those in the Reward type, substance use mapped onto resting-state connectivity in the Value/Reward, Ventral-Frontoparietal and Salience networks; for the Cognitive type in the Auditory, Parietal Association, Frontoparietal and Salience networks; and for the Relief type in the Parietal Association, Higher Visual and Salience networks (pFDR < 0.05). Subtypes were equally distributed amongst individuals with different primary SUDs (χ2 = 4.71, p = 0.32) and gender (χ2 = 3.44, p = 0.18). Results support functionally derived subtypes, demonstrating considerable individual heterogeneity in the multi-dimensional impairments in addiction. This confirms the need for mechanism-based subtyping to inform the development of personalized addiction medicine approaches.

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.

Reward and inhibition in obesity and cigarette smoking: Neurobiological overlaps and clinical implications

Cigarette smoking and obesity are the leading causes of premature morbidity and mortality and increase the risk of all-cause mortality four-fold when comorbid. Individuals with these conditions demonstrate neurobiological and behavioral differences regarding how they respond to rewarding stimuli or engage in inhibitory control. This narrative review examines the role of reward and inhibition in cigarette smoking and obesity independently, as well as recent research demonstrating an effect of increased body mass index (BMI) on neurocognitive function in individuals who smoke. It is possible that chronic smoking and overeating of highly palatable food, contributing to obesity, dysregulates reward neurocircuitry, subsequently leading to hypofunction of brain networks associated with inhibitory control. These brain changes do not appear to be specific to food or nicotine and, as a result, can potentiate continued cross-use. Changes to reward and inhibitory function due to increased BMI may also make cessation more difficult for those comorbid for obesity and smoking.

Does combined training of biofeedback and neurofeedback affect smoking status, behavior, and longitudinal brain plasticity?

Introduction: Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, behavior and to changes in brain activity. We aimed to: (a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, (b) validate training-induced feedback learning, and (c) document effects on resting-state functional connectivity networks (rsFCN); considering gender and degree of nicotine dependence in a longitudinal design. Methods: We analyzed clinical, behavioral, and electrophysiological data from 17 smokers who completed five BF and 20 NF sessions and three evaluation stages. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs). Results: Improvements in smoking status were observed as exhaled carbon monoxide levels, Total Oxidative Stress, and Fageström scores decreased while Vitamin E levels increased across time. BF/NF promoted gains in anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after BF sessions. Discussion: Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02991781.

Resting state networks of awake adolescent and adult squirrel monkeys using ultra-high field (9.4T) functional magnetic resonance imaging

Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys ( n =12 adolescents [6 male/6 female] ∼2.5 years and n =15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (IC) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward (e.g., basal ganglia), and cognitive processes were identified in both adolescent and adult monkeys. Significant age-related differences between the adult and adolescent subjects (adult > adolescent) were found in two networks of interest: (1) the right upper occipital region with an OFC IC and (2) the left temporal cortex, bilateral visual areas, and cerebellum with the cingulate IC. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.

Significance Statement

Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization.

Disrupted functional connectivity of the brain reward system in substance use problems: A meta-analysis of functional neuroimaging studies

Extensive literature suggests that the brain reward system is crucial in understanding the neurobiology of substance use disorders. However, evidence of reliable deficits in functional connectivity across studies on substance use problems remains limited. Therefore, a voxel-wise seed-based meta-analysis using brain regions of the reward system as seeds of interest was conducted on 96 studies representing 5757 subjects with substance use problems. The ventromedial prefrontal cortex exhibited hyperconnectivity with the ventral striatum and hypoconnectivity with the amygdala and hippocampus. The executive striatum showed hyperconnectivity with the motor thalamus and dorsolateral prefrontal cortex and hypoconnectivity with the anterior cingulate cortex and anterior insula. Finally, the limbic striatum was found to be hyperconnected to the orbitofrontal cortex and hypoconnected to the precuneus compared with healthy subjects. The current study provided meta-analytical evidence of deficient functional connectivity between brain regions of the reward system and cortico-striato-thalamocortical loops in addiction. These results are consistent with deficits in motivation and habit formation occurring in addiction, and they highlight alterations in brain regions involved in socio-emotional processing and attention salience.

Executive control network resting state fMRI functional and effective connectivity and delay discounting in cocaine dependent subjects compared to healthy controls

Resting state functional magnetic resonance imaging (fMRI) has been used to study functional connectivity of brain networks in addictions. However, most studies to-date have focused on the default mode network (DMN) with fewer studies assessing the executive control network (ECN) and salience network (SN), despite well-documented cognitive executive behavioral deficits in addictions. The present study assessed the functional and effective connectivity of the ECN, DMN, and SN in cocaine dependent subjects (CD) (n = 22) compared to healthy control subjects (HC) (n = 22) matched on age and education. This study also investigated the relationship between impulsivity measured by delay discounting and functional and effective connectivity of the ECN, DMN, and SN. The Left ECN (LECN), Right ECN (RECN), DMN, and SN functional networks were identified using FSL MELODIC independent component analysis. Functional connectivity differences between CD and HC were assessed using FSL Dual Regression analysis and FSLNets. Effective connectivity differences between CD and HC were measured using the Parametric Empirical Bayes module of Dynamic Causal Modeling. The relationship between delay discounting and functional and effective connectivity were examined using regression analyses. Dynamic causal modeling (DCM) analysis showed strong evidence (posterior probability > 0.95) for CD to have greater effective connectivity than HC in the RECN to LECN pathway when tobacco use was included as a factor in the model. DCM analysis showed strong evidence for a positive association between delay discounting and effective connectivity for the RECN to LECN pathway and for the DMN to DMN self-connection. There was strong evidence for a negative association between delay discounting and effective connectivity for the DMN to RECN pathway and for the SN to DMN pathway. Results also showed strong evidence for a negative association between delay discounting and effective connectivity for the RECN to SN pathway in CD but a positive association in HC. These novel findings provide preliminary support that RECN effective connectivity may differ between CD and HC after controlling for tobacco use. RECN effective connectivity may also relate to tobacco use and impulsivity as measured by delay discounting.

Efficacy of Onabotulinum Toxin A on Obsessive–Compulsive Traits in a Population of Chronic Migraine Patients

Background: Drug addiction may play an important role in chronic migraine (CM) with medication-overuse headache (MOH). Psychiatric diseases are associated with CM, but data regarding obsessive–compulsive disorder (OCD) are lacking. We aimed to establish the prevalence of OCD traits in CM patients with MOH and the impact on onabotulinum toxin A (OBT-A) treatment. Methods: A total of 75 patients with CM and MOH undergoing treatment with OBT-A in our Headache Centre were evaluated. At baseline and after four injection sessions, we assessed the migraine burden and the presence of OCD traits with the Obsessive–Compulsive Inventory—Revised (OCI-R) test. Results: At baseline, 28% of patients had OCI-R scores compatible with borderline OCD aspects, while 22.7% were pathological. An improvement in headache was significantly associated with an increase in the number of subjects with a normal OCI-R score at T0 and T1, whereas patients with a pathological OCI-R score at T0 showed a significantly higher prevalence of CM at T1. Conclusions: Our data showed a significant rate of OCD traits at baseline, which could strengthen the hypothesis of an addictive disorder underlying CM with MOH. OCD traits seem to influence the OBT-A response. An OCD assessment could be useful in improving patients’ selections before starting treatments.