Executive control network connectivity strength protects against relapse to cocaine use

A novel deep neural network approach to detect and monitor cocaine drug abuse

PURPOSE

Cocaine is one of the most commonly used drugs that may lead to physical and mental health problems. It is necessary to identify individuals having cocaine use disorder as early as possible to monitor them properly. The objective of this work is to predict the time of cocaine use in scenarios where clinical testing is not possible. The time of cocaine use is defined as how many days before the individual has used cocaine.

METHODOLOGY

It is possible to predict the time of cocaine use based on personality traits and demographic information as features. The personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, impulsivity, and sensation seeking) along with demographic information features (education level, age, gender, country of residence, and ethnicity) have been used to predict the time of cocaine use. These features are given as inputs to long short-term memory networks (LSTM) to predict the time of cocaine use.

FINDINGS

The highest F-score for the prediction of time of cocaine use for the LSTM method is found to be 0.99. A comparative study has also been carried out using both deep neural networks and artificial neural networks to predict the time of cocaine use to demonstrate the superiority of the LSTM method. The proposed method shows promising results for predicting the time of cocaine use and can be considered for monitoring the cocaine use disorder.

PRACTICAL AND SOCIAL IMPLICATIONS

The proposed method will be an efficient tool to identify the mental health of a person if the person has cocaine use disorder. As a result, proper treatment can be given to the individual in time.

ORIGINALITY

The originality of the work is that it predicts the time of cocaine use with better accuracy. The LSTM method has not been used previously for predicting the time of cocaine use.

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.

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.

Hub disruption in HIV disease and cocaine use: A connectomics analysis of brain function

BACKGROUND

Cocaine use (CU) is prevalent in people with HIV (PWH). Both conditions are linked to changes in cognitive functioning and neural network topology. The current study utilizes graph theory to investigate functional connectomics associated with HIV and CU, focusing on disruption of densely connected nodes called hubs.

METHODS

Resting state functional magnetic resonance imaging (fMRI) from 206 adults (ages 22-55 years) were analyzed. A HIV x CU factorial design was implemented with participants in four groups: HIV+CU (n= 41), HIV only (n= 88), CU only (n= 36), and controls (n= 41). Functional connectomes were constructed, and thresholded graph metrics were calculated. Network centrality metrics - betweenness centrality (BC), participation coefficient (PC), and within module degree (WD) - were quantified into hub disruption indices (HDI). For each index, a 2×2 ANCOVA was performed controlling for education.

RESULTS

Participants were 68 % male and 74 % African-American with a mean age of 44.4 years. HIV and CU were associated with hub disruption in all three indices. Interactions were significant for HDI-PC and HDI-WD, such that HIV disease was associated with greater hub disruption among participants without CU, but not among participants with CU. Overall, lower global cognitive functioning was associated with greater hub disruption on all three indices.

CONCLUSIONS

Widespread hub disruption was evident in HIV disease and CU, highlighting topological reorganization in both diseases with neurocognitive effects. Hub-related measures inform functional connectivity disruptions in HIV disease and CU, particularly with respect to changes in network topology throughout the connectome.

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.

Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response

Cocaine use disorder (CUD) is prevalent, and repetitive transcranial magnetic stimulation (rTMS) shows promise in reducing cravings. However, the association between a consistent CUD-specific functional connectivity signature and treatment response remains unclear. Here we identify a validated functional connectivity signature from functional magnetic resonance imaging to discriminate CUD, with successful independent replication. We found increased connectivity within the visual and dorsal attention networks and between the frontoparietal control and ventral attention networks, alongside reduced connectivity between the default mode and limbic networks in patients with CUD. These connections were associated with drug use history and cognitive impairments. Using data from a randomized clinical trial, we also established the prognostic value of these functional connectivities for rTMS treatment outcomes in CUD, especially involving the frontoparietal control and default mode networks. Our findings reveal insights into the neurobiological mechanisms of CUD and link functional connectivity biomarkers with rTMS treatment response, offering potential targets for future therapeutic development.

Accelerated aging in people living with HIV: The neuroimmune feedback model

People living with HIV (PLWH) experience earlier onset of aging-related comorbidities compared to their counterparts without HIV. This paper lays out a theoretical model to explain why PLWH experience accelerated aging. Briefly, the model is structured as follows. PLWH experience disproportionately heavy burdens of psychosocial stress across the life course. This psychosocial stress increases risks for depressive symptoms and problematic substance use. Depressive symptoms and problematic substance use interfere with long-term adherence to antiretroviral therapy (ART). Lower ART adherence, in turn, exacerbates the elevated systemic inflammation stemming from HIV infection. This inflammation increases risks for aging-related comorbidities. Systemic inflammation also reduces connectivity in the brain's central executive network (CEN), a large-scale brain network that is critical for coping with stressful circumstances. This reduced capacity for coping with stress leads to further increases in depressive symptoms and problematic substance use. Together, these changes form a neuroimmune feedback loop that amplifies the impact of psychosocial stress on aging-related comorbidities. In this paper, I review the existing evidence relevant to this model and highlight directions for future research.

DRD2 TaqIA polymorphism-related functional connectivity between anterior insula and dorsolateral prefrontal cortex predicts the retention time in heroin-dependent individuals under methadone maintenance treatment

BACKGROUND

Dopamine receptor D2 (DRD2) TaqIA polymorphism has an influence on addiction treatment response and prognosis by mediating brain dopaminergic system efficacy. Insula is crucial for conscious urges to take drugs and maintain drug use. However, it remains unclear about the contribution of DRD2 TaqIA polymorphism to the regulation of insular on addiction behavioral and its relation with the therapeutic effect of methadone maintenance treatment (MMT).

METHODS

57 male former heroin dependents receiving stable MMT and 49 matched male healthy controls (HC) were enrolled. Salivary genotyping for DRD2 TaqA1 and A2 alleles, brain resting-state functional MRI scan and a 24-month follow-up for collecting illegal-drug-use information was conducted and followed by clustering of functional connectivity (FC) patterns of HC insula, insula subregion parcellation of MMT patients, comparing the whole brain FC maps between the A1 carriers and non-carriers and analyzing the correlation between the genotype-related FC of insula sub-regions with the retention time in MMT patients by Cox regression.

RESULTS

Two insula subregions were identified: the anterior insula (AI) and the posterior insula (PI) subregion. The A1 carriers had a reduced FC between the left AI and the right dorsolateral prefrontal cortex (dlPFC) relative to no carriers. And this reduced FC was a poor prognostic factor for the retention time in MMT patients.

CONCLUSION

DRD2 TaqIA polymorphism affects the retention time in heroin-dependent individuals under MMT by mediating the functional connectivity strength between left AI and right dlPFC, and the two brain regions are promising therapeutic targets for individualized treatment.

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.

Whole-brain resting-state connectivity underlying impaired inhibitory control during early versus longer-term abstinence in cocaine addiction

Lapses in inhibitory control have been linked to relapse in human drug addiction. Evidence suggests differences in inhibitory control depending on abstinence duration, but the underlying neural mechanisms remain unknown. We hypothesized that early abstinence (2-5 days) would be characterized by the strongest impairments of inhibitory control and most wide-spread deviations in resting-state functional connectivity of brain networks, while longer-term abstinence (>30 days) would be characterized by weaker impairments as compared to healthy controls. In this laboratory-based cross-sectional study, we compared individuals with Cocaine Use Disorder (iCUD) during early (cocaine urine-positive: N = 19, iCUD+; 32% female; mean age: 46.8 years) and longer-term abstinence (cocaine urine-negative: N = 29, iCUD-; 15% female; mean age: 46.6 years) to healthy controls (N = 33; 24% female; mean age: 40.9 years). We compared the groups on inhibitory control performance (Stop-Signal Task) and, using a whole-brain graph theory analysis (638 region parcellation) of functional magnetic resonance imaging (fMRI) data, we tested for group differences in resting-state brain function (local/global efficiency). We characterized how resting-state brain function was associated with inhibitory control performance within iCUD. Inhibitory control performance was worst in the early abstinence group, and intermediate in the longer-term abstinence group, as compared to the healthy control group (P < 0.01). More recent use of cocaine (CUD+ > CUD- > healthy controls) was characterized by decreased efficiency in fronto-temporal and subcortical networks (primarily in the salience, semantic, and basal ganglia networks) and increased efficiency in visual networks. Importantly, a similar functional connectivity pattern characterized impaired inhibitory control performance within iCUD (all brain analyses P < 0.05, FWE-corrected). Together, we demonstrated that a similar pattern of systematic and widespread deviations in resting-state brain efficiency, extending beyond the networks commonly investigated in human drug addiction, is linked to both abstinence duration and inhibitory control deficits in iCUD.

Hypothalamic-pituitary-adrenal and autonomic response to psychological stress in abstinent alcohol use disorder individuals with and without depressive symptomatology

BACKGROUND

Stress and depression have each been associated with relapse risk. In clinical practice, chronic alcohol use is often accompanied by poor emotional and self-regulatory processes. Tonic and phasic changes in stress responsivity impact an individual's relapse risk to alcohol. A further complicating factor is the pervasive coexistence of depressive symptoms in those with Alcohol Use Disorder (AUD), where the contribution of depressive symptomatology to these processes is not well understood. Individuals with AUD (AD) (21 with and 12 without sub-clinical depressive symptoms) and 37 social drinking controls (16 with and 21 without sub-clinical depressive symptoms) as part of a more extensive study (Fox et al., 2019). All participants were exposed to two 5-min personalized guided imagery conditions (stress and neutral) in a randomized and counterbalanced order across consecutive days. Alcohol craving, negative mood, Stroop performance, and plasma measures (cortisol, adrenocorticotrophic hormone, and salivary alpha-amylase) were collected before and after imagery exposure.

RESULTS

Elevations in autonomic response (heart rate) to imagery (stress and neutral) were observed as a function of drinking (in both depressed and non-depressed individuals with alcohol use disorder compared with depressed and non-depressed social drinkers). Conversely, suppressed cortisol following stress was observed as a function of depressive symptomatology across both drinking groups. Individuals with comorbid AD and depressive symptoms demonstrated attenuated Adrenocorticotropic Hormone and poor Stroop performance compared with the other groups, indicating an interactive effect between drinking and depression on pituitary and inhibitory systems.

CONCLUSION

Sub-clinical depressive pathophysiology may be distinct from drinking severity and may alter relapse-related stress adaptations during protracted abstinence from alcohol.

Frontal tDCS reduces alcohol relapse rates by increasing connections from left dorsolateral prefrontal cortex to addiction networks

BACKGROUND

Brain-based interventions are needed to address persistent relapse in alcohol use disorder (AUD). Neuroimaging evidence suggests higher frontal connectivity as well as higher within-network connectivity of theoretically defined addiction networks are associated with reduced relapse rates and extended abstinence during follow-up periods.

OBJECTIVE

/Hypothesis: A longitudinal randomized double-blind sham-controlled clinical trial investigated whether a non-invasive neuromodulation intervention delivered during early abstinence can (i) modulate connectivity of addiction networks supporting abstinence and (ii) improve relapse rates.

HYPOTHESES

Active transcranial direct current stimulation (tDCS) will (i) increase connectivity of addiction networks known to support abstinence and (ii) reduce relapse rates.

METHODS

Short-term abstinent AUD participants (n = 60) were assigned to 5 days of either active tDCS or sham during cognitive training. Causal discovery analysis (CDA) examined the directional influence from left dorsolateral prefrontal cortex (LDLPFC, stimulation site) to addiction networks that support abstinence.

RESULTS

Active tDCS had an effect on the average strength of CDA-determined connectivity from LDLPFC to the incentive salience and negative emotionality addiction networks - increasing in the active tDCS group only. Active tDCS had an effect on relapse rates following the intervention, with lower probability of relapse in the active tDCS vs. sham. Active tDCS showed an unexpected sex-dependent effect on relapse rates.

CONCLUSION

Our results suggest that LDLPFC stimulation delivered during early abstinence has an effect on addiction networks supporting abstinence and on relapse rates. The unexpected sex-dependent neuromodulation effects need to be further examined in larger clinical trials.

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.

A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder

Cocaine use disorder (CUD) is a prevalent substance abuse disorder, and repetitive transcranial magnetic stimulation (rTMS) has shown potential in reducing cocaine cravings. However, a robust and replicable biomarker for CUD phenotyping is lacking, and the association between CUD brain phenotypes and treatment response remains unclear. Our study successfully established a cross-validated functional connectivity signature for accurate CUD phenotyping, using resting-state functional magnetic resonance imaging from a discovery cohort, and demonstrated its generalizability in an independent replication cohort. We identified phenotyping FCs involving increased connectivity between the visual network and dorsal attention network, and between the frontoparietal control network and ventral attention network, as well as decreased connectivity between the default mode network and limbic network in CUD patients compared to healthy controls. These abnormal connections correlated significantly with other drug use history and cognitive dysfunctions, e.g., non-planning impulsivity. We further confirmed the prognostic potential of the identified discriminative FCs for rTMS treatment response in CUD patients and found that the treatment-predictive FCs mainly involved the frontoparietal control and default mode networks. Our findings provide new insights into the neurobiological mechanisms of CUD and the association between CUD phenotypes and rTMS treatment response, offering promising targets for future therapeutic development.

Acute improvement in the attention network with repetitive transcranial magnetic stimulation in Parkinson's disease

PURPOSE

To investigate the effect of two weeks of repetitive transcranial magnetic stimulation (rTMS) on the attention network in Parkinson's disease (PD) patients.

MATERIALS AND METHODS

Sixty PD patients were randomly divided into equal-sized active- and sham-rTMS groups. Executive function was assessed by neuropsychological tests including the Trail-Making Test (TMT), word fluency test, digit span, Wisconsin Card Sorting Test (WCST) and Stroop test. The attention network was evaluated by the attention network test (ANT). rTMS (5 Hz) was applied over the left dorsolateral prefrontal cortex (DLPFC) in the active-rTMS group, and the sham-rTMS group underwent sham stimulation, both for two weeks. All tests were performed before and after rTMS.

RESULTS

After active rTMS, nonparametric analysis revealed significant improvements in categories completed (CC) (p < 0.001) in the WCST and reaction times (RTs) in part 3 (p = 0.002) and the Stroop interference effect (SIE) (p < 0.001) in the Stroop test. Regarding the ANT, the RTs of the executive control network were significantly reduced (p < 0.001). There was no significant change after sham rTMS.

CONCLUSIONS

In the short term, in PD patients, rTMS improved the executive control network involved in resolving conflicting information. However, it showed milder effects on neuropsychological test outcomes assessing executive function, which may involve different neuromechanisms.Implications for rehabilitationCognitive impairment is common in patients with Parkinson's disease (PD), and it is related to functional disability and reduced quality of life.Attention is a main component of the cognitive system, and attention deficits are responsible for disability.This study demonstrates that rTMS is beneficial for cognitive rehabilitation in PD, as patients showed improved performance on the attention network test and neuropsychological tests.

Alterations of static and dynamic functional network connectivity in acute ischemic brainstem stroke

Background

Prior studies have shown abnormal brain functional network changes in patients with acute ischemic stroke. However, the alterations of dynamic functional network connectivity (FNC) in brainstem strokes have not been elucidated.

Purpose

To assess alterations of static and dynamic FNCs and determine the relationships between these and upper limb movement performance in patients with acute brainstem ischemic stroke.

Material and Methods

In total, 50 patients with acute brainstem ischemic stroke and 50 age- and sex-matched healthy controls were enrolled in the present study and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Independent component analysis was conducted to assess static and dynamic FNC patterns based on seven resting-state networks, namely, the default mode network (DMN), executive control network (ECN), attention network (AN), somatomotor network (SMN), visual network (VN), auditory network (AUN), and cerebellum network (CN).

Results

Compared with controls, patients with acute brainstem ischemic stroke exhibited wide aberrations of static FNC, including increased FNC in DMN–ECN, DMN–VN, ECN–VN, ECN–AN and AN–AUN pairs. Patients with acute brainstem ischemic stroke showed aberrant dynamic FNC in State 1, involving increased FNC aberrance in the DMN with AN, DMN with ECN, and reduced FNC in SMN–VN pairs. In State 5, patients with acute brainstem ischemic stroke showed increased FNC in DMN–VN and AN–AUN, and decreased FNC in AN–SMN pairs.

Conclusion

This study suggests that static and dynamic FNC impairment and aberrant connections exist in acute brainstem ischemic stroke, which expands what is known regarding the relationship between stroke and FNC from static and dynamic perspectives.

The effect of long-term methadone maintenance treatment on coupling among three large-scale brain networks in male heroin-dependent individuals: A resting-state fMRI study

PURPOSE

Methadone maintenance treatment (MMT) is considered as an effective and mainstream therapy for heroin dependence. However, whether long-term MMT would improve the coupling among the three core large-scale brain networks (salience, default mode, and executive control) and its relationship with the craving for heroin is unknown.

METHODS

Forty-four male heroin-dependent individuals during long-term MMT, 27 male heroin-dependent individuals after short-term detoxification/abstinence (SA), and 26 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging. We analyzed the difference in coupling among the salience, default mode, and executive control networks among the three groups and examined how the coupling among these large-scale networks was associated with craving before and after drug-cue exposure.

RESULTS

Compared with the SA group, the MMT group showed lower craving before and after cue exposure and stronger connectivity between the dorsal anterior cingulate cortex (a key node of the salience network) and key regions of the bilateral executive control network, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and dorsomedial prefrontal cortex. Among the heroin-dependent individuals, the functional connectivity was negatively correlated with the craving before and after heroin-cue exposure.

CONCLUSION

Our findings suggest that long-term MMT could increase the coupling between the salience and bilateral executive control networks and decrease craving for heroin. These findings contribute to the understanding of the neural mechanism of MMT, from the perspective of large-scale brain networks.

Disrupted intra- and inter-network connectivity in unilateral acute tinnitus with hearing loss

Purpose

Currently, the underlying neurophysiological mechanism of acute tinnitus is still poorly understood. This study aimed to explore differences in brain functional connectivity (FC) within and between resting-state networks (RSNs) in acute tinnitus patients with hearing loss (ATHL). Furthermore, it also evaluated the correlations between FC alterations and clinical characteristics.

Methods

Two matched groups of 40 patients and 40 healthy controls (HCs) were included. Independent component analysis (ICA) was employed to obtain RSNs and FC differences were calculated within RSNs. In addition, the relationships between networks were conducted using functional network connectivity (FNC) analysis. Finally, an analysis of correlation was used to evaluate the relationship between FNC abnormalities and clinical data.

Results

Results of this study found that seven major RSNs including the auditory network (AN), cerebellum network (CN), default mode network (DMN), executive control network (ECN), sensorimotor network (SMN), ventral attention network (VAN), and visual network (VN) were extracted using the group ICA in both groups. Furthermore, it was noted that the ATHL group showed aberrant FC within the CN, ECN, and VN as compared with HCs. Moreover, different patterns of network interactions were observed between groups, including the SMN-ECN, SMN-CN, ECN-AN, DMN-VAN, and DMN-CN connections. The correlations between functional disconnection and clinical characteristics in ATHL were also found in this study.

Conclusion

In conclusion, this study indicated widespread alterations of intra- and inter-network connectivity in ATHL, suggesting that multiple large-scale network dysfunctions and interactions are involved in the early stage. Furthermore, our findings may provide new perspectives to understand the neuropathophysiological mechanism of acute tinnitus.

Shared network-level functional alterations across substance use disorders: A multi-level kernel density meta-analysis of resting-state functional connectivity studies

An increasing number of neuroimaging studies indicate functional alterations in cortico-striatal loops in individuals with substance use disorders (SUD). Dysregulations in these circuits may contribute to drug-seeking and drug-consuming behaviour by impeding inhibitory control, habit formation, and reward processing. Despite evidence of network-level changes in SUD, a shared pattern of functional alterations within and between spatially distributed brain networks has not been systematically investigated. The present meta-analytic investigation aims at identifying common alterations in resting-state functional connectivity patterns across different SUD, including stimulant, heroin, alcohol, cannabis, and nicotine use. To this aim, seed-based whole-brain connectivity maps for different functional networks were extracted and subjected to multi-level kernel density analysis to identify dysfunctional networks in individuals with SUD compared with healthy controls. In addition, an exploratory analysis examined substance-specific effects as well as the influence of drug use status on the main findings. Our findings indicate a hypoconnectivity pattern for the limbic, salience, and frontoparietal networks in individuals with SUD as compared with healthy controls. The default mode network additionally exhibited a complex pattern of hypo- and hyperconnectivity across the studies. The observed disrupted connectivity between networks in SUD may associate with deficient inhibitory control mechanisms that are thought to contribute to excessive craving and automatic drug-related behaviour as well as failure in substance use cessation. The identified network-based alterations in SUD represent potential treatment targets for neuromodulation, for example, network-based real-time functional magnetic resonance imaging (fMRI) neurofeedback. Such interventions can evaluate the behavioural relevance of the identified neural circuits.

High-Frequency Transcranial Magnetic Stimulation Combined With Functional Magnetic Resonance Imaging Reveals Distinct Activation Patterns Associated With Different Dorsolateral Prefrontal Cortex Stimulation Sites

OBJECTIVES

Transcranial magnetic stimulation (TMS) has been extensively used for the treatment of depression, obsessive-compulsive disorder, and certain neurologic disorders. Despite having promising treatment efficacy, the fundamental neural mechanisms of TMS remain understudied.

MATERIALS AND METHODS

In this study, 15 healthy adult participants received simultaneous TMS and functional magnetic resonance imaging to map the modulatory effect of TMS when it was applied over three different sites in the dorsolateral prefrontal cortex. Independent component analysis (ICA) was used to identify the networks affected by TMS when applied over the different sites. The standard general linear model (GLM) analysis was used for comparison.

RESULTS

ICA showed that TMS affected the stimulation sites as well as remote brain areas, some areas/networks common across all TMS sites, and other areas/networks specific to each TMS site. In particular, TMS site and laterality differences were observed at the left executive control network. In addition, laterality differences also were observed at the dorsal anterior cingulate cortex and dorsolateral/dorsomedial prefrontal cortex. In contrast with the ICA findings, the GLM-based results mainly showed activation of auditory cortices regardless of the TMS sites.

CONCLUSIONS

Our findings support the notion that TMS could act through a top-down mechanism, indirectly modulating deep subcortical nodes by directly stimulating cortical regions.

CLINICAL TRIAL REGISTRATION

The Clinicaltrials.gov registration number for the study is NCT03394066.

Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity

Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent patterns of network abnormalities is warranted. Here we aimed at integrating rsFC abnormalities and systematically searching for large-scale functional brain networks in substance use disorder (SUD) and behavioral addictions (BA), through a coordinate-based meta-analysis of seed-based rsFC studies. A total of fifty-two studies are eligible in the meta-analysis, including 1911 SUD and BA patients and 1580 healthy controls. In addition, we performed multilevel kernel density analysis (MKDA) for the brain regions reliably involved in hyperconnectivity and hypoconnectivity in SUD and BA. Data from fifty-two studies showed that SUD was associated with putamen, caudate and middle frontal gyrus hyperconnectivity relative to healthy controls. Eight BA studies showed hyperconnectivity clusters within the putamen and medio-temporal lobe relative to healthy controls. Altered connectivity in salience or emotion-processing areas may be related to dysregulated affective and cognitive control-related networks, such as deficits in regulating elevated sensitivity to drug-related stimuli. These findings confirm that SUD and BA might be characterized by dysfunctions in specific brain networks, particularly those implicated in the core cognitive and affective functions. These findings might provide insight into the development of neural mechanistic biomarkers for SUD and BA.

Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging

Numerous brain regions have been identified as contributing to withdrawal behaviors, but it is unclear the way in which these brain regions as a whole lead to withdrawal. The search for a final common brain pathway that is involved in withdrawal remains elusive. To address this question, we implanted osmotic minipumps containing either saline, nicotine (24 mg/kg/d), cocaine (60 mg/kg/d), or methamphetamine (4 mg/kg/d) for one week in male C57BL/6J mice. After one week, the minipumps were removed and brains collected 8 h (saline, nicotine, and cocaine) or 12 h (methamphetamine) after removal. We then performed single-cell whole-brain imaging of neural activity during the withdrawal period when brains were collected. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical-driven to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway associated with withdrawal.

Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke

This study aimed to detect alterations in intra- and inter-network functional connectivity (FC) of multiple networks in acute brainstem ischemic stroke patients, and the relationship between FC and movement assessment scores to assess their ability to predict upper extremity motor impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from acute brainstem ischemic stroke patients (n = 50) and healthy controls (HCs) (n = 45). Resting-state networks (RSNs) were established based on independent component analysis (ICA) and the functional network connectivity (FNC) analysis was performed. Subsequently, correlation analysis was subsequently used to explore the relationship between FNC abnormalities and upper extremity motor impairment. Altered FC within default mode network (DMN), executive control network (ECN), the salience network (SN), auditory network (AN), and cerebellum network (CN) were found in the acute brainstem ischemic stroke group relative to HCs. Moreover, different patterns of altered network interactions were found between the patients and HCs, including the SN-CN, SN-AN, and ECN-DMN connections. Correlations between functional disconnection and upper limb dysfunction measurements in acute brainstem ischemic stroke patients were also found. This study intimated that widespread FNC impairment and altered integration existed in brainstem ischemic stroke at acute stage, suggesting that FNC disruption may be applied for early diagnosis and prediction of upper limb dysfunction in acute brainstem ischemic stroke.

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.

Can pharmacotherapy improve treatment outcomes in people with co-occurring major depressive and cocaine use disorders?

Introduction: Major depressive disorder (MDD) and cocaine use disorder (CUD) are prevalent and frequently co-occur. When co-occurring, the presence of one disorder typically negatively impacts the prognosis for the other. Given the clinical relevance, we sought to examine pharmacotherapies for co-occurring CUD and MDD. While multiple treatment options have been examined in the treatment of each condition individually, studies exploring pharmacological options for their comorbidity are fewer and not conclusive.Areas Covered: For this review, the authors searched the literature in PubMed using clinical query options for therapies and keywords relating to each condition. Then, they described potentially promising pharmacologic therapeutic options based on shared mechanisms between the two conditions and/or results from individual clinical trials conducted to date.Expert opinion: Medications like stimulants, dopamine (D3) receptors partial agonists or antagonists, antagonists of kappa opioid receptors, topiramate, and ketamine could be promising as there is significant overlap relating to reward deficiency models, antireward pathways, and altered glutamatergic systems. However, the available clinical literature on any one of these types of agents is mixed. Additionally, for some agents there is possible concern related to abuse potential (e.g. ketamine and stimulants).

Functional connectivity of dorsolateral prefrontal cortex predicts cocaine relapse: implications for neuromodulation treatment

Relapse is one of the most perplexing problems of addiction. The dorsolateral prefrontal cortex is crucially involved in numerous cognitive and affective processes that are implicated in the phenotypes of both substance use disorders and other neuropsychiatric diseases and has become the principal site to deliver transcranial magnetic stimulation for their treatment. However, the dorsolateral prefrontal cortex is an anatomically large and functionally heterogeneous region, and the specific dorsolateral prefrontal cortex locus and dorsolateral prefrontal cortex-based functional circuits that contribute to drug relapse and/or treatment outcome remain unknown. We systematically investigated the relationship of cocaine relapse with functional circuits from 98 dorsolateral prefrontal cortex regions-of-interest defined by evenly sampling the entire surface of bilateral dorsolateral prefrontal cortex in a cohort of cocaine dependent patients (n = 43, 5 Fr) following a psychosocial treatment intervention. Cox regression models were utilized to predict relapse likelihood based on dorsolateral prefrontal cortex functional connectivity strength. Functional connectivity from only 3 of the 98 dorsolateral prefrontal cortex loci, one in the left and two in the right hemisphere, significantly predicted cocaine relapse with an accuracy of 83.9%, 84.6% and 85.4%, respectively. Combining all three loci significantly improved prediction validity to 87.5%. Protective and risk circuits related to these dorsolateral prefrontal cortex loci were identified that have previously been implicated to support 'bottom up' drive to use drug and 'top down' control over behaviour together with social emotional, learning and memory processing. Three dorsolateral prefrontal cortex-centric circuits were identified that predict relapse to cocaine use with high accuracy. These functionally distinct dorsolateral prefrontal cortex-based circuits provide insights into the multiple roles played by the dorsolateral prefrontal cortex in cognitive and affective functioning that affects treatment outcome. The identified dorsolateral prefrontal cortex loci may serve as potential neuromodulation targets to be tested in subsequent clinical studies for addiction treatment and as clinically relevant biomarkers of its efficacy. Zhai et al. identify three dorsolateral prefrontal cortex (dlPFC)-centric circuits that predict cocaine relapse with high accuracy, providing insights into the multiple roles of the dlPFC in brain functioning that affects treatment outcome and suggesting the dlPFC loci as potential neuromodulation targets for addiction treatment.

Transcranial magnetic stimulation and neuroimaging for cocaine use disorder: Review and future directions

Background: Cocaine use disorder (CUD) is a public health problem with limited treatment options and a significant relapse rate. Neuroimaging studies have identified abnormal functional connectivity in individuals with substance use disorders. Neuromodulation has been proposed to target this altered neurocircuitry. Combining TMS with neuroimaging has the potential to inform identification of biomarkers, diagnosis, and treatment.Objectives: We review the literature of transcranial magnetic stimulation (TMS) with neuroimaging for CUD and outline a research path forward whereby TMS can be used to identify brain network features as diagnostic or prognostic biomarkers for treatment.Methods: We reviewed the literature for primary research studies of TMS with neuroimaging for CUD. We searched PubMed using search terms of "cocaine," "transcranial magnetic stimulation," and "neuroimaging." Identified studies were screened by title and abstract. Full-text studies were reviewed for inclusion.Results: In our initial search, we identified 73 studies. Six studies met our inclusion criteria. These studies used rTMS (n = 3) and single or paired pulse TMS (n = 3) and included a total of 289 participants. All studies used fMRI as the neuroimaging modality. The most common outcome measure was craving and cue-reactivity (n = 3).Conclusion: The literature combining TMS with neuroimaging is small and heterogeneous. We propose that combining TMS with neuroimaging will accelerate our understanding of substance use disorder neurobiology and treatment. Once network biomarkers of substance use have been identified, TMS can be used to manipulate the dysfunctional circuits in order to identify a causal relationship between connectivity and psychopathology.

Cocaine addicted rats show reduced neural activity as revealed by manganese-enhanced MRI

Cocaine addiction develops as a continuum from recreational to habitual and ultimately compulsive drug use. Cocaine addicts show reduced brain activity. However, it is not clear if this condition results from individual predisposing traits or is the result of chronic cocaine intake. A translational neuroimaging approach with an animal model distinguishing non-addict-like vs. addict-like animals may help overcome the limitations of clinical research by comparing controlled experimental conditions that are impossible to obtain in humans. Here we aimed to evaluate neuronal activity in freely moving rats by manganese enhanced magnetic resonance imaging in the 0/3crit model of cocaine addiction. We show that addict-like rats exhibit reduced neuronal activity compared to cocaine-naïve controls during the first week of abstinence. In contrast, cocaine-experienced non-addict-like rats maintained their brain activity at a level comparable to cocaine-naïve controls. We also evaluated brain activity during cocaine bingeing, finding a general reduction of brain activity in cocaine experienced rats independent of an addiction-like phenotype. These findings indicate that brain hypoactivity in cocaine addiction is associated with the development of compulsive use rather than the amount of cocaine consumed, and may be used as a potential biomarker for addiction that clearly distinguishes non-addict-like vs addict-like cocaine use.

Common and separable neural alterations in substance use disorders: A coordinate-based meta-analyses of functional neuroimaging studies in humans

Delineating common and separable neural alterations in substance use disorders (SUD) is imperative to understand the neurobiological basis of the addictive process and to inform substance‐specific treatment strategies. Given numerous functional MRI (fMRI) studies in different SUDs, a meta‐analysis could provide an opportunity to determine robust shared and substance‐specific alterations. The present study employed a coordinate‐based meta‐analysis covering fMRI studies in individuals with addictive cocaine, cannabis, alcohol, and nicotine use. The primary meta‐analysis demonstrated common alterations in primary dorsal striatal, and frontal circuits engaged in reward/salience processing, habit formation, and executive control across different substances and task‐paradigms. Subsequent sub‐analyses revealed substance‐specific alterations in frontal and limbic regions, with marked frontal and insula‐thalamic alterations in alcohol and nicotine use disorders respectively. Examining task‐specific alterations across substances revealed pronounced frontal alterations during cognitive processes yet stronger striatal alterations during reward‐related processes. Finally, an exploratory meta‐analysis revealed that neurofunctional alterations in striatal and frontal reward processing regions can already be determined with a high probability in studies with subjects with comparably short durations of use. Together the findings emphasize the role of dysregulations in frontostriatal circuits and dissociable contributions of these systems in the domains of reward‐related and cognitive processes which may contribute to substance‐specific behavioral alterations.

An insula-driven network computes decision uncertainty and promotes abstinence in chronic cocaine users

The anterior insular cortex (AIC) and its interconnected brain regions have been associated with both addiction and decision-making under uncertainty. However, the causal interactions in this uncertainty-encoding neurocircuitry and how these neural dynamics impact relapse remain elusive. Here, we used model-based fMRI to measure choice uncertainty in a motor decision task in 61 individuals with cocaine use disorder (CUD) and 25 healthy controls. CUD participants were assessed before discharge from a residential treatment program and followed for up to 24 weeks. We found that choice uncertainty was tracked by the AIC, dorsal anterior cingulate cortex (dACC) and ventral striatum (VS), across participants. Stronger activations in these regions measured pre-discharge predicted longer abstinence after discharge in individuals with CUD. Dynamic causal modeling revealed an AIC-to-dACC-directed connectivity modulated by uncertainty in controls, but a dACC-to-AIC connectivity in CUD participants. This reversal was mostly driven by early relapsers (<30 days). Furthermore, CUD individuals who displayed a stronger AIC-to-dACC excitatory connection during uncertainty encoding remained abstinent for longer periods. These findings reveal a critical role of an AIC-driven, uncertainty-encoding neurocircuitry in protecting against relapse and promoting abstinence.

Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients

Purpose: Individuals with presbycusis often show deficits in cognitive function, however, the exact neurophysiological mechanisms are not well understood. This study explored the alterations in intra- and inter-network functional connectivity (FC) of multiple networks in presbycusis patients, and further correlated FC with cognitive assessment scores to assess their ability to predict cognitive impairment.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed in 40 presbycusis patients and 40 matched controls, and 12 resting-state networks (RSNs) were identified by independent component analysis (ICA) approach. A two-sample t-test was carried out to detect the intra-network FC differences, and functional network connectivity (FNC) was calculated to compare the inter-network FC differences. Pearson or Spearman correlation analysis was subsequently used to explore the correlation between altered FC and cognitive assessment scores.

Results: Our study demonstrated that patients with presbycusis showed significantly decreased FC in the subcortical limbic network (scLN), default mode network (DMN), executive control network (ECN), and attention network (AN) compared with the control group. Moreover, the connectivity for scLN-AUN (auditory network) and VN (visual network)-DMN were found significantly increased while AN-DMN was found significantly decreased in presbycusis patients. Ultimately, this study revealed the intra- and inter-network alterations associated with some cognitive assessment scores.

Conclusion: This study observed intra- and inter-network FC alterations in presbycusis patients, and investigated that presbycusis can lead to abnormal connectivity of RSNs and plasticity compensation mechanism, which may be the basis of cognitive impairment, suggesting that FNC can be used to predict potential cognitive impairment in their early stage.

Is craving a risk factor for substance use among treatment-seeking individuals with alcohol and other drugs use disorders? A meta-analytic review

BACKGROUND

It is still unclear whether craving should be considered a key risk factor for substance-use behaviors (SUB) among treatment-seeking individuals with alcohol (AUD) and other drugs use disorders. Therefore, this study aims at clarifying this topic using a meta-analytic approach.

METHODS

Cohen's d was computed as effect size (ES) measure. Heterogeneity of ESs was computed using the Q statistic and I² index. The analyses also evaluated the impact assessment length on ESs. Furthermore, proximal effects of craving on SUB were compared to distal ones. The diagnoses of specific substance use disorders (SUDs), together with assessment instruments and research design were considered as additional moderators.

RESULTS

Thirty-six independent studies were included for a total of 4868 treatment-seeking individuals with SUDs. Patients who used substances showed slightly higher levels of craving than abstinent ones. The heterogeneity of results was large and significant. The length of period of assessment was positively related to ESs. The analyses highlighted no differences between pooled ESs of proximal and distal impacts of craving on SUB. The diagnoses of SUDs were significant moderators. Considering AUD, assessment instruments and research design were additional moderators.

CONCLUSIONS

Craving is a modest time-dependent proximal and distal risk factor for SUB among individuals with SUDs. Both the frequency of craving episodes and a heightened reactivity to craving cues are largely associated to SUB among individuals with AUD. Future studies should evaluate the mediating and moderating roles of self-regulatory mechanisms on the relationship between craving and SUB.

Baclofen-induced Changes in the Resting Brain Modulate Smoking Cue Reactivity: A Double-blind Placebo-controlled Functional Magnetic Resonance Imaging Study in Cigarette Smokers

Objective

Smoking cue-(SC) elicited craving can lead to relapse in SC-vulnerable individuals. Thus, identifying treatments that target SC-elicited craving is a top research priority. Reduced drug cue neural activity is associated with recovery and is marked by a profile of greater tonic (resting) activation in executive control regions, and increased connectivity between executive and salience regions. Evidence suggests the GABA-B agonist baclofen can reduce drug cue-elicited neural activity, potentially through its actions on the resting brain. Based on the literature, we hypothesize that baclofen’s effects in the resting brain can predict its effects during SC exposure.

Methods

In this longitudinal, double blind, placebo-controlled neuropharmacological study 43 non-abstinent, sated treatment-seeking cigarette smokers (63% male) participated in an fMRI resting-state scan and a SC-reactivity task prior to (T1) and 3 weeks following randomization (T2; baclofen: 80 mg/day; n = 21). Subjective craving reports were acquired before and after SC exposure to explicitly examine SC-induced craving.

Results

Whole-brain full-factorial analysis revealed a group-by-time interaction with greater resting brain activation of the right dorsolateral prefrontal cortex (dlPFC) at T2 in the baclofen group (BAC) (p_FWEcorr = 0.02), which was associated with reduced neural responses to SCs in key cue-reactive brain regions; the anterior ventral insula and ventromedial prefrontal cortex (p_FWEcorr < 0.01). BAC, but not the placebo group reported decreased SC-elicited craving (p = 0.02).

Conclusion

Results suggest that baclofen mitigates the reward response to SCs through an increase in tonic activation of the dlPFC, an executive control region. Through these mechanisms, baclofen may offer SC-vulnerable smokers protection from SC-induced relapse.

Triple Network Resting State Connectivity Predicts Distress Tolerance and Is Associated with Cocaine Use

Distress tolerance (DT), a predictor of substance use treatment retention and post-treatment relapse, is associated with task based neural activation in regions located within the salience (SN), default mode (DMN), and executive control networks (ECN). The impact of network connectivity on DT has yet to be investigated. The aim of the present study was to test within and between network resting-state functional connectivity (rsFC) associations with DT, and the impact of cocaine use on this relationship. Twenty-nine adults reporting regular cocaine use (CU) and 28 matched healthy control individuals (HC), underwent resting-state functional magnetic resonance imaging followed by the completion of two counterbalanced, computerized DT tasks. Dual-regression analysis was used to derive within and between network rsFC of the SN, DMN, and lateralized (left and right) ECN. Cox proportional-hazards survival models were used to test the interactive effect of rsFC and group on DT. The association between cocaine use severity, rsFC, and DT was tested within the CU group. Lower LECN and higher DMN-SN rsFC were associated with DT impairment. Greater amount of cocaine use per using day was associated with greater DMN-SN rsFC. The findings emphasize the role of neural resource allocation within the ECN and between DMN-SN on distress tolerance.

Accelerated Intermittent Theta-Burst Stimulation as a Treatment for Cocaine Use Disorder: A Proof-of-Concept Study

There are no effective treatments for cocaine use disorder (CUD), a chronic, relapsing brain disease characterized by dysregulated circuits related to cue reactivity, reward processing, response inhibition, and executive control. Transcranial magnetic stimulation (TMS) has the potential to modulate circuits and networks implicated in neuropsychiatric disorders, including addiction. Although acute applications of TMS have reduced craving in urine-negative cocaine users, the tolerability and safety of administering accelerated TMS to cocaine-positive individuals is unknown. As such, we performed a proof-of-concept study employing an intermittent theta-burst stimulation (iTBS) protocol in an actively cocaine-using sample. Although our main goal was to assess the tolerability and safety of administering three iTBS sessions daily, we also hypothesized that iTBS would reduce cocaine use in this non-treatment seeking cohort. We recruited 19 individuals with CUD to receive three open-label iTBS sessions per day, with approximately a 60-min interval between sessions, for 10 days over a 2-week period (30 total iTBS sessions). iTBS was delivered to left dorsolateral prefrontal cortex (dlPFC) with neuronavigation guidance. Compliance and safety were assessed throughout the trial. Cocaine use behavior was assessed before, during, and after the intervention and at 1- and 4-week follow-up visits. Of the 335 iTBS sessions applied, 73% were performed on participants with cocaine-positive urine tests. Nine of the 14 participants who initiated treatment received at least 26 of 30 iTBS sessions and returned for the 4-week follow-up visit. These individuals reduced their weekly cocaine consumption by 78% in amount of dollars spent and 70% in days of use relative to pre-iTBS cocaine use patterns. Similarly, individuals reduced their weekly consumption of nicotine, alcohol, and THC, suggesting iTBS modulated a common circuit across drugs of abuse. iTBS was well-tolerated, despite the expected occasional headaches. A single participant developed a transient neurological event of uncertain etiology on iTBS day 9 and cocaine-induced psychosis 2 weeks after discontinuation. It thus appears that accelerated iTBS to left dlPFC administered in active, chronic cocaine users is both feasible and tolerable in actively using cocaine participants with preliminary indications of efficacy in reducing both the amount and frequency of cocaine (and other off target drug) use. The neural underpinnings of these behavioral changes could help in the future development of effective treatment of CUD.

Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead

There is growing interest in non-invasive brain stimulation (NIBS) as a novel treatment option for substance-use disorders (SUDs). Recent momentum stems from a foundation of preclinical neuroscience demonstrating links between neural circuits and drug consuming behavior, as well as recent FDA-approval of NIBS treatments for mental health disorders that share overlapping pathology with SUDs. As with any emerging field, enthusiasm must be tempered by reason; lessons learned from the past should be prudently applied to future therapies. Here, an international ensemble of experts provides an overview of the state of transcranial-electrical (tES) and transcranial-magnetic (TMS) stimulation applied in SUDs. This consensus paper provides a systematic literature review on published data - emphasizing the heterogeneity of methods and outcome measures while suggesting strategies to help bridge knowledge gaps. The goal of this effort is to provide the community with guidelines for best practices in tES/TMS SUD research. We hope this will accelerate the speed at which the community translates basic neuroscience into advanced neuromodulation tools for clinical practice in addiction medicine.

Oxytocin-Induced Changes in Intrinsic Network Connectivity in Cocaine Use Disorder: Modulation by Gender, Childhood Trauma, and Years of Use

Cocaine use disorder (CUD) is a major public health concern with devastating social, economic, and mental health implications. A better understanding of the underlying neurobiology and phenotypic variations in individuals with CUD is necessary for the development of effective and targeted treatments. In this study, 39 women and 54 men with CUD completed a 6-min resting-state functional magnetic resonance imaging scan after intranasal oxytocin (OXY) or placebo administration. Graph-theory network analysis was used to quantify functional connectivity changes caused by OXY in striatum, anterior cingulate cortex (ACC), insula, and amygdala nodes of interest. OXY increased connectivity in the right ACC and left amygdala in males, whereas OXY increased connectivity in the right ACC and right accumbens in females. Machine learning was then used to associate treatment response (placebo minus OXY) in nodes of interest with years of cocaine use and severity of childhood trauma separately for males and females. Childhood trauma and years of cocaine use were associated with OXY-induced changes in ACC connectivity for both men and women, but connectivity changes in the amygdala were associated with years of cocaine use in men and connectivity changes in the right insula were associated with years of cocaine use in women. These findings suggest that salience network nodes (ACC and insula) are potential OXY treatment targets in CUD, with the amygdala as a treatment target for men and the accumbens as a treatment target for women.

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.

Classification of cocaine-dependent participants with dynamic functional connectivity from functional magnetic resonance imaging data

Static functional connectivity (FC) analyses based on functional magnetic resonance imaging (fMRI) data have been extensively explored for studying various psychiatric conditions in the brain, including cocaine addiction. A recently emerging, more powerful technique, dynamic functional connectivity (DFC), studies how the FC dynamics change during the course of the fMRI experiments. The aim in this paper was to develop a computational approach, using a machine learning framework, to determine if DFC features were more successful than FC features in the classification of cocaine-dependent patients and healthy controls. fMRI data were obtained from of 25 healthy and 58 cocaine-dependent participants while performing a motor response inhibition task, stop signal task. Group independent component analysis was carried out on all participant data to compute spatially independent components (ICs). Eight ICs were selected manually as relevant brain networks, which were used to classify healthy versus cocaine-dependent participants. FC and DFC measures of the chosen IC pairs were used as features for the classification algorithm. Support Vector Machines were used for both feature selection/reduction and participant classification. Based on DFC with only seven IC pairs, participants were successfully classified with 95% accuracy (and with 90% accuracy with three IC pairs), whereas static FC yielded only 81% accuracy. Visual, sensorimotor, default mode, and executive control networks, amygdala, and insula played the most significant role in the DFC-based classification. These findings support the use of DFC-based classification of fMRI data as a potential biomarker for the identification of cocaine dependence.

Connectome-Based Prediction of Cocaine Abstinence

OBJECTIVE

The authors sought to identify a brain-based predictor of cocaine abstinence by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. CPM is a predictive tool and a method of identifying networks that underlie specific behaviors ("neural fingerprints").

METHODS

Fifty-three individuals participated in neuroimaging protocols at the start of treatment for cocaine use disorder, and again at the end of 12 weeks of treatment. CPM with leave-one-out cross-validation was conducted to identify pretreatment networks that predicted abstinence (percent cocaine-negative urine samples during treatment). Networks were applied to posttreatment functional MRI data to assess changes over time and ability to predict abstinence during follow-up. The predictive ability of identified networks was then tested in a separate, heterogeneous sample of individuals who underwent scanning before treatment for cocaine use disorder (N=45).

RESULTS

CPM predicted abstinence during treatment, as indicated by a significant correspondence between predicted and actual abstinence values (r=0.42, df=52). Identified networks included connections within and between canonical networks implicated in cognitive/executive control (frontoparietal, medial frontal) and in reward responsiveness (subcortical, salience, motor/sensory). Connectivity strength did not change with treatment, and strength at posttreatment assessment also significantly predicted abstinence during follow-up (r=0.34, df=39). Network strength in the independent sample predicted treatment response with 64% accuracy by itself and 71% accuracy when combined with baseline cocaine use.

CONCLUSIONS

These data demonstrate that individual differences in large-scale neural networks contribute to variability in treatment outcomes for cocaine use disorder, and they identify specific abstinence networks that may be targeted in novel interventions.

Sex differences in tobacco smokers: Executive control network and frontostriatal connectivity

BACKGROUND

Women experience greater difficulty quitting smoking than men, which may be explained by sex differences in brain circuitry underlying cognitive control. Prior work has linked reduced interhemispheric executive control network (ECN) coupling with poor executive function, shorter time to relapse, and greater substance use. Lower structural connectivity between a key ECN hub, the dorsolateral prefrontal cortex (DLPFC), and the dorsal striatum (DS) also contributes to less efficient cognitive control recruitment, and reduced intrahemispheric connectivity between these regions has been associated with smoking relapse. Therefore, sex differences were probed by evaluating interhemispheric ECN and intrahemispheric DLPFC-DS connectivity. To assess the potential sex by nicotine interaction, a pilot sample of non-smokers was evaluated following acute nicotine and placebo administration.

METHODS

Thirty-five smokers (19 women) completed one resting state functional magnetic resonance imaging scan. Seventeen non-smokers (8 women) were scanned twice using a repeated measures design where they received 2 and 0 mg nicotine.

RESULTS

In smokers, women had less interhemispheric ECN and DLPFC-DS coupling than men. In non-smokers, there was a drug x sex interaction where women, relative to men, had weaker ECN coupling following nicotine but not placebo administration.

CONCLUSIONS

The current work indicates that nicotine-dependent women, versus men, have weaker connectivity in brain networks critically implicated in cognitive control. How these connectivity differences contribute to the behavioral aspects of smoking requires more testing. However, building on the literature, it is likely these deficits in functional connectivity contribute to the lower abstinence rates noted in women relative to men.

Changes in Global and Nodal Networks in Patients With Unipolar Depression After 3-Week Repeated Transcranial Magnetic Stimulation Treatment

Objectives: Repeated transcranial magnetic stimulation (rTMS) therapy has been applied in depressive disorders, but its neurobiological effect has not been well understood. Changes in cortical source network after treatment need to be confirmed. The present study investigated the effect of 3-week rTMS therapy on the symptom severity and cortical source network in patients with unipolar depression. Methods: Thirty-five patients with unipolar major depressive disorder participated in the study. High-frequency (10 Hz) rTMS was applied at the left dorsolateral prefrontal cortex during 3 weeks (five consecutive weekdays every week). Clinical symptoms were examined using the Hamilton Rating Scale for Depression and Anxiety. The resting state electroencephalography was recorded with 62 scalp channels before and after rTMS treatment. Results: Clinical symptoms significantly improved after rTMS treatment in both the active (p = 0.001) and sham groups (p = 0.002). However, an increased cortical source network in global and nodal levels was observed only in the active group after a 3-week treatment. Conclusions: The present study indicates that rTMS treatment leads to improved symptoms in patients with unipolar depression. Furthermore, treatment outcome of real effect was assured in changes of cortical source network.

Dynamic network dysfunction in cocaine dependence: Graph theoretical metrics and stop signal reaction time

Graphic theoretical metrics have become increasingly popular in characterizing functional connectivity of neural networks and how network connectivity is compromised in neuropsychiatric illnesses. Here, we add to this literature by describing dynamic network connectivities of 78 cocaine dependent (CD) and 85 non-drug using healthy control (HC) participants who underwent fMRI during performance of a stop signal task (SST). Compared to HC, CD showed prolonged stop signal reaction time (SSRT), consistent with deficits in response inhibition. In graph theoretical analysis of dynamic functional connectivity, we examined temporal flexibility and spatiotemporal diversity of 14 networks covering the whole brain. Temporal flexibility quantifies how frequently a brain region interacts with regions of other communities across time, with high temporal flexibility indicating that a region interacts predominantly with regions outside its own community. Spatiotemporal diversity quantifies how uniformly a brain region interacts with regions in other communities over time, with high spatiotemporal diversity indicating that the interactions are more evenly distributed across communities. Compared to HC, CD exhibited decreased temporal flexibility and increased spatiotemporal diversity in the great majority of neural networks. The graph metric measures of the default mode network negatively correlated with SSRT in CD but not HC. The findings are consistent with diminished temporal flexibility and a compensatory increase in spatiotemporal diversity, in association with impairment of a critical executive function, in cocaine addiction. More broadly, the findings suggest that graph theoretical metrics provide new insights for connectivity analyses to elucidate network dysfunction that may elude conventional measures.

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Cocaine addiction (CA) is associated with prolonged stop signal reaction time (SSRT).

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CA is associated with decreased temporal flexibility (TF) of neural networks.

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CA is associated with increased spatial temporal diversity (STD) of neural networks.

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The TF and STD of default mode network correlated negatively with SSRT in CA.

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Dynamic connectivity captures network dysfunction in link with inhibition deficits in CA.

Reduced interhemispheric executive control network coupling in men during early cocaine abstinence: A pilot study

BACKGROUND

Individuals who use cocaine have fewer cognitive resources needed to maintain abstinence. This is evidenced by blunted brain function during cognitive control tasks and reduced communication between brain regions associated with cognitive function. For instance, relapse vulnerability is heightened in individuals with less communication between the right and left frontoparietal executive control network (ECN). Given that recent cocaine use enhances such communication, it is plausible that recency of cocaine use influences interhemispheric ECN communication. However, it is unclear whether ECN communication weakens over the course of early cocaine abstinence, which may then enhance relapse risk.

METHODS

In ten men with cocaine use disorder, we conducted a preliminary assessment of the relationship between the number of days since last cocaine use (1-3days) and interhemispheric ECN coupling using resting state functional magnetic resonance imaging (fMRI).

RESULTS

Reduced interhemispheric ECN coupling was associated with increasing days since last cocaine use; weaker coupling was also associated with lower urine cocaine metabolite concentrations. This association was more prominent in prefrontal than parietal ECN-subregions.

CONCLUSIONS

Preliminary results indicate that resting state interhemispheric ECN coupling weakens within the first few days following last cocaine use. Because of the known link between reduced ECN interhemispheric coupling and relapse vulnerability, these results suggest that relapse risk may increase the longer an individual abstains during an early quit attempt. Treatments focused on reversing this coupling deficit may facilitate abstinence.