Salience and default mode network dysregulation in chronic cocaine users predict treatment outcome

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 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.

Effective connectivity of default mode network subsystems and automatic smoking behaviour among males

BACKGROUND

The default mode network (DMN) is not a single system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in tobacco use disorder (TUD) and the neurobiological features associated with smoking motivation are still unclear; thus, we sought to assess causal or direct connectivity alterations within 3 subsystems of the DMN among people with TUD.

METHODS

We recruited male smokers and nonsmokers. We conducted resting-state functional magnetic resonance imaging (rs-fMRI) and collected ratings on smoking-related clinical scales. We applied dynamic causal modelling (DCM) to rs-fMRI to characterize changes of effective connectivity in TUD from 3 DMN subsystems, including the midline core network (i.e., the posterior cingulate cortex and the anterior medial prefrontal cortex [PCC-aMPFC] core DMN), the medial temporal subsystem (MTL-DMN), and the dorsal medial prefrontal cortex subsystem (dMPFC-DMN). We used leave-one-out cross-validation to investigate whether the neural response could predict smoking reasons, evaluated using the Russell Reason for Smoking Questionnaire).

RESULTS

We recruited 88 smokers and 54 nonsmokers. Among people with TUD, the parahippocampal cortex (PHC) region showed enhanced self-connection, which was associated with the severity of TUD after nighttime withdrawal. Compared with nonsmokers, people with TUD displayed significant increased effective connectivity within the dMPFC-DMN, and decreased effective connectivity from the dMPFC-DMN to the PCC-aMPFC core DMN. Moreover, decreased effective connectivity from the lateral temporal cortex to the dMPFC could predict the smoking reason related to automatic behaviour.

LIMITATIONS

Although we found aberrance in causal connections in DMN subsystems among people with TUD, our cross-sectional study could not be used to investigate changes in effective connectivity over time and their relationship with clinical features.

CONCLUSION

This study emphasized the aberrant causal connections of different functional subsystems of the DMN in TUD and revealed the neural correlates of automatic smoking behaviours. These findings suggested DMN subsystem-derived indicators could be a potential biomarker for TUD and could be used to identify the heterogeneity in motivation for smoking behaviour.

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.

The Brain Salience Network at the Intersection of Pain and Substance use Disorders: Insights from Functional Neuroimaging Research

Purpose of Review

The brain's salience network (SN), primarily comprising the anterior insula and anterior cingulate cortex, plays a key role in detecting salient stimuli and processing physical and socioemotional pain (e.g., social rejection). Mounting evidence underscores an altered SN in the etiology and maintenance of substance use disorders (SUDs). This paper aims to synthesize recent functional neuroimaging research emphasizing the SN's involvement in SUDs and physical/socioemotional pain and explore the therapeutic prospects of targeting the SN for SUD treatment.

Recent Findings

The SN is repeatedly activated during the experience of both physical and socioemotional pain. Altered activation within the SN is associated with both SUDs and chronic pain conditions, characterized by aberrant activity and connectivity patterns as well as structural changes. Among individuals with SUDs, functional and structural alterations in the SN have been linked to abnormal salience attribution (e.g., heightened responsiveness to drug-related cues), impaired cognitive control (e.g., impulsivity), and compromised decision-making processes. The high prevalence of physical and socioemotional pain in the SUD population may further exacerbate SN alterations, thus contributing to hindered recovery progress and treatment failure. Interventions targeting the restoration of SN functioning, such as real-time functional MRI feedback, neuromodulation, and psychotherapeutic approaches, hold promise as innovative SUD treatments.

Summary

The review highlights the significance of alterations in the structure and function of the SN as potential mechanisms underlying the co-occurrence of SUDs and physical/socioemotional pain. Future work that integrates neuroimaging with other research methodologies will provide novel insights into the mechanistic role of the SN in SUDs and inform the development of next-generation treatment modalities.

The default mode network is associated with changes in internalizing and externalizing problems differently in adolescent boys and girls

Internalizing and externalizing problems that emerge during adolescence differentially increase boys' and girls' risk for developing psychiatric disorders. It is not clear, however, whether there are sex differences in the intrinsic functional architecture of the brain that underlie changes in the severity of internalizing and externalizing problems in adolescents. Using resting-state fMRI data and self-reports of behavioral problems obtained from 128 adolescents (73 females; 9-14 years old) at two timepoints, we conducted multivoxel pattern analysis to identify resting-state functional connectivity markers at baseline that predict changes in the severity of internalizing and externalizing problems in boys and girls 2 years later. We found sex-differentiated involvement of the default mode network in changes in internalizing and externalizing problems. Whereas changes in internalizing problems were associated with the dorsal medial subsystem in boys and with the medial temporal subsystem in girls, changes in externalizing problems were predicted by hyperconnectivity between core nodes of the DMN and frontoparietal network in boys and hypoconnectivity between the DMN and affective networks in girls. Our results suggest that different neural mechanisms predict changes in internalizing and externalizing problems in adolescent boys and girls and offer insights concerning mechanisms that underlie sex differences in the expression of psychopathology in adolescence.

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.

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.

Laboratory method to induce state boredom increases impulsive choice in people who use cocaine and controls

Background: Impulsive choice is associated with both cocaine use and relapse. Little is known about the influence of transient states on impulsive choice in people who use cocaine (PWUC).Objective: This study investigated the direct effects of induced boredom on impulsive choice (i.e., temporal discounting) in PWUC relative to well-matched community controls.Methods: Forty-one PWUC (≥1× cocaine use in past 3 months; 7 females) and 38 demographically matched controls (5 females) underwent two experimental conditions in counterbalanced order. Temporal discounting was assessed immediately after a standardized boredom induction task (peg-turning) and a self-selected video watched for the same duration (non-boredom). Subjective mood state and perceived task characteristics were assessed at baseline, during experimental manipulations, and after the choice task.Results: PWUC and controls were well matched on sex, age, and socioeconomic status. Groups were also similar in reported use of drugs other than cocaine, except for recent cigarette and alcohol use (PWUC > controls). As expected, peg-turning increased boredom in the sample overall, with higher boredom reported during peg-turning than the video (p < .001, η2p = .20). Participants overall exhibited greater impulsive choice after boredom than non-boredom (p = .028, η2p = .07), with no preferential effects in PWUC (p > .05, BF01 = 2.9).Conclusion: Experimentally induced boredom increased state impulsivity irrespective of cocaine use status - in PWUC and carefully matched controls - suggesting a broad link between boredom and impulsive choice. This is the first study to show that transient boredom directly increases impulsive choice. Data support a viable laboratory method to further parse the effects of boredom on impulsive choice.

Regional cerebral metabolism alterations and functional connectivity in individuals with opioid use disorder: An integrated resting-state PET/fMRI study

Individuals with opioid use disorder (OUD) have been reported to show abnormal brain metabolism and impaired coupling among brain networks such as the default mode network (DMN), salience network (SN), and executive control network (ECN). However, the characteristics of brain glucose metabolism and its related functions in the brain networks in individuals with OUD remain unknown. Thirty-six individuals with OUD and thirty matched healthy controls (HCs) were recruited in this integrated positron emission tomography/magnetic resonance imaging (PET/MRI) study. Differences in glucose metabolism were analyzed by using 18F-fluorodeoxyglucose (18F-FDG), and the corresponding coupling characteristics of the individuals with OUD were also analyzed. The individuals with OUD showed widespread bilateral hypometabolism in the middle temporal gyrus (MTG), superior temporal gyrus, angular gyrus, supramarginal gyrus, inferior parietal lobe, Rolandic operculum, and left insula, but obvious hypermetabolism in the brainstem and left cerebellum. Meanwhile, in individuals with OUD, the hypometabolism of right MTG which is included in the DMN was accompanied by decreased coupling with the left superior frontal gyrus and right superior parietal gyrus which are included in the ECN. Furthermore, individuals with OUD showed a positive correlation between the duration of heroin use and glucose metabolism of the left MTG. The individuals with OUD were characterized by widespread bilateral hypometabolism in the temporal and parietal regions but obvious hypermetabolism in the brainstem and left cerebellum. The results suggest that the hypometabolism in the temporal and parietal regions might be related to DMN dysfunction and the hypermetabolism in the brainstem and left cerebellum may be compensate for other brain regions showing hypometabolism. In particular, hypometabolism in the self-referential-related DMN regions in OUD might attenuate their relationships with the inhibitory-control-related ECN regions. These findings highlight the importance of evaluating the metabolic and functional profiles of the right MTG in future studies on the treatment of OUD.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background

Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD).

Aims

This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM).

Methods

One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8-month follow-up of abstinence. CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ (HCQfollow-up-HCQbaseline). Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.

Results

CPM could predict craving changes induced by long-term abstinence, as shown by a significant correlation between predicted and actual HCQfollow-up (r=0.417, p<0.001) and changes in HCQ (negative: r=0.334, p=0.002；positive: r=0.233, p=0.038). Identified craving-related prediction networks included the somato-motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal-parietal network (FPN)-SMN, FPN-DMN and FPN-SALN and increased connectivity of subcortical network (SCN)-DMN, SCN-SALN and SCN-SMN were positively correlated with craving levels.

Conclusions

These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.

Deficits in Key Brain Network for Social Interaction in Individuals with Schizophrenia

Individuals with schizophrenia (SZ) show impairment in social functioning. The reward network and the emotional salience network are considered to play important roles in social interaction. The current study investigated alterations in the resting-state (rs-) amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and functional connectivity (fc) in the reward network and the emotional salience network in SZ patients. MRI scans were collected from 60 subjects, including 30 SZ patients and 30 matched healthy controls. SZ symptoms were measured using the Positive and Negative Syndrome Scale (PANSS). We analyzed the ALFF, fALFF and ReHo in key brain regions in the reward network and emotional salience network as well as rs-fc among the bilateral amygdala, lateral orbitofrontal cortex (OFC), medial OFC and insula between groups. The SZ patients demonstrated increased ALFF in the right caudate and right putamen, increased fALFF and ReHo in the bilateral caudate, putamen and pallidum, along with decreased fALFF in the bilateral insula. Additionally, reduced rs-fc was found between the right lateral OFC and the left amygdala, which simultaneously belong to the reward network and the emotional salience network. These findings highlight the association between impaired social functioning in SZ patients and aberrant resting-state ALFF, fALFF, ReHo and fc. Future studies are needed to conduct network-based statistical analysis and task-state fMRI, reflecting live social interaction to advance our understanding of the mechanism of social interaction deficits in SZ.

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.

Cortico-striatal networking deficits associated with advanced HIV disease and cocaine use

Cocaine use is disproportionately prevalent in people with HIV (PWH) and is known to potentiate HIV neuropathogenesis. As both HIV and cocaine have well-documented cortico-striatal effects, PWH who use cocaine and have a history of immunosuppression may exhibit greater FC deficits compared to PWH without these conditions. However, research investigating the legacy effects of HIV immunosuppression (i.e., a history of AIDS) on cortico-striatal functional connectivity (FC) in adults with and without cocaine use is sparse. Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment data from 273 adults were analyzed to examine FC in relation to HIV disease: HIV-negative (n = 104), HIV-positive with nadir CD4 ≥ 200 (n = 96), HIV-positive with nadir CD4 < 200 (AIDS; n = 73), and cocaine use (83 COC and 190 NON). Using independent component analysis/dual regression, FC was assessed between the basal ganglia network (BGN) and five cortical networks: dorsal attention network (DAN), default mode network, left executive network, right executive network, and salience network. There were significant interaction effects such that AIDS-related BGN-DAN FC deficits emerged in COC but not in NON participants. Independent of HIV, cocaine effects emerged in FC between the BGN and executive networks. Disruption of BGN-DAN FC in AIDS/COC participants is consistent with cocaine potentiation of neuro-inflammation and may be indicative of legacy HIV immunosuppressive effects. The current study bolsters previous findings linking HIV and cocaine use with cortico-striatal networking deficits. Future research should consider the effects of the duration of HIV immunosuppression and early treatment initiation.

The complexity of cortical folding is reduced in chronic cocaine users

Cocaine use is a worldwide health problem with psychiatric, somatic and socioeconomic complications, being the second most widely used illicit drug in the world. Despite several structural neuroimaging studies, the alterations in cortical morphology associated with cocaine use and addiction are still poorly understood. In this study, we compared the complexity of cortical folding (CCF), a measure that aims to summarize the convoluted structure of the cortex between patients with cocaine addiction (n = 52) and controls (n = 36), and correlated it with characteristics of addiction and impulsivity. We found that patients with cocaine addiction had greater impulsivity and showed reduced CCF in a cluster that encompassed the left insula and the supramarginal gyrus (SMG) and in one in the left medial orbitofrontal cortex. Finally, the CCF in the left medial orbitofrontal cortex was correlated with the age of onset of cocaine addiction and with attentional impulsivity. Overall, our findings suggest that chronic cocaine use is associated with changes in the cortical surface in the fronto-parieto-limbic regions that underlie emotional regulation and these changes are associated with earlier cocaine use. Future longitudinal studies are warranted to unravel the association of these changes with the diathesis for the disorder and with the chronic use of this substance.

Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study

BACKGROUND

Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence.

METHODS

Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes.

RESULTS

Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone.

CONCLUSIONS

Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.

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

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

Abnormal neuroanatomical patterns as potential diagnostic biomarkers for cocaine use disorder

Cocaine use disorder (CUD) is a global health problem with serious consequences for both individuals and society. Previous studies on abnormal anatomical patterns in CUD have mainly used voxel-based morphometry to investigate grey matter volume changes, while surface-based morphometry (SBM) has been found to provide detail information on cortical thickness (CT), surface area and cortical meancurve, which can contribute to a better understanding of structural brain changes associated with CUD. In this study, SBM was conducted to investigate abnormal neuroanatomical patterns in CUD and whether these abnormal patterns could be used as potential diagnostic biomarkers for CUD. Sixty-eight CUD individuals and 52 matched healthy controls were enrolled, and all participants performed once MRI scanning and clinical assessments. We found that CUD individuals exhibited altered morphological indicators across widespread brain regions and these abnormal anatomical alterations were significantly predictive of CUD status. Furthermore, the CT reduction of right insula was significantly associated with years of cocaine use in CUD. These findings revealed the association of abnormal anatomical patterns in specific brain regions in CUD, which further improve the understanding of CUD pathophysiology and provide the alternative diagnostic biomarkers for CUD.

DLPFC stimulation alters large-scale brain networks connectivity during a drug cue reactivity task: A tDCS-fMRI study

Transcranial direct current stimulation (tDCS) is a promising intervention for reducing craving/consumption in individuals with substance use disorders. However, its exact mechanism of action has not yet been well explored. We aimed to examine the network-based effects of tDCS while people with methamphetamine use disorders (MUDs) were exposed to drug cues. In a randomized, double-blind sham-controlled trial with a crossover design, 15 participants with MUDs were recruited to receive 20 min of active/sham tDCS with an anode/cathode over F4/F3. MRI data, including structural and task-based functional MRI during a standard drug cue-reactivity task, were collected immediately before and after stimulation sessions. Craving scores were also recorded before and after MRI scans. Individualized head models were generated to determine brain regions with strong electric fields (EFs). Using atlas-based parcellation of head models, averaged EFs were extracted from the main nodes of three large-scale networks that showed abnormalities in MUDs; executive control (ECN), default mode (DMN), and ventral attention (VAN) networks. Main nodes with high EF intensity were used as seed regions for task-based functional connectivity (FC) [using generalized psychophysiological interaction (gPPI)] and activity [using a general linear model (GLM)] calculations. Subjective craving showed a significant reduction in immediate craving after active (-15.42 ± 5.42) compared to sham (-1 ± 2.63). In seed-to-whole brain results, the PFC node in ECN showed an enhanced PPI connectivity with precuneus and visual cortex; the cluster center in MNI (6, -84, -12); the PFC node in DMN showed a decreased PPI connectivity with contralateral parietal cortex;(-48, -60, 46). ROI-to-ROI results showed increased PPI connectivity within/between ECN-VAN while connectivity between ECN-DMN decreased. In line with connectivity, functional activity in the right PFC node in DMN decreased after tDCS while activity in PFC nodes of ECN/VAN increased. EF calculations in PFC nodes revealed that EF in DMN was outward, while the direction of EFs was inward in ECN/VAN. This study provides new insight into neural circuitry underlying MUDs that can be modulated by tDCS at the network level and specifically suggests that bilateral tDCS increases cortical excitability in ECN and VAN, while it has opposite effects on DMN that may be related to the direction of EFs.

Sign-tracking modulates reward-related neural activation to reward cues, but not reward feedback

Research shows cognitive and neurobiological overlap between sign-tracking [value-modulated attentional capture (VMAC) by response-irrelevant, discrete cues] and maladaptive behaviour (e.g. substance abuse). We investigated the neural correlates of sign-tracking in 20 adults using an additional singleton task (AST) and functional magnetic resonance imaging (fMRI). Participants responded to a target to win monetary reward, the amount of which was signalled by singleton type (reward cue: high value vs. low value). Singleton responses resulted in monetary deductions. Sign-tracking-greater distraction by high-value vs. low-value singletons (H > L)-was observed, with high-value singletons producing slower responses to the target than low-value singletons. Controlling for age and sex, analyses revealed no differential brain activity across H > L singletons. Including sign-tracking as a regressor of interest revealed increased activity (H > L singletons) in cortico-subcortical loops, regions associated with Pavlovian conditioning, reward processing, attention shifts and relative value coding. Further analyses investigated responses to reward feedback (H > L). Controlling for age and sex, increased activity (H > L reward feedback) was found in regions associated with reward anticipation, attentional control, success monitoring and emotion regulation. Including sign-tracking as a regressor of interest revealed increased activity in the temporal pole, a region related to value discrimination. Results suggest sign-tracking is associated with activation of the 'attention and salience network' in response to reward cues but not reward feedback, suggesting parcellation between the two at the level of the brain. Results add to the literature showing considerable overlap in neural systems implicated in reward processing, learning, habit formation, emotion regulation and substance craving.

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.

Resting state functional connectivity in alcohol users and co-users of other substances

Polysubstance use (PSU) is the use of more than one psychoactive substance simultaneously or independently, and occurs in roughly half of individuals who seek treatment for substance use. The current study sought to use resting state functional connectivity (rs-FC) to examine functional connectivity in participants who report using multiple or single substances. Participants were drawn from a larger neuroimaging study. From there, participants were placed into one of three groups based on their frequency of alcohol, tobacco, cannabis, and illicit drug use. The final sample consisted of 82 participants. We observed three clusters that differed significantly between the three groups; one within the salience network and two within the temporal network. Tri+ users were found to have a lesser amount of rs-FC in these regions (compared to the other two groups) and dual users were found to have a greater amount of rs-FC within these regions. Findings indicate that use of three or more substances may significantly impact rs-FC within the salience and temporal networks, and that those who use alcohol+cannabis have significantly greater rs-FC than those who use alcohol+tobacco. Research is needed to examine larger samples of PSU for comparisons across specific substance combinations.

Slow-Wave EEG Activity Correlates with Impaired Inhibitory Control in Internet Addiction Disorder

Impaired inhibitory control is a core feature of internet addiction disorder (IAD). It is therefore of interest to determine the neurophysiological markers associated with it. The present study aimed to find such biomarkers with a resting-state electroencephalogram (EEG). We specifically used scores on the Chinese Internet Addiction Scale revised edition (CIAS-R) to divide 46 participants into two groups: the IAD group (>53, n = 23) and control group (<46, n = 23). Both behavioral aspects (Go/NoGo responses and impulsivity) and EEG were measured in the lab. The results suggest that the IAD group presented a decreased slow-wave (1−8 Hz) absolute power across the whole brain. The slow-wave activities in the frontal areas were also correlated with the commission error rate in the Go/NoGo task in the IAD group. These results imply that the frontal slow-wave EEG activity may serve as a neurophysiological marker of IAD, helping to understand the underlying neural mechanisms of inhibitory control deficits in IAD and point to possible interventions.

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.

Psychedelic-Assisted Therapy for Substance Use Disorders and Potential Mechanisms of Action

Substance use disorders (SUD) represent a significant public health issue with a high need for novel and efficacious treatment options. In light of this high unmet need, recent results reporting beneficial outcomes of psychedelic-assisted therapy in SUD are particularly relevant. However, several questions remain with regard to this treatment approach. The clinical mechanisms of action of psychedelic substances in the treatment of SUD are not well understood. Closing this knowledge gap is critical to inform and optimize the psychotherapeutic embedding of the acute substance administration. In this chapter, we discuss potential mechanisms that have implications on psychotherapeutic approaches including induced neuroplasticity, alterations in brain network connectivity, reward and emotion processing, social connectedness, insight, and mystical experiences. Furthermore, we outline considerations and approaches that leverage these mechanisms in order to optimize the therapeutic embedding by maximizing synergy between substance effects and psychotherapy. Understanding the mechanisms of action, developing psychotherapeutic approaches accordingly, and evaluating their synergistic efficacy in scientific studies will be critical to advance the framework of psychedelic-assisted therapy for addiction, create evidence-based approaches, and achieve the best treatment outcome for patients with SUD.

Cox Regression Based Modeling of Functional Connectivity and Treatment Outcome for Relapse Prediction and Disease Subtyping in Substance Use Disorder

Functional magnetic resonance imaging (fMRI) has become one of the most widely used noninvasive neuroimaging technique in research of cognitive neurosciences and of neural mechanisms of neuropsychiatric/neurological diseases. A primary goal of fMRI-based neuroimaging studies is to identify biomarkers for brain-behavior relationship and ultimately perform individualized treatment outcome prognosis. However, the concern of inadequate validation and the nature of small sample sizes are associated with fMRI-based neuroimaging studies, both of which hinder the translation from scientific findings to clinical practice. Therefore, the current paper presents a modeling approach to predict time-dependent prognosis with fMRI-based brain metrics and follow-up data. This prediction modeling is a combination of seed-based functional connectivity and voxel-wise Cox regression analysis with built-in nested cross-validation, which has been demonstrated to be able to provide robust and unbiased model performance estimates. Demonstrated with a cohort of treatment-seeking cocaine users from psychosocial treatment programs with 6-month follow-up, our proposed modeling method is capable of identifying brain regions and related functional circuits that are predictive of certain follow-up behavior, which could provide mechanistic understanding of neuropsychiatric/neurological disease and clearly shows neuromodulation implications and can be used for individualized prognosis and treatment protocol design.

Longitudinal changes in network engagement during cognitive control in cocaine use disorder

BACKGROUND

Cocaine use disorder (CUD) is characterized by poor cognitive control and has limited empirically supported treatment options. Furthermore, an understanding of brain mechanisms underlying CUD is at a relatively early stage. Thus, this study aimed to investigate longitudinal alterations in functional neural networks associated with cognitive control in cocaine use disorder (CUD).

METHODS

Secondary analysis was performed on data from 44 individuals who participated in three randomized clinical trials for CUD and completed an fMRI Stroop task both at baseline and post-treatment. Independent component analysis (ICA) was performed to assess changes in functional network engagement and investigate associations with cocaine-use behaviors. Mixed linear models were performed to test for longitudinal effects on network engagement and relationships with baseline patterns of cocaine use (i.e., past-month frequency and lifetime years of use) and periods of abstinence/use between scans (i.e., percent negative urine toxicology and maximum days of contiguous abstinence).

RESULTS

Six functional networks were identified as being related to cognitive control and/or exhibiting changes in engagement following treatment. Results indicated that engagement of amygdala-striatal, middle frontal and right-frontoparietal networks were reduced over time in CUD. Less change in the amygdala-striatal network was associated with greater lifetime years of cocaine use. Additional analyses revealed that negative toxicology results and achievement of continuous abstinence were associated with greater engagement of the right-frontoparietal network.

CONCLUSIONS

Neural systems that underlie cognitive control may change over time in individuals with CUD. A longer history of cocaine-use may hinder changes in network activity, potentially impeding recovery.

Neurophysiological correlate of incubation of craving in individuals with methamphetamine use disorder

Previous studies both in laboratory animals and humans have reported that abstinence induces incubation of cue-induced drug craving for nicotine, alcohol, cocaine, and methamphetamine. However, current experimental procedures utilized to study incubation of methamphetamine craving do not incorporate the temporal dynamics of neuropsychological measures and electrophysiological activities associated with this incubation process. This study utilized the high-density electroencephalogram (EEG) signals as a rapid, inexpensive, and noninvasive measure of cue-induced craving potential. A total of 156 male individuals with methamphetamine use disorder (MUD) enrolled in this multisite, cross-sectional study. Structured clinical interview data, self-report questionnaires (cued craving, quality of sleep, impulsivity, anxiety, and depression) and resting-state, eye-closed 128 high-density channel EEG signals were collected at 5 abstinence duration time points (<1, 1-3, 3-6, 6-12, and 12-24 months) to track the neuropsychological and neurophysiological signatures. Cue-induced craving was higher after 1-3 months than after the other time points. This incubation effect was also observed for sleep quality but not for anxiety, depression, and impulsivity symptoms, along with exhibited decreased power spectrum for theta (5.5-8 Hz) and alpha (8-13 Hz), and increased in beta (16.5-26.5 Hz) frequency band. Source reconstructed resting-state EEG analysis showed increased synchronization of medial prefrontal cortex (MPFC) for the beta frequency band in 1-3 months abstinent MUD group, and associated with the incubation of craving. Remarkably, the robust incubation-related abnormalities may be driven by beta-band source space connectivity between MPFC and bilateral orbital gyrus (ORB). Our findings suggest the enhancement of beta activity in the incubation period most likely originates from a dysfunction involving frontal brain regions. This neurophysiological signature of incubation of craving can be used to identify individuals who might be most susceptible to relapse, providing a potential insight into future therapeutic interventions for MUD via neuromodulation of beta activity.

Distance disintegration characterizes node-level topological dysfunctions in cocaine addiction

Previous investigations have used global graph theory measures in order to disentangle the complexity of the neural reorganizations occurring in cocaine use disorder (CUD). However, how these global topological alterations map into individual brain network areas remains unknown. In this study, we used resting state functional magnetic resonance imaging (fMRI) data to investigate node-level topological dysfunctions in CUD. The sample was composed of 32 individuals with CUD and 32 healthy controls, matched in age, years of education and intellectual functioning. Graph theory measures of optimal connectivity distance, node strength, nodal efficiency and clustering coefficient were estimated in each participant using voxel-wise functional connectivity connectomes. CUD individuals as compared with healthy controls showed higher optimal connectivity distances in ventral striatum, insula, cerebellum, temporal cortex, lateral orbitofrontal cortex, middle frontal cortex and left hippocampus. Furthermore, clinical measures quantifying severity of dependence were positively related with optimal connectivity distances in the right rolandic operculum and the right lateral orbitofrontal cortex, whereas length of abstinence was negatively associated with optimal connectivity distances in the right temporal pole and the left insula. Our results reveal a topological distancing of cognitive and affective related areas in addiction, suggesting an overall reduction in the communication capacity of these regions.

Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder

Internet gaming disorder (IGD), a worldwide mental health issue, has been widely studied using neuroimaging techniques during the last decade. Although dysfunctions in resting-state functional connectivity have been reported in IGD, mapping relationships from abnormal connectivity patterns to behavioral measures have not been fully investigated. Connectome-based predictive modeling (CPM)-a recently developed machine-learning approach-has been used to examine potential neural mechanisms in addictions and other psychiatric disorders. To identify the resting-state connections associated with IGD, we modified the CPM approach by replacing its core learning algorithm with a support vector machine. Resting-state functional magnetic resonance imaging (fMRI) data were acquired in 72 individuals with IGD and 41 healthy comparison participants. The modified CPM was conducted with respect to classification and regression. A comparison of whole-brain and network-based analyses showed that the default-mode network (DMN) is the most informative network in predicting IGD both in classification (individual identification accuracy = 78.76%) and regression (correspondence between predicted and actual psychometric scale score: r = 0.44, P < 0.001). To facilitate the characterization of the aberrant resting-state activity in the DMN, the identified networks have been mapped into a three-subsystem division of the DMN. Results suggest that individual differences in DMN function at rest could advance our understanding of IGD and variability in disorder etiology and intervention outcomes.

An Investigation of the Impacts of Three Anesthetic Regimens on Task-Functional Magnetic Resonance Imaging and Functional Connectivity Resting-State Functional Magnetic Resonance Imaging in Sprague Dawley and Wistar Rats

Aim: The aim of this study was to investigate basic task-functional magnetic resonance imaging (fMRI) or resting-state fMRI (rs-fMRI) results on Sprague Dawley (SD) rats and Wistar rats under three anesthetic regimens. Introduction: SD rats and Wistar rats are the two-most commonly used rat strains in medical research and neuroimaging studies. It still lacks a direct comparison of basic task-fMRI and rs-fMRI results between the Wistar rats and SD rats under different anesthetic regimens. Methods: Two rat strains and different time points were adopted to investigate task-fMRI activation and rs-fMRI functional connectivity (FC) results under three kinds of anesthetic regimens (2-2.5% isoflurane only, dexmedetomidine bolus combined with a continuous infusion, and dexmedetomidine bolus combined with 0.3-0.5% isoflurane). The electrical forepaw stimulation method and seed-based FC results were used to compare the task-fMRI brain activation and rs-fMRI FC patterns between the two rat strains. Results: The results showed that Wistar rats had more robust brain activation in task fMRI experiments while exhibiting a less specific interhemispheric FC than that of SD rats under the two dexmedetomidine anesthetic regimens. Moreover, even low-level isoflurane could significantly affect task-fMRI and rs-fMRI results in both rat strains. Conclusions: SD and Wistar rats showed different brain activations and interhemispheric FC patterns under the two dexmedetomidine anesthetic regimens. These results may serve as reference information for small-animal fMRI studies. Impact statement Our study demonstrates different stimulation-induced blood oxygen level-dependent responses and functional connectivity patterns between Sprague Dawley rats and Wistar rats under three anesthetics. This study provides some reference results for different anesthetics' effects on different rat strains in different functional magnetic resonance imaging modalities.

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.

Cortical thickness and subcortical volume abnormalities in male crack-cocaine users

Crack-cocaine offers a higher risk of abuse than intranasal and intravenous use of cocaine. Yet, current treatments remain disappointing and our understanding of the mechanism of crack-cocaine neurotoxicity is still incomplete. Magnetic resonance images studies on brain changes of crack-cocaine addicts show divergent data. The present study investigated gray matter (GM) abnormalities in crack-cocaine dependents (n = 18) compared to healthy controls (n = 17). MRI data was analysed using FreeSurfer and voxel-based morphometry (VBM). FreeSurfer analysis showed that CD had decreased cortical thickness (CT) in the left inferior temporal cortex (lTC), left orbitofrontal cortex (lOFC) and left rostro frontal cortex (lRFC), enlargement in left inferior lateral ventricle, and smaller GM volume in right hippocampus and right ventral diencephalon. VBM analysis showed that CD had significantly decreased GM volume in left Putamen and left nucleus accumbens. Furthermore, we found a negative correlation between duration of crack-cocaine use and lTC CT. These results provide compelling evidence for GM abnormalities in CD and also suggest that duration of crack-cocaine use may be associated with CT alterations.

Altered power spectra in antisocial males during rest as a function of cocaine dependence: A network analysis

Abnormalities in the spectral power of offenders' neural oscillations have been noted within select Resting-State Networks (RSNs); however, no study has yet evaluated the influence of cocaine dependence, drug use severity, and psychopathic traits on these abnormalities. To this end, the present study compared rest-related power spectral characteristics between two groups of offenders (with and without a DSM-IV-TR cocaine-dependence diagnosis) and a non-offender control group. Results indicated that both offender groups presented with lower low frequency power ratio (LFPR) scores (i.e. across all RSNs) than non-offenders. These differences in LFPR scores were due to both higher high-frequency power (0.15-0.25 Hz; within seven (in non-dependent offenders) and five (in cocaine-dependent offenders) of eight investigated networks) and decreased low-frequency power (0.01-0.10 Hz; within six (in non-dependent offenders) and one (in cocaine-dependent offenders) of eight investigated networks) compared to non-offenders. Thus, both cocaine-dependent and non-dependent offenders displayed abnormal neural oscillations, suggesting that these oscillatory abnormalities could exist as neurobiological features associated with offender status. Offenders' LFPR levels correlated with lifetime years of cocaine use, but not with the level of psychopathic traits. These findings supplement our knowledge regarding the influence of substance use on resting-state activity in offenders; moreover, they provide further indication of the importance of evaluating shared/unique variance associated with drug use and pyschopathic personality traits.

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.

Long-Term Cocaine Self-administration Produces Structural Brain Changes That Correlate With Altered Cognition

BACKGROUND

An enduring question from cross-sectional clinical studies is whether the structural and functional differences often observed between cocaine users and healthy control subjects result from a history of drug use or instead reflect preexisting differences. To assess causality from drug exposure, true predrug baseline imaging and neurocognitive assessments are needed.

METHODS

We addressed this fundamental question of causality using longitudinal anatomical magnetic resonance imaging and neurocognitive assessments in rhesus macaques. Cognitive tasks employed were stimulus reversal learning as a measure of cognitive flexibility/inhibitory control and delayed match to sample as a measure of visual working memory. Time points examined were before and following 12 months of chronic cocaine (n = 8) or water (n = 6) self-administration. A magnetic resonance imaging-only time point was also obtained following 2 years of forced abstinence.

RESULTS

We identified localized patterns of gray matter density (GMD) changes that were largely concordant with cross-sectional clinical studies. These included decreases in orbitofrontal cortex, insula, amygdala, and temporal cortex. There was also a prominent increase in GMD in the caudate putamen. GMD decreases were significantly correlated with cognitive impairments across individuals only in select cortical regions. Following abstinence, changes in GMD in some regions, including the orbitofrontal cortex, insula, and amygdala, were persistent and thus may play an important role in risk of relapse following extended abstinence.

CONCLUSIONS

Cocaine use is causal in producing regional changes in GMD, and those changes appear to drive cognitive impairments.

Clinical and Functional Connectivity Outcomes of 5-Hz Repetitive Transcranial Magnetic Stimulation as an Add-on Treatment in Cocaine Use Disorder: A Double-Blind Randomized Controlled Trial

BACKGROUND

Cocaine use disorder (CUD) is a global condition lacking effective treatment. Repetitive transcranial magnetic stimulation (rTMS) may reduce craving and frequency of cocaine use, but little is known about its efficacy and neural effects. We sought to elucidate short- and long-term clinical benefits of 5-Hz rTMS as an add-on to standard treatment in patients with CUD and discern underlying functional connectivity effects using magnetic resonance imaging.

METHODS

A total of 44 patients with CUD were randomly assigned to complete the 2-week double-blind randomized controlled trial (acute phase) (sham [n = 20, 2 female] and active [n = 24, 4 female]), in which they received two daily sessions of rTMS on the left dorsolateral prefrontal cortex (PFC). Subsequently, 20 patients with CUD continued to an open-label maintenance phase for 6 months (two weekly sessions for up to 6 mo).

RESULTS

rTMS plus standard treatment for 2 weeks significantly reduced craving (baseline: 3.9 ± 3.6; 2 weeks: 1.5 ± 2.4, p = .013, d = 0.77) and impulsivity (baseline: 64.8 ± 16.8; 2 weeks: 53.1 ± 17.4, p = .011, d = 0.79) in the active group. We also found increased functional connectivity between the left dorsolateral PFC and ventromedial PFC and between the ventromedial PFC and right angular gyrus. Clinical and functional connectivity effects were maintained for 3 months, but they dissipated by 6 months. We did not observe reduction in positive results for cocaine in urine; however, self-reported frequency and grams consumed for 6 months were reduced.

CONCLUSIONS

With this randomized controlled trial, we show that 5-Hz rTMS has potential promise as an adjunctive treatment for CUD and merits further research.

Effects of long-term cocaine self-administration on brain resting-state functional connectivity in nonhuman primates

Long-term cocaine use is associated with a variety of neural and behavioral deficits that impact daily function. This study was conducted to examine the effects of chronic cocaine self-administration on resting-state functional connectivity of the dorsal anterior cingulate (dACC) and putamen-two brain regions involved in cognitive function and motoric behavior-identified in a whole brain analysis. Six adult male squirrel monkeys self-administered cocaine (0.32 mg/kg/inj) over 140 sessions. Six additional monkeys that had not received any drug treatment for ~1.5 years served as drug-free controls. Resting-state fMRI imaging sessions at 9.4 Tesla were conducted under isoflurane anesthesia. Functional connectivity maps were derived using seed regions placed in the left dACC or putamen. Results show that cocaine maintained robust self-administration with an average total intake of 367 mg/kg (range: 299-424 mg/kg). In the cocaine group, functional connectivity between the dACC seed and regions primarily involved in motoric behavior was weaker, whereas connectivity between the dACC seed and areas implicated in reward and cognitive processing was stronger. In the putamen seed, weaker widespread connectivity was found between the putamen and other motor regions as well as with prefrontal areas that regulate higher-order executive function; stronger connectivity was found with reward-related regions. dACC connectivity was associated with total cocaine intake. These data indicate that functional connectivity between regions involved in motor, reward, and cognitive processing differed between subjects with recent histories of cocaine self-administration and controls; in dACC, connectivity appears to be related to cumulative cocaine dosage during chronic exposure.

Effects of early ketamine exposure on cerebral gray matter volume and functional connectivity

Ketamine has been used for medical purposes, most typically as an anesthetic, and recent studies support its use in the treatment of depression. However, ketamine tends to be abused by adolescents and young adults. In the current study, we examined the effects of early ketamine exposure on brain structure and function. We employed MRI to assess the effects of ketamine abuse on cerebral gray matter volume (GMV) and functional connectivity (FC) in 34 users and 19 non-users, employing covariates. Ketamine users were categorized as adolescent-onset and adult-onset based on when they were first exposed to ketamine. Imaging data were processed by published routines in SPM and AFNI. The results revealed lower GMV in the left precuneus in ketamine users, with a larger decrease in the adolescent-onset group. The results from a seed-based correlation analysis show that both ketamine groups had higher functional connectivity between left precuneus (seed) and right precuneus than the control group. Compared to controls, ketamine users showed decreased GMV in the right insula, left inferior parietal lobule, left dorsolateral prefrontal cortex/superior frontal gyrus, and left medial orbitofrontal cortex. These preliminary results characterize the effects of ketamine misuse on brain structure and function and highlight the influence of earlier exposure to ketamine on the development of the brain. The precuneus, a structure of central importance to cerebral functional organization, may be particularly vulnerable to the influences of early ketamine exposure. How these structural and functional brain changes may relate to the cognitive and affective deficits remains to be determined with a large cohort of participants.

Understanding Cluster Headache Using Magnetic Resonance Imaging

Cluster headache is an excruciating pain syndrome characterized by unilateral head pain attacks, lasting between 15 and 180 min, accompanied by marked ipsilateral cranial autonomic symptoms, such as lacrimation and conjunctival injection. Despite important insights provided by neuroimaging studies and deep brain stimulation findings, the pathophysiology of cluster headache and its pathways of chronicization are still elusive. In this mini-review, we will provide an overview of the functional and structural neuroimaging studies in episodic and chronic cluster headache conditions conducted to clarify the underlying pathophysiology.

Increased Resting State Triple Network Functional Connectivity in Undergraduate Problematic Cannabis Users: A Preliminary EEG Coherence Study

An increasing body of experimental data have suggested that aberrant functional interactions between large-scale networks may be the most plausible explanation of psychopathology across multiple mental disorders, including substance-related and addictive disorders. In the current research, we have investigated the association between problematic cannabis use (PCU) and triple-network electroencephalographic (EEG) functional connectivity. Twelve participants with PCU and 24 non-PCU participants were included in the study. EEG recordings were performed during resting state (RS). The exact Low-Resolution Electromagnetic Tomography software (eLORETA) was used for all EEG analyses. Compared to non-PCU, PCU participants showed an increased delta connectivity between the salience network (SN) and central executive network (CEN), specifically, between the dorsal anterior cingulate cortex and right posterior parietal cortex. The strength of delta connectivity between the SN and CEN was positively and significantly correlated with higher problematic patterns of cannabis use after controlling for age, sex, educational level, tobacco use, problematic alcohol use, and general psychopathology (r_p = 0.40, p = 0.030). Taken together, our results show that individuals with PCU could be characterized by a specific dysfunctional interaction between the SN and CEN during RS, which might reflect the neurophysiological underpinnings of attentional and emotional processes of cannabis-related thoughts, memories, and craving.

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.

Bouncing back: Brain rehabilitation amid opioid and stimulant epidemics

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Frontoparietal event related potentials predict/track recovery.

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Frontostriatal functional magnetic resonance imaging signals predict/track recovery.

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Transcranial magnetic left prefrontal stimulation reduces craving and drug use.

Recent methamphetamine and opioid use epidemics are a major public health concern. Chronic stimulant and opioid use are characterized by significant psychosocial, physical and mental health costs, repeated relapse, and heightened risk of early death. Neuroimaging research highlights deficits in brain processes and circuitry that are linked to responsivity to drug cues over natural rewards as well as suboptimal goal-directed decision-making. Despite the need for interventions, little is known about (1) how the brain changes with prolonged abstinence or as a function of various treatments; and (2) how symptoms change as a result of neuromodulation. This review focuses on the question: What do we know about changes in brain function during recovery from opioids and stimulants such as methamphetamine and cocaine? We provide a detailed overview and critique of published research employing a wide array of neuroimaging methods – functional and structural magnetic resonance imaging, electroencephalography, event-related potentials, diffusion tensor imaging, and multiple brain stimulation technologies along with neurofeedback – to track or induce changes in drug craving, abstinence, and treatment success in stimulant and opioid users. Despite the surge of methamphetamine and opioid use in recent years, most of the research on neuroimaging techniques for recovery focuses on cocaine use. This review highlights two main findings: (1) interventions can lead to improvements in brain function, particularly in frontal regions implicated in goal-directed behavior and cognitive control, paired with reduced drug urges/craving; and (2) the targeting of striatal mechanisms implicated in drug reward may not be as cost-effective as prefrontal mechanisms, given that deep brain stimulation methods require surgery and months of intervention to produce effects. Overall, more studies are needed to replicate and confirm findings, particularly for individuals with opioid and methamphetamine use disorders.

An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings

The brain is constituted of multiple networks of functionally correlated brain areas, out of which the default-mode network (DMN) is the largest. Most existing research into the DMN has taken a corticocentric approach. Despite its resemblance with the unitary model of the limbic system, the contribution of subcortical structures to the DMN may be underappreciated. Here, we propose a more comprehensive neuroanatomical model of the DMN including subcortical structures such as the basal forebrain, cholinergic nuclei, anterior and mediodorsal thalamic nuclei. Additionally, tractography of diffusion-weighted imaging was employed to explore the structural connectivity, which revealed that the thalamus and basal forebrain are of central importance for the functioning of the DMN. The contribution of these neurochemically diverse brain nuclei reconciles previous neuroimaging with neuropathological findings in diseased brains and offers the potential for identifying a conserved homologue of the DMN in other mammalian species.

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.

The Insula: A Brain Stimulation Target for the Treatment of Addiction

Substance use disorders (SUDs) are a growing public health concern with only a limited number of approved treatments. However, even approved treatments are subject to limited efficacy with high long-term relapse rates. Current treatment approaches are typically a combination of pharmacotherapies and behavioral counselling. Growing evidence and technological advances suggest the potential of brain stimulation techniques for the treatment of SUDs. There are three main brain stimulation techniques that are outlined in this review: transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS). The insula, a region of the cerebral cortex, is known to be involved in critical aspects underlying SUDs, such as interoception, decision making, anxiety, pain perception, cognition, mood, threat recognition, and conscious urges. This review focuses on both the preclinical and clinical evidence demonstrating the role of the insula in addiction, thereby demonstrating its promise as a target for brain stimulation. Future research should evaluate the optimal parameters for brain stimulation of the insula, through the use of relevant biomarkers and clinical outcomes for SUDs.

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.