Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users

Effects of Low-Level Light Therapy on Resting-State Connectivity Following Moderate Traumatic Brain Injury: Secondary Analyses of a Double-blinded Placebo-controlled Study

Background Low-level light therapy (LLLT) has been shown to modulate recovery in patients with traumatic brain injury (TBI). However, the impact of LLLT on the functional connectivity of the brain when at rest has not been well studied. Purpose To use functional MRI to assess the effect of LLLT on whole-brain resting-state functional connectivity (RSFC) in patients with moderate TBI at acute (within 1 week), subacute (2-3 weeks), and late-subacute (3 months) recovery phases. Materials and Methods This is a secondary analysis of a prospective single-site double-blinded sham-controlled study conducted in patients presenting to the emergency department with moderate TBI from November 2015 to July 2019. Participants were randomized for LLLT and sham treatment. The primary outcome of the study was to assess structural connectivity, and RSFC was collected as the secondary outcome. MRI was used to measure RSFC in 82 brain regions in participants during the three recovery phases. Healthy individuals who did not receive treatment were imaged at a single time point to provide control values. The Pearson correlation coefficient was estimated to assess the connectivity strength for each brain region pair, and estimates of the differences in Fisher z-transformed correlation coefficients (hereafter, z differences) were compared between recovery phases and treatment groups using a linear mixed-effects regression model. These analyses were repeated for all brain region pairs. False discovery rate (FDR)-adjusted P values were computed to account for multiple comparisons. Quantile mixed-effects models were constructed to quantify the association between the Rivermead Postconcussion Symptoms Questionnaire (RPQ) score, recovery phase, and treatment group. Results RSFC was evaluated in 17 LLLT-treated participants (median age, 50 years [IQR, 25-67 years]; nine female), 21 sham-treated participants (median age, 50 years [IQR, 43-59 years]; 11 female), and 23 healthy control participants (median age, 42 years [IQR, 32-54 years]; 13 male). Seven brain region pairs exhibited a greater change in connectivity in LLLT-treated participants than in sham-treated participants between the acute and subacute phases (range of z differences, 0.37 [95% CI: 0.20, 0.53] to 0.45 [95% CI: 0.24, 0.67]; FDR-adjusted P value range, .010-.047). Thirteen different brain region pairs showed an increase in connectivity in sham-treated participants between the subacute and late-subacute phases (range of z differences, 0.17 [95% CI: 0.09, 0.25] to 0.26 [95% CI: 0.14, 0.39]; FDR-adjusted P value range, .020-.047). There was no evidence of a difference in clinical outcomes between LLLT-treated and sham-treated participants (range of differences in medians, -3.54 [95% CI: -12.65, 5.57] to -0.59 [95% CI: -7.31, 8.49]; P value range, .44-.99), as measured according to RPQ scores. Conclusion Despite the small sample size, the change in RSFC from the acute to subacute phases of recovery was greater in LLLT-treated than sham-treated participants, suggesting that acute-phase LLLT may have an impact on resting-state neuronal circuits in the early recovery phase of moderate TBI. ClinicalTrials.gov Identifier: NCT02233413 © RSNA, 2024 Supplemental material is available for this article.

Repetitive deep TMS in alcohol dependent patients halts progression of white matter changes in early abstinence

AIM

Alcohol use disorder (AUD) is the most prevalent form of addiction, with a great burden on society and limited treatment options. A recent clinical trial reported significant clinical benefits of deep transcranial magnetic stimulations (Deep TMS) targeting midline frontocortical areas. However, the underlying biological substrate remained elusive. Here, we report the effect of Deep TMS on the microstructure of white matter.

METHODS

A total of 37 (14 females) AUD treatment-seeking patients were randomized to sham or active Deep TMS. Twenty (six females) age-matched healthy controls were included. White matter integrity was evaluated by fractional anisotropy (FA). Secondary measures included brain functional connectivity and self-reports of craving and drinking units in the 3 months of follow-up period.

RESULTS

White matter integrity was compromised in patients with AUD relative to healthy controls, as reflected by the widespread reduction in FA. This alteration progressed during early abstinence (3 weeks) in the absence of Deep TMS. However, stimulation of midline frontocortical areas arrested the progression of FA changes in association with decreased craving and relapse scores. Reconstruction of axonal tracts from white-matter regions showing preserved FA values identified cortical regions in the posterior cingulate and dorsomedial prefrontal cortices where functional connectivity was persistently modulated. These effects were absent in the sham-stimulated group.

CONCLUSIONS

By integrating brain structure and function to characterize the alcohol-dependent brain, this study provides mechanistic insights into the TMS effect, pointing to myelin plasticity as a possible mediator.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Childhood Trauma, Emotional Awareness, and Neural Correlates of Long-Term Nicotine Smoking

Importance

Temporal dynamic measures provide insight into the neurobiological properties of nicotine use. It is critical to determine whether brain-based measures are associated with substance use risk factors, such as childhood trauma-related emotion dysregulation.

Objective

To assess temporal dynamic differences based on smoking status and examine the associations between childhood trauma, alexithymia, nicotine smoking, and default mode network (DMN) states.

Design, Setting, and Participants

This cross-sectional study was conducted in the Baltimore, Maryland, area at the National Institute on Drug Abuse. Participants included individuals aged 18 to 65 years who smoked nicotine long term and matched controls with no co-occurring substance use or psychiatric disorders. Participants were enrolled from August 8, 2013, to August 9, 2022. Analysis was conducted from August 2022 to July 2023.

Exposure

Long-term nicotine smoking.

Main Outcomes and Measures

The main outcome was temporal dynamic differences based on smoking status. Coactivation pattern analysis was conducted based on 16-minute resting-state functional magnetic resonance imaging; total time in, persistence of, and frequency of transitions into states were evaluated. The associations between childhood trauma (Childhood Trauma Questionnaire), alexithymia (20-item Toronto Alexithymia Scale), and DMN temporal dynamics were assessed.

Results

The sample included 204 participants (102 individuals who smoked nicotine and 102 control individuals) with a mean (SD) age of 37.53 (10.64) years (109 [53.4%] male). Compared with controls, individuals who smoked nicotine spent more time in the frontoinsular DMN (FI-DMN) state (mean difference, 25.63 seconds; 95% CI, 8.05-43.20 seconds; η2p = 0.04; P = .004 after Bonferroni correction). In those who smoked nicotine, greater alexithymia was associated with less time spent in the FI-DMN state (r, -0.26; 95% CI, -0.44 to -0.07; P = .007). In a moderated mediation analysis, alexithymia mediated the association between childhood trauma and time spent in the FI-DMN state only in individuals who smoked nicotine (c' = -0.24; 95% CI, -0.58 to -0.03; P = .02).

Conclusions and Relevance

Compared with controls, individuals who smoked nicotine spent more time in the FI-DMN state. Among those who smoked nicotine, childhood trauma-related alexithymia was associated with less time spent in the FI-DMN state, indicating that considering trauma-related factors may reveal alternative neurobiological underpinnings of substance use. These data may aid in reconciling contradictory findings in prior literature regarding the role of FI-DMN regions in substance use.

Alterations of brain activity in patients with alcohol use disorder: a resting-state fMRI study

BACKGROUND

Alcohol use disorder (AUD) has a negative impact on one's health and wastes a lot of societal resources since it damages one's brain tissue. Yet the knowledge of the neural mechanisms underlying alcohol addiction still remains limited. This study aims to investigate the neural mechanisms underlying alcohol addiction by using voxel-wise binarized degree centrality (DC), weighted DC and functional connectivity (FC) methods to analyze brain network activity in individuals with AUD.

METHODS

Thirty-three AUD patients and 29 healthy controls (HC) participated in this study. Binarized and weighted DC approach coupled with a second seed-based FC algorithm was used to assess the abnormal intrinsic hub features in AUD. We also examined the correlation between changes in functional network nodes and the severity of alcohol dependence.

RESULTS

Thirty AUD patients and 26 HC were retained after head motion correction. The spatial distribution maps of the binarized DC and weighted DC for the AUD and HC groups were roughly similar. In comparison to HC, the AUD group had decreased binarized DC and decreased weighted DC in the left precentral gyrus (PreCG) and the left inferior parietal lobule (IPL). Significantly different brain regions in the DC analysis were defined as seed points in the FC analysis. Compared with HC, changes in FC within the right inferior temporal gyrus (ITG), right middle temporal gyrus (MTG), left dorsolateral superior frontal gyrus (SFGdor), bilateral IPL, left precuneus (PCUN), left lingual gyrus (LING), right cerebellum_crus1/ITG/inferior occipital gyrus (IOG) and right superior parietal gyrus (SPG) were observed. The correlation analysis revealed that FC of right MTG-right PreCG was negatively correlated with MAST scores, and FC of right IPL-left IPL was positively correlated with ADS scores.

CONCLUSIONS

Alcohol use disorder is associated with aberrant regional activities in multiple brain areas. Binarized DC, weighted DC and FC analyses may be useful biological indicators for the detection of regional brain activities in patients with AUD. Intergroup differences in FC have also been observed in AUD patients, and these variations were connected to the severity of the symptoms. The AUD patients with lower FC value of the right IPL - left IPL has a lighter dependence on alcohol. This difference in symptom severity may be a compensation for cognitive impairment, indicating a difference in pathological pathways. Future AUD research will now have a fresh path thanks to these discoveries.

Shared and specific neurobiology in bipolar disorder and unipolar disorder: Evidence based on the connectome gradient and a transcriptome-connectome association study

BACKGROUND

Distinguishing bipolar disorder (BD) and unipolar disorder (UD) remains challenging. To identify the common and diagnosis-specific neuropathological alterations and their potential molecular mechanisms in patients with UD and BD (with a current depressive episode).

METHODS

Resting-state functional magnetic resonance imaging was obtained from 279 participants (95 BD patients, 107 UD patients and 77 health controls). Connectome gradients analysis was performed to explore the shared and diagnosis-specific gradient alterations in BD and UD. The Allen Human Brain Atlas data was used to explore the potential gene mechanisms of the gradient alterations.

RESULTS

BD and UD had shared hierarchical disorganisation, including downgrading and contraction from the unimodal sensory networks (vision and sensorimotor) to the transmodal cognitive networks (limbic, frontoparietal, dorsal attention, and default) (all P < 0.05, FDR corrected) in gradient 1 and gradient 2. The BD patients had specific connectome gradient dysfunction in the subcortical network. Moreover, the hierarchical disorganisation was closely correlated with profiles of gene expression specific to the neuroglial cells in the prefrontal cortex in BD and UD, while the most correlated gene ontology biological processes and function were concentrated in synaptic signalling, calcium ion binding, and transmembrane transporter activity.

CONCLUSION

These findings reveal the shared and diagnosis-specific neurobiological mechanism underlying BD and UD patients, which advances our understanding of the neuromechanisms of these disorders.

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

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

Negative affect and craving during abstinence from smoking are both linked to default mode network connectivity

BACKGROUND

Negative affect and craving during abstinence from cigarettes predict resumption of smoking. Therefore, understanding their neural substrates may guide development of new interventions. Negative affect and craving have traditionally been linked to functions of the brain's threat and reward networks, respectively. However, given the role of default mode network (DMN), particularly the posterior cingulate cortex (PCC), in self-related thought, we examined whether DMN activity underlies both craving and negative affective states in adults who smoke.

METHODS

46 adults who smoke abstained from smoking overnight and underwent resting-state fMRI, after self-reporting their psychological symptoms (negative affect) and craving on the Shiffman-Jarvik Withdrawal Scale and state anxiety (negative affect) on the Spielberger State-Trait Anxiety Inventory. Within-DMN functional connectivity using 3 different anterior PCC seeds was tested for correlations with self-report measures. Additionally, independent component analysis with dual regression was performed to measure associations of self-report with whole-brain connectivity of the DMN component.

RESULTS

Craving correlated positively with connectivity of all three anterior PCC seeds with posterior PCC clusters (pcorr<0.04). The measures of negative affective states correlated positively with connectivity of the DMN component to various brain regions, including posterior PCC (pcorr=0.02) and striatum (pcorr<0.008). Craving and state anxiety were correlated with connectivity of an overlapping region of PCC (pcorr=0.003). Unlike the state measures, nicotine dependence and trait anxiety were not associated with PCC connectivity within DMN.

CONCLUSIONS

Although negative affect and craving are distinct subjective states, they appear to share a common neural pathway within the DMN, particularly involving the PCC.

Daily Cannabidiol Administration for 10 Weeks Modulates Hippocampal and Amygdalar Resting-State Functional Connectivity in Cannabis Users: A Functional Magnetic Resonance Imaging Open-Label Clinical Trial

Introduction: Cannabis use is associated with brain functional changes in regions implicated in prominent neuroscientific theories of addiction. Emerging evidence suggests that cannabidiol (CBD) is neuroprotective and may reverse structural brain changes associated with prolonged heavy cannabis use. In this study, we examine how an ∼10-week exposure of CBD in cannabis users affected resting-state functional connectivity in brain regions functionally altered by cannabis use. Materials and Methods: Eighteen people who use cannabis took part in a ∼10 weeks open-label pragmatic trial of self-administered daily 200 mg CBD in capsules. They were not required to change their cannabis exposure patterns. Participants were assessed at baseline and post-CBD exposure with structural magnetic resonance imaging (MRI) and a functional MRI resting-state task (eyes closed). Seed-based connectivity analyses were run to examine changes in the functional connectivity of a priori regions-the hippocampus and the amygdala. We explored if connectivity changes were associated with cannabinoid exposure (i.e., cumulative cannabis dosage over trial, and plasma CBD concentrations and Δ9-tetrahydrocannabinol (THC) plasma metabolites postexposure), and mental health (i.e., severity of anxiety, depression, and positive psychotic symptom scores), accounting for cigarette exposure in the past month, alcohol standard drinks in the past month and cumulative CBD dose during the trial. Results: Functional connectivity significantly decreased pre-to-post the CBD trial between the anterior hippocampus and precentral gyrus, with a strong effect size (d=1.73). Functional connectivity increased between the amygdala and the lingual gyrus pre-to-post the CBD trial, with a strong effect size (d=1.19). There were no correlations with cannabinoids or mental health symptom scores. Discussion: Prolonged CBD exposure may restore/reduce functional connectivity differences reported in cannabis users. These new findings warrant replication in a larger sample, using robust methodologies-double-blind and placebo-controlled-and in the most vulnerable people who use cannabis, including those with more severe forms of Cannabis Use Disorder and experiencing worse mental health outcomes (e.g., psychosis, depression).

RNA alternative splicing impacts the risk for alcohol use disorder

Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains

With the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks. In this study, we implement the neuromark pipeline in COINSTAC, an open-source neuroimaging framework for collaborative/decentralized analysis. Decentralized exploratory analysis of nearly 2000 resting-state functional magnetic resonance imaging datasets collected at different sites across two cohorts and co-located in different countries was performed to study the resting brain functional network connectivity changes in adolescents who smoke and consume alcohol. Results showed hypoconnectivity across the majority of networks including sensory, default mode, and subcortical domains, more for alcohol than smoking, and decreased low frequency power. These findings suggest that global reduced synchronization is associated with both tobacco and alcohol use. This proof-of-concept work demonstrates the utility and incentives associated with large-scale decentralized collaborations spanning multiple sites.

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

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

Cortical hierarchy disorganization in major depressive disorder and its association with suicidality

Objectives

To explore the suicide risk-specific disruption of cortical hierarchy in major depressive disorder (MDD) patients with diverse suicide risks.

Methods

Ninety-two MDD patients with diverse suicide risks and 38 matched controls underwent resting-state functional MRI. Connectome gradient analysis and stepwise functional connectivity (SFC) analysis were used to characterize the suicide risk-specific alterations of cortical hierarchy in MDD patients.

Results

Relative to controls, patients with suicide attempts (SA) had a prominent compression from the sensorimotor system; patients with suicide ideations (SI) had a prominent compression from the higher-level systems; non-suicide patients had a compression from both the sensorimotor system and higher-level systems, although it was less prominent relative to SA and SI patients. SFC analysis further validated this depolarization phenomenon.

Conclusion

This study revealed MDD patients had suicide risk-specific disruptions of cortical hierarchy, which advance our understanding of the neuromechanisms of suicidality in MDD patients.

Alcohol use disorder-associated structural and functional characteristics of the insula

Based on our current understanding of insular regions, effects of chronic alcohol use on the insula may affect the integration of sensory-motor, socio-emotional, and cognitive function. There is no comprehensive understanding about these differences in individuals with alcohol use disorder that accounts for both structural and functional differences related to chronic alcohol use. The purpose of this study was to investigate these variations in both the anterior and posterior insula in persons with alcohol use disorder. We investigated insula gray matter volume, morphometry, white matter structural connectivity, and resting state functional connectivity in 75 participants with alcohol use disorder (females = 27) and 75 age-matched healthy control participants (females = 39). Results indicated structural differences mostly in the anterior regions, while functional connectivity differences were observed in both the anterior and posterior insula in those with alcohol use disorder. Differing connectivity was observed with frontal, parietal, occipital, cingulate, cerebellar, and temporal brain regions. While these results align with prior studies showing differences primarily in anterior insular regions, they also contribute to the existing literature suggesting differences in anterior insular connectivity with brain regions shown to be engaged during higher cognitive and emotional tasks.

Correlations Between the DMN and the Smoking Cessation Outcome of a Real-Time fMRI Neurofeedback Supported Exploratory Therapy Approach: Descriptive Statistics on Tobacco-Dependent Patients

The aim of this study was to explore the potential of default mode network (DMN) functional connectivity for predicting the success of smoking cessation in patients with tobacco dependence in the context of a real-time function al MRI (RT-fMRI) neurofeedback (NF) supported therapy.Fifty-four tobacco-dependent patients underwent three RT-fMRI-NF sessions including resting-state functional connectivity (RSFC) runs over a period of 4 weeks during professionally assisted smoking cessation. Patients were randomized into two groups that performed either active NF of an addiction-related brain region or sham NF. After preprocessing, the RSFC baseline data were statistically evaluated using seed-based ROI (SBA) approaches taking into account the smoking status of patients after 3 months (abstinence/relapse).The results of the real study group showed a widespread functional connectivity in the relapse subgroup (n = 10) exceeding the DMN template and mainly low correlations and anticorrelations in the within-seed analysis. In contrast, the connectivity pattern of the abstinence subgroup (n = 8) primarily contained the core DMN in the seed-to-whole-brain analysis and a left lateralized correlation pattern in the within-seed analysis. Calculated Multi-Subject Dictionary Learning (MSDL) matrices showed anticorrelations between DMN regions and salience regions in the abstinence group. Concerning the sham group, results of the relapse subgroup (n = 4) and the abstinence subgroup (n = 6) showed similar trends only in the within-seed analysis.In the setting of a RT-fMRI-NF-assisted therapy, a widespread intrinsic DMN connectivity and a low negative coupling between the DMN and the salience network (SN) in patients with tobacco dependency during early withdrawal may be useful as an early indicator of later therapy nonresponse.

Identifying Alcohol Use Disorder With Resting State Functional Magnetic Resonance Imaging Data: A Comparison Among Machine Learning Classifiers

Alcohol use disorder (AUD) is a burden to society creating social and health problems. Detection of AUD and its effects on the brain are difficult to assess. This problem is enhanced by the comorbid use of other substances such as nicotine that has been present in previous studies. Recent machine learning algorithms have raised the attention of researchers as a useful tool in studying and detecting AUD. This work uses AUD and controls samples free of any other substance use to assess the performance of a set of commonly used machine learning classifiers detecting AUD from resting state functional network connectivity (rsFNC) derived from independent component analysis. The cohort used included 51 alcohol dependent subjects and 51 control subjects. Despite alcohol, none of the 102 subjects reported use of nicotine, cannabis or any other dependence or habit formation substance. Classification features consisted of whole brain rsFNC estimates undergoing a feature selection process using a random forest approach. Features were then fed to 10 different machine learning classifiers to be evaluated based on their classification performance. A neural network classifier showed the highest performance with an area under the curve (AUC) of 0.79. Other good performers with similar AUC scores were logistic regression, nearest neighbor, and support vector machine classifiers. The worst results were obtained with Gaussian process and quadratic discriminant analysis. The feature selection outcome pointed to functional connections between visual, sensorimotor, executive control, reward, and salience networks as the most relevant for classification. We conclude that AUD can be identified using machine learning classifiers in the absence of nicotine comorbidity.

Brain Network Allostasis after Chronic Alcohol Drinking Is Characterized by Functional Dedifferentiation and Narrowing

Alcohol use disorder (AUD) causes complex alterations in the brain that are poorly understood. The heterogeneity of drinking patterns and the high incidence of comorbid factors compromise mechanistic investigations in AUD patients. Here we used male Marchigian Sardinian alcohol-preferring (msP) rats, a well established animal model of chronic alcohol drinking, and a combination of longitudinal resting-state fMRI and manganese-enhanced MRI to provide objective measurements of brain connectivity and activity, respectively. We found that 1 month of chronic alcohol drinking changed the correlation between resting-state networks. The change was not homogeneous, resulting in the reorganization of pairwise interactions and a shift in the equilibrium of functional connections. We identified two fundamentally different forms of network reorganization. First is functional dedifferentiation, which is defined as a regional increase in neuronal activity and overall correlation, with a concomitant decrease in preferential connectivity between specific networks. Through this mechanism, occipital cortical areas lost their specific interaction with sensory-insular cortex, striatal, and sensorimotor networks. Second is functional narrowing, which is defined as an increase in neuronal activity and preferential connectivity between specific brain networks. Functional narrowing strengthened the interaction between striatal and prefrontocortical networks, involving the anterior insular, cingulate, orbitofrontal, prelimbic, and infralimbic cortices. Importantly, these two types of alterations persisted after alcohol discontinuation, suggesting that dedifferentiation and functional narrowing rendered persistent network states. Our results support the idea that chronic alcohol drinking, albeit at moderate intoxicating levels, induces an allostatic change in the brain functional connectivity that propagates into early abstinence.SIGNIFICANCE STATEMENT Excessive consumption of alcohol is positioned among the top five risk factors for disease and disability. Despite this priority, the transformations that the nervous system undergoes from an alcohol-naive state to a pathologic alcohol drinking are not well understood. In our study, we use an animal model with proven translational validity to study this transformation longitudinally. The results show that shortly after chronic alcohol consumption there is an increase in redundant activity shared by brain structures, and the specific communication shrinks to a set of pathways. This functional dedifferentiation and narrowing are not reversed immediately after alcohol withdrawal but persist during early abstinence. We causally link chronic alcohol drinking with an early and abstinence-persistent retuning of the functional equilibrium of the brain.

Severity of alcohol use disorder influences sex differences in sleep, mood and brain functional connectivity impairments

Growing evidence suggests greater vulnerability of women than men to the adverse effects of alcohol on mood and sleep. However, the underlying neurobiological mechanisms are still poorly understood.

Here we examined sex difference in resting state functional connectivity in alcohol use disorder using a whole-brain data driven approach and tested for relationships with mood and self-reported sleep. To examine whether sex effects vary by severity of alcohol use disorder, we studied two cohorts: non-treatment seeking n = 141 participants with alcohol use disorder (low severity; 58 females) from the Human Connectome project, and recently detoxified n = 102 treatment seeking participants with alcohol use disorder (high severity; 34 females) at the National Institute on Alcohol Abuse and Alcoholism.

For both cohorts, participants with alcohol use disorder had greater sleep and mood problems than HC, whereas sex by alcohol use effect varied by severity. Non-treatment seeking females with alcohol use disorder showed significant greater impairments in sleep but not mood compared to non-treatment seeking males with alcohol use disorder, whereas treatment-seeking females with alcohol use disorder reported greater negative mood but not sleep than treatment-seeking males with alcohol use disorder. Greater sleep problems in non-treatment seeking females with alcohol use disorder were associated with lower cerebello-parahippocampal functional connectivity, while greater mood problems in treatment-seeking females with alcohol use disorder were associated with lower fronto-occipital functional connectivity during rest.

The current study suggests that changes in resting state functional connectivity may account for sleep and mood impairments in females with alcohol use disorder. The effect of severity on sex differences might reflect neuroadaptive processes with progression of alcohol use disorder and needs to be tested with longitudinal data in the future.

Altered striatal-opercular intrinsic connectivity reflects decreased aversion to losses in alcohol use disorder

The persistence of addictive behaviours despite their adverse consequences highlights decreased punishment sensitivity as a facet of decision-making impairments in Alcohol Use Disorder (AUD). This attitude departs from the typical loss aversion (LA) pattern, i.e. the stronger sensitivity to negative than positive outcomes, previously associated with striatal and limbic-somatosensory responsiveness in healthy individuals. Consistent evidence highlights decreased LA as a marker of disease severity in AUD, but its neural bases remain largely unexplored. AUD-specific modulations of frontolateral activity by LA were previously related to the higher executive demands of anticipating losses than gains, but the relationship between LA and executive/working-memory performance in AUD is debated. Building on previous evidence of overlapping neural bases of LA during decision-making and at rest, we investigated a possible neural signature of altered LA in AUDs, and its connections with executive skills, in terms of complementary facets of resting-state functioning. In patients, smaller LA than controls, unrelated to executive performance, reflected reduced connectivity within striatal and medial temporal networks, and altered connectivity from these regions to the insular-opercular cortex. AUD-specific loss-related modulations of intrinsic connectivity thus involved structures previously associated both with drug-seeking and with coding the trade-off between appetitive and aversive motivational drives. These findings fit the hypothesis that altered striatal coding of choice-related incentive value, and interoceptive responsiveness to prospective outcomes, enhance neural sensitivity to drug-related stimuli in addictions. LA and its neural bases might prove useful markers of AUD severity and effectiveness of rehabilitation strategies targeting the salience of negative choice outcomes.

Sex differences in brain regional homogeneity during acute abstinence in cocaine use disorder

There are significant sex differences in the clinical characteristics of cocaine use disorder (CUD). As this is a brain disorder that involves changes in functional connectivity, we investigated the existence of sex differences among people with CUD and controls. We used a data‐driven method comparing males (n = 20, CK‐M) and females with CUD (n = 20, CK‐F) and healthy controls (20 males, HC‐M and 20 females, HC‐F). The participants undertook a resting‐state functional magnetic resonance imaging exam. Regional homogeneity (ReHo) was performed to identify group and sex differences. Persons with CUD of both sexes presented lower ReHo parameters than controls, especially within the parietal lobule. Males with CUD showed higher ReHo than females in three right‐side brain areas: postcentral gyrus, putamen and fusiform gyrus. It was found that abstinence symptoms severity was associated with lower ReHo values in the right postcentral gyrus and the right fusiform gyrus. Participants with CUD exhibited altered ReHo parameters compared to controls, similar to what is found in ageing‐related disorders. Our data also indicate that cocaine has sex‐specific effects on brain functioning when analysing ReHo.

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.

From a systems view to spotting a hidden island: A narrative review implicating insula function in alcoholism

Excessive use of alcohol promotes the development of alcohol addiction, but the understanding of how alcohol-induced brain alterations lead to addiction remains limited. To further this understanding, we adopted an unbiased discovery strategy based on the principles of systems medicine. We used functional magnetic resonance imaging data from patients and animal models of alcohol addiction-like behaviors, and developed mathematical models of the 'relapse-prone' network states to identify brain sites and functional networks that can be selectively targeted by therapeutic interventions. Our systems level, non-local, and largely unbiased analyses converged on a few well-defined brain regions, with the insula emerging as one of the most consistent finding across studies. In proof-of-concept experiments we were able to demonstrate that it is possible to guide network dynamics towards increased resilience in animals but an initial translation into a clinical trial targeting the insula failed. Here, in a narrative review, we summarize the key experiments, methodological developments and knowledge gained from this completed round of a discovery cycle moving from identification of 'relapse-prone' network states in humans and animals to target validation and intervention trial. Future concerted efforts are necessary to gain a deeper understanding of insula function a in a state-dependent, circuit-specific and cell population perspective, and to develop the means for insula-directed interventions, before therapeutic targeting of this structure may become possible.

Data-driven study on resting-state functional magnetic resonance imaging during early abstinence of alcohol dependence in male patients and its predictive value for relapse

BACKGROUND

Alcohol dependence is a mental disorder with a high relapse rate. However, specific neuroimaging biomarkers have not been determined for alcohol dependence and its relapse. We conducted data-driven research to investigate resting-state functional magnetic resonance imaging (rs-fMRI) during early abstinence from alcohol dependence and its potential ability to predict relapse.

METHODS

Participants included 68 alcohol-dependent patients and 68 healthy controls (HCs). The regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were compared between the alcohol dependence group and the HCs and between the relapse group and the nonrelapse group. The brain regions that presented significantly different ReHo and/or fALFF between the alcohol-dependent patients and HCs and/or between the relapsed and nonrelapsed patients were selected as the seeds to calculate the functional connectivities (FCs).

RESULTS

During a 6-month follow-up period, 52.24% of alcohol-dependent patients relapsed. A regression model for differentiating alcohol-dependent patients and HCs showed that reductions in ReHo in the left postcentral region, fALFF in the right fusiform region, and FC in the right fusiform region to the right middle cingulum were independently associated with alcohol dependence, with an area under the receiver operating characteristic curve (AUC) of 0.841. The baseline FC of the left precentral to the left cerebellum of the relapse group was significantly lower than that of the nonrelapse group. The AUC of this FC to predict relapse was 0.774.

CONCLUSIONS

Our findings contribute to advancing research on the neurobiological etiology and predictive biomarkers for relapse associated with alcohol dependence.

Mindfulness-Based Interventions for the Treatment of Aberrant Interoceptive Processing in Substance Use Disorders

Altered interoception, or the processing of bodily signals, has been argued to play a role in the development and maintenance of substance use disorders (SUD). Therefore, interoceptive interventions focusing on bodily awareness, such as mindfulness meditation, may improve treatment outcomes for individuals with SUD. Here we review: (1) subjective, behavioral and brain evidence for altered interoceptive processing in SUD, focusing on insular and anterior cingulate cortices (INS, ACC), key regions for interoceptive processing; (2) research highlighting links between mindfulness and brain function; and (3) extant brain research investigating mindfulness-based interventions in SUD. SUD tend to be characterized by heightened INS and ACC responses to drug cues but blunted interoceptive awareness and attenuated INS and ACC responses during tasks involving bodily attention and/or perturbations. In contrast, mindfulness interventions in healthy individuals are linked to enhanced INS and ACC responses and heightened interoceptive awareness. It is crucial for future research to identify: (1) whether mindfulness-based treatments are efficacious across substance classes; (2) what particular approaches and dosages show the largest effect sizes in enhancing INS and ACC function to non-drug stimuli and reducing responsivity to substance cues, thereby improving SUD treatment outcomes (reducing drug craving and relapse).

Sexual Differences in Internet Gaming Disorder (IGD): From Psychological Features to Neuroanatomical Networks

Internet gaming disorder (IGD) has been included in the 2013 Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a condition in need of further study, and gaming disorder was recognized by the World Health Organization as a mental disorder in the International Classification of Disease (ICD-11) of 2018. IGD has different characteristics in the two sexes and is more prevalent in males than females. However, even if the female gamer population is constantly growing, the majority of available studies analyzed only males, or the data were not analyzed by sex. To better elucidate sex differences in IGD, we selectively reviewed research publications that evaluated IGD separately for males and females collected in approximately one hundred publications over the past 20 years. The available data in this narrative review indicate that IGD is strongly dimorphic by sex for both its psychological features and the involvement of different brain areas. Impulsivity, low self-control, anxiety, emotion dysregulation, and depression are some of the psychological features associated with IGD that show a sex dimorphism. At the same time, IGD and its psychological alterations are strongly correlated to dimorphic functional characteristics in relevant brain areas, as evidenced by fMRI. More research is needed to better understand sex differences in IGD. Animal models could help to elucidate the neurological basis of this disorder.

The physiological basis underlying functional connectivity differences in older adults: A multi-modal analysis of resting-state fMRI

The purpose of this study was to determine if differences in functional connectivity strength (FCS) with age were confounded by vascular parameters including resting cerebral blood flow (CBF₀), cerebrovascular reactivity (CVR), and BOLD-CBF coupling. Neuroimaging data were collected from 13 younger adults (24 ± 2 years) and 14 older adults (71 ± 4 years). A dual-echo resting state pseudo-continuous arterial spin labeling sequence was performed, as well as a BOLD breath-hold protocol. A group independent component analysis was used to identify networks, which were amalgamated into a region of interest (ROI). Within the ROI, FC strength (FCS) was computed for all voxels and compared across the groups. CBF₀, CVR and BOLD-CBF coupling were examined within voxels where FCS was different between young and older adults. FCS was greater in old compared to young (P = 0.001). When the effect of CBF₀, CVR and BOLD-CBF coupling on FCS was examined, BOLD-CBF coupling had a significant effect (P = 0.003) and group differences in FCS were not present once all vascular parameters were considered in the statistical model (P = 0.07). These findings indicate that future studies of FCS should consider vascular physiological markers in order to improve our understanding of aging processes on brain connectivity.

The effects of nalmefene on the impulsive and reflective system in alcohol use disorder: A resting-state fMRI study

RATIONALE

Central aspects of alcohol use disorder (AUD) are the irresistible desire for alcohol and impaired control over its intake. According to the triadic neurocognitive model of addiction, this arises from aberrant functioning of different neural and cognitive systems: an impulsive system, a reflective system, and the abnormal dynamics between both systems based on an insular-dependent system.

OBJECTIVES

In this study, we examined the effects of a single dose of nalmefene on resting-state functional connectivity (rsFC) patterns within and between these addiction-related neural systems in AUD.

METHODS

Non-treatment seeking participants with AUD (N = 17; 19-66 years, 6 female) took part in a randomized, placebo-controlled, double-blind, crossover study and received either a single dose of 18 mg nalmefene or a placebo. Using seed-based correlation analyses on resting-state functional magnetic resonance imaging data, we examined the effects of nalmefene on key nodes related to the (1) impulsive system; (2) reflective system; (3) salience network; and (4) default mode network.

RESULTS

Under nalmefene, participants showed reduced rsFC between components of the impulsive system (Nucleus accumbens-putamen/pallidum/insula). Reduced rsFC was found between elements of the reflective system and impulsive system (orbitofrontal cortex-insula/putamen/pallidum), salience network (orbitofrontal cortex-insula/inferior frontal gyrus), and default mode network (lateral prefrontal cortex-precuneus/cuneus). Components of the salience network showed both increased (anterior cingulate cortex) and decreased (insular cortex) rsFC to elements of the reflective system.

CONCLUSION

A single dose of nalmefene impacts rsFC and alters the interaction between key nodes of addiction-related neural systems in non-treatment seeking participants with AUD. Nalmefene may normalize rsFC patterns by weakening the impulsive system while strengthening the reflective system.

TRIAL REGISTRATION

clinicaltrials.gov: NCT02372318.

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.

Increased network centrality of the anterior insula in early abstinence from alcohol

Abnormal resting‐state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph‐theoretical analyses, enabling improved resolution and fine‐grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large‐scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region‐specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular–supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.

Association between Changes in Cortical Thickness and Functional Connectivity in Male Patients with Alcohol-dependence

Many studies have reported structural or functional brain changes in patients with alcohol-dependence (ADPs). However, there has been an insufficient number of studies that were able to identify functional changes along with structural abnormalities in ADPs. Since neuronal cell death can lead to abnormal brain function, a multimodal approach combined with structural and functional studies is necessary to understand definitive neural mechanisms. Here, we explored regional difference in cortical thickness and their impact on functional connection along with clinical relevance. Fifteen male ADPs who have been diagnosed by the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) underwent high-resolution T1 and resting-state functional magnetic resonance imaging (MRI) scans together with 15 male healthy controls (HCs). The acquired MRI data were post-processed using the Computational Anatomy Toolbox (CAT 12) and CONN-fMRI functional connectivity (FC) toolbox with Statistical Parametric Mapping (SPM 12). When compared with male HCs, the male ADPs showed significantly reduced cortical thickness in the left postcentral gyrus (PoCG), an area responsible for altered resting-state FC patterns in male ADPs. Statistically higher FCs in PoCG-cerebellum (Cb) and lower FCs in PoCG-supplementary motor area (SMA) were observed in male ADPs. In particular, the FCs with PoCG-Cb positively correlated with alcohol use disorders identification test (AUDIT) scores in male ADPs. Our findings suggest that the association of brain structural abnormalities and FC changes could be a characteristic difference in male ADPs. These findings can be useful in understanding the neural mechanisms associated with anatomical, functional and clinical features of individuals with alcoholism.

Alcohol use and interoception - A narrative review

Interoception, defined as the ability to perceive and interpret body signals, may play an important role in alcohol use disorder (AUD). Earlier studies suggested an association between interoception impairment and known risk factors for AUD (e.g., alexithymia, emotion dysregulation, impulsivity, pain). Neurobiological studies show that the neurotoxicity of alcohol affects various elements of the interoceptive system (especially the insula) at structural and functional levels, with differential short/long term impacts. Conversely, primary interoceptive impairments may promote alcohol consumption and foster the evolution towards addiction. Despite convincing evidence demonstrating that interoception impairment may be an important contributor to the development and course of AUD, only a few studies directly evaluated interoceptive abilities in AUD. The research shows that interoceptive accuracy, the objective component of interoception, is lower in AUD individuals, and is correlated with craving and emotion dysregulation. Interoceptive sensibility is in turn higher in AUD individuals compared to healthy controls. Moreover, there is evidence that therapy focused on improving the ability to sense signals from the body in addiction treatment is effective. However, important methodological limitations in interoceptive measures persist, and it is therefore necessary to further investigate the associations between interoception and AUD.

Exploration of the influence of body mass index on intra-network resting-state connectivity in chronic cigarette smokers

BACKGROUND

Obesity and cigarette smoking are two leading preventable causes of death. Previous research suggests that comorbid smoking and obesity likely share neurobehavioral underpinnings; however, the influence of body mass index (BMI) on resting-state functional connectivity (rsFC) in smokers remains unknown. In this study, we explore how BMI affects rsFC and associations between rsFC and smoking-related behavior.

METHODS

Treatment-seeking cigarette smokers (N = 87; 54 % men) completed a BOLD resting-state fMRI scan session. We grouped smokers into BMI groups (N = 23 with obesity, N = 33 with overweight, N = 31 lean) and used independent components analysis (ICA) to identify the resting state networks commonly associated with cigarette smoking: salience network (SN), right and left executive control networks (ECN) and default mode network (DMN). Average rsFC values were extracted (p < 0.001, k = 100) to determine group differences in rsFC and relationship to self-reported smoking and dependence.

RESULTS

Analyses revealed a significant relationship between BMI and connectivity in the SN and a significant quadratic effect of BMI on DMN connectivity. Heavier smoking was related to greater rsFC in the SN among lean and obese groups but reduced rsFC in the overweight group.

CONCLUSIONS

Findings build on research suggesting an influence of BMI on the neurobiology of smokers. In particular, dysfunction of SN-DMN-ECN circuitry in smokers with overweight may lead to a failure to modulate attention and behavior and subsequent difficulty quitting smoking. Future research is needed to elucidate the mechanism underlying the interaction of BMI and smoking and its impact on treatment.

Drinking reduction during cognitive behavioral therapy for alcohol use disorder is associated with a reduction in anterior insula-bed nucleus of the stria terminalis resting-state functional connectivity

BACKGROUND

Connectivity between the anterior insula (AI) and the bed nucleus of the stria terminalis (BNST) may play a role in negative emotions that drive compulsive drinking in patients with alcohol use disorder (AUD). We hypothesized that reductions in drinking during cognitive behavioral therapy (CBT), an effective treatment that teaches regulation (coping) skills for managing negative emotions during abstinence, would be associated with reductions in resting-state functional connectivity (RSFC) between the AI and the BNST.

METHODS

We included 18 patients with a Diagnostic and Statistical Manual of Mental Disorders, fifth edition diagnosis of AUD who were (1) seeking treatment and (2) drinking heavily at baseline. We measured RSFC as Pearson's correlation between the BNST and multiple regions of interest in the insula at baseline and after completion of 12 weeks of a single-arm clinical trial of outpatient CBT. We also assessed the number of heavy drinking days over the previous 28 days (NHDD) at both time points. We used 1-sample t-tests to evaluate AI-BNST RSFC at baseline, paired t-tests to evaluate changes in AI-BNST RSFC from pre-CBT to post-CBT, and linear regression to evaluate the relationship between changes in AI-BNST RSFC and NHDD.

RESULTS

We found a significant positive RSFC between the AI and the BNST at baseline (p = 0.0015). While there were no significant changes in AI-BNST RSFC from pre- to post-CBT at the group level (p = 0.42), we found that individual differences in reductions in AI-BNST RSFC from pre- to post-CBT were directly related to reductions in NHDD from pre- to post-CBT (r = 0.73, p = 0.0008).

CONCLUSIONS

These findings provide preliminary evidence that reduced AI-BNST RSFC may be a mechanism of drinking reduction in AUD and that AI-BNST RSFC may be a target for CBT and possibly other treatments.

Anterior cingulate cortex metabolites and white matter microstructure: a multimodal study of emergent alcohol use disorder

Multimodal imaging is increasingly used to address neuropathology associated with alcohol use disorder (AUD). Few studies have investigated relationships between metabolite concentrations and white matter (WM) integrity; currently, there are no such data in AUD. In this preliminary study, we used complementary neuroimaging techniques, magnetic resonance spectroscopy (MRS), and diffusion weighted imaging (DWI), to study AUD neurophysiology. We tested for relationships between metabolites in the dorsal anterior cingulate cortex (dACC) and adjacent WM microstructure in young adult AUD and control (CON) subjects. Sixteen AUD and fourteen CON underwent whole-brain DWI and MRS of the dACC. Outcomes were dACC metabolites, and diffusion tensor metrics of dACC-adjacent WM. Multiple linear regression terms included WM region, group, and region × group for prediction of dACC metabolites. dACC myo-inositol was positively correlated with axial diffusivity in the left anterior corona radiata (p < 0.0001) in CON but not AUD (group effect: p < 0.001; region × group: p < 0.001; Bonferroni-corrected). In the bilateral anterior corona radiata and right genu of the corpus callosum, glutamate was negatively related to mean diffusivity in AUD, but not CON subjects (all model terms: p < 0.05, uncorrected). In AUD subjects, dACC glutamate was negatively correlated with AUD symptom severity. This is likely the first integrative study of cortical metabolites and WM integrity in young individuals with AUD. Differential relationships between dACC metabolites and adjacent WM tract integrity in AUD could represent early consequences of hazardous drinking, and/or novel biomarkers of early-stage AUD. Additional studies are required to replicate these findings, and to determine the behavioral relevance of these results.

Combined nicotine and ethanol age-dependently alter neural and behavioral responses in male rats

Use of alcohol (EtOH) and nicotine (Nic) typically begins during adolescence. Smoking and drinking often occur together and lead to a higher consumption of alcohol. Although we have shown that Nic+EtOH is reinforcing in self-administration tests in adolescent male rats, whether Nic+EtOH affects other behaviors or neuronal activity in an age-dependent manner is unknown. To address this, adolescent and adult male rats were given intravenous injections of Nic (30 µg/kg)+EtOH (4 mg/kg) and evaluated for locomotor and anxiety-like behaviors. Regional neuronal activity, assessed by cFos mRNA expression, was measured and used to evaluate functional connectivity in limbic regions associated with anxiety and motivation. Nic+EtOH increased locomotor activity and was anxiolytic in adolescents, but not adults. The posterior ventral tegmental area (pVTA), a critical regulator of drug reward, was selectively activated by Nic+EtOH in adults, while activity in its target region, the NAc-shell, was decreased. Drug-induced alterations in functional connectivity were more extensive in adults than adolescents and may act to inhibit behavioral responses to Nic+EtOH that are seen in adolescence. Overall, our findings suggest that brief, low-dose exposure to Nic+EtOH produces marked, age-dependent changes in brain and behavior and that there may be an ongoing maturation of the pVTA during adolescence that allows increased sensitivity to Nic+EtOH's reinforcing, hyperlocomotor, and anxiolytic effects. Furthermore, this work provides a potential mechanism for high rates of co-use of nicotine and alcohol by teenagers: this drug combination is anxiolytic and recruits functional networks that are unique from protective, inhibitory networks recruited in the mature and adult brain.

Effects of moderate alcohol levels on default mode network connectivity in heavy drinkers

BACKGROUND

It is well established that even moderate levels of alcohol affect cognitive functions such as memory, self-related information processing, and response inhibition. Nevertheless, the neural mechanisms underlying these alcohol-induced changes are still unclear, especially on the network level. The default mode network (DMN) plays an important role in memory and self-initiated mental activities; hence, studying functional interactions of the DMN may provide new insights into the neural mechanisms underlying alcohol-related changes.

METHODS

We investigated resting-state functional connectivity (rsFC) of the DMN in a cohort of 37 heavy drinkers at a breath alcohol concentration of 0.8 g/kg. Alcohol and saline were infused in a single-blind crossover design.

RESULTS

Intranetwork connectivity analyses revealed that participants showed significantly decreased rsFC of the right hippocampus and right middle temporal gyrus during acute alcohol exposure. Moreover, follow-up analyses revealed that these rsFC decreases were more pronounced in participants who reported stronger craving for alcohol. Exploratory internetwork connectivity analyses of the DMN with other resting-state networks showed no significant alcohol-induced changes, but suffered from low statistical power.

CONCLUSIONS

Our results indicate that acute alcohol exposure affects rsFC within the DMN. Functionally, this finding may be associated with impairments in memory encoding and self-referential processes commonly observed during alcohol intoxication. Future resting-state functional magnetic resonance imaging studies might therefore also investigate memory function and test whether DMN-related connectivity changes are associated with alcohol-induced impairments or craving.

Meta-analysis of grey matter changes and their behavioral characterization in patients with alcohol use disorder

Alcohol Use Disorder (AUD) is associated with reductions in grey matter (GM) volume which can lead to changes in numerous brain functions. The results of previous studies on altered GM in AUD differ considerably in the regions identified. Three meta-analyses carried out between 2014 and 2017 yielded different results. The present study includes the considerable amount of newer research and delivers a state-of-the art meta-analysis in line with recently published guidelines. Additionally, we behaviorally characterized affected regions using fMRI metadata and identified related brain networks by determining their meta-analytic connectivity patterns. Twenty-seven studies with 1,045 AUD patients and 1,054 healthy controls were included in the analysis and analyzed by means of Anatomical Likelihood Estimation (ALE). GM alterations were identified in eight clusters covering different parts of the cingulate and medial frontal gyri, paracentral lobes, left post- and precentral gyri, left anterior and right posterior insulae and left superior frontal gyrus. The behavioral characterization associated these regions with specific cognitive, emotional, somatosensory and motor functions. Moreover, the clusters represent nodes within behaviorally relevant brain networks. Our results suggest that GM reduction in AUD could disrupt network communication responsible for the neurocognitive impairments associated with high chronic alcohol consumption.

Adolescent alcohol use disrupts functional neurodevelopment in sensation seeking girls

Exogenous causes, such as alcohol use, and endogenous factors, such as temperament and sex, can modulate developmental trajectories of adolescent neurofunctional maturation. We examined how these factors affect sexual dimorphism in brain functional networks in youth drinking below diagnostic threshold for alcohol use disorder (AUD). Based on the 3-year, annually acquired, longitudinal resting-state functional magnetic resonance imaging (MRI) data of 526 adolescents (12-21 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) cohort, developmental trajectories of 23 intrinsic functional networks (IFNs) were analyzed for (1) sexual dimorphism in 259 participants who were no-to-low drinkers throughout this period; (2) sex-alcohol interactions in two age- and sex-matched NCANDA subgroups (N = 76 each), half no-to-low, and half moderate-to-heavy drinkers; and (3) moderating effects of gender-specific alcohol dose effects and a multifactorial impulsivity measure on IFN connectivity in all NCANDA participants. Results showed that sex differences in no-to-low drinkers diminished with age in the inferior-occipital network, yet girls had weaker within-network connectivity than boys in six other networks. Effects of adolescent alcohol use were more pronounced in girls than boys in three IFNs. In particular, girls showed greater within-network connectivity in two motor networks with more alcohol consumption, and these effects were mediated by sensation-seeking only in girls. Our results implied that drinking might attenuate the naturally diminishing sexual differences by disrupting the maturation of network efficiency more severely in girls. The sex-alcohol-dose effect might explain why women are at higher risk of alcohol-related health and psychosocial consequences than men.

Neural network involving medial orbitofrontal cortex and dorsal periaqueductal gray regulation in human alcohol abuse

Prompted by recent evidence of neural circuitry in rodent models, functional magnetic resonance imaging and functional connectivity analyses were conducted for a large adolescent population at two ages, together with alcohol abuse measures, to characterize a neural network that may underlie the onset of alcoholism. A network centered on the medial orbitofrontal cortex (mOFC), as well as including the dorsal periaqueductal gray (dPAG), central nucleus of the amygdala, and nucleus accumbens, was identified, consistent with the rodent models, with evidence of both inhibitory and excitatory coregulation by the mOFC over the dPAG. Furthermore, significant relationships were detected between raised baseline excitatory coregulation in this network and impulsivity measures, supporting a role for negative urgency in alcohol dependence.

When your brain looks older than expected: combined lifestyle risk and BrainAGE

Lifestyle may be one source of unexplained variance in the great interindividual variability of the brain in age-related structural differences. While physical and social activity may protect against structural decline, other lifestyle behaviors may be accelerating factors. We examined whether riskier lifestyle correlates with accelerated brain aging using the BrainAGE score in 622 older adults from the 1000BRAINS cohort. Lifestyle was measured using a combined lifestyle risk score, composed of risk (smoking, alcohol intake) and protective variables (social integration and physical activity). We estimated individual BrainAGE from T1-weighted MRI data indicating accelerated brain atrophy by higher values. Then, the effect of combined lifestyle risk and individual lifestyle variables was regressed against BrainAGE. One unit increase in combined lifestyle risk predicted 5.04 months of additional BrainAGE. This prediction was driven by smoking (0.6 additional months of BrainAGE per pack-year) and physical activity (0.55 less months in BrainAGE per metabolic equivalent). Stratification by sex revealed a stronger association between physical activity and BrainAGE in males than females. Overall, our observations may be helpful with regard to lifestyle-related tailored prevention measures that slow changes in brain structure in older adults.

Immunological Disturbances and Neuroimaging Findings in Major Depressive Disorder (MDD) and Alcohol Use Disorder (AUD) Comorbid Patients

Mood disorders and Major Depressive Disorder, in particular, appear to be some of the most common psychiatric disorders with a high rate of comorbidity most frequently of anxiety or substance abuse disorders (alcohol use disorder). In both cases - MDD and AUD, a number of immunological disturbances are observed, such as chronic mild inflammation response, increased level of cytokines, hypercortisolaemia, which lead to specific changes in brain neurotransmitter functions. Some of the contemporary brain imaging techniques are functional magnetic resonance imaging (fMRI) and magnetic spectroscopy which are most commonly used to assess the brain metabolism and functional connectivity changes such as altered responses to emotional stimuli in MDD or overactivation of ventromedial prefrontal areas during delayed and underactivation of dorsolateral prefrontal regions during impulsive reward decisions in AUD and dysfunction of gamma-aminobutyric acid (GABA) and/or glutamate neurotransmitter systems, low NAA and myo-Inositol in both MDD and AUD.

A whole-brain modeling approach to identify individual and group variations in functional connectivity

Resting-state functional connectivity is an important and widely used measure of individual and group differences. Yet, extant statistical methods are limited to linking covariates with variations in functional connectivity across subjects, especially at the voxel-wise level of the whole brain. This paper introduces a modeling approach that regresses whole-brain functional connectivity on covariates. Our approach is a mesoscale approach that enables identification of brain subnetworks. These subnetworks are composite of spatially independent components discovered by a dimension reduction approach (such as whole-brain group ICA) and covariate-related projections determined by the covariate-assisted principal regression, a recently introduced covariance matrix regression method. We demonstrate the efficacy of this approach using a resting-state fMRI dataset of a medium-sized cohort of subjects obtained from the Human Connectome Project. The results suggest that the approach may improve statistical power in detecting interaction effects of gender and alcohol on whole-brain functional connectivity, and in identifying the brain areas contributing significantly to the covariate-related differences in functional connectivity.

Delta resting-state functional connectivity in the cognitive control network as a prognostic factor for maintaining abstinence: An eLORETA preliminary study

BACKGROUND

Cortical regions that support cognitive control are increasingly well recognized, but the functional mechanisms that promote such control over emotional and behavioral hyperreactivity to alcohol in recently abstinent alcohol-dependent patients are still insufficiently understood. This study aimed to identify neurophysiological biomarkers of maintaining abstinence in alcohol-dependent individuals after alcohol treatment by investigating the resting-state EEG-based functional connectivity in the cognitive control network (CCN).

METHODS

Lagged phase synchronization between CCN areas by means of eLORETA as well as the Barratt Impulsiveness Scale (BIS-11) and Beck Depression Inventory (BDI) were assessed in abstinent alcohol-dependent patients recruited from treatment centers. A preliminary prospective study design was used to classify participants into those who did and did not maintain abstinence during a follow-up period (median 12 months) after discharge from residential treatment.

RESULTS

Alcohol-dependent individuals, who maintained abstinence (N = 18), showed significantly increased lagged phase synchronization between the left dorsolateral prefrontal cortex (DLPFC) and the left posterior parietal cortex (IPL) as well as between the right anterior insula cortex/frontal operculum (IA/FO) and the right inferior frontal junction (IFJ) in the delta band compared to those who later relapsed (N = 16). Regression analysis showed that the increased left frontoparietal delta connectivity in the early period of abstinence significantly predicted maintaining abstinence over the ensuing 12 months. Furthermore, right frontoinsular delta connectivity correlated negatively with impulsivity and depression measures.

CONCLUSIONS

These results suggest that the increased delta resting-state functional connectivity in the CCN may be a promising neurophysiological predictor of maintaining abstinence in individuals with alcohol dependence.

Resting-State Functional Magnetic Resonance Imaging Reveals Overactivation of the Habitual Control Brain System in Tobacco Dependence

INTRODUCTION

We studied the regulatory mechanism of the habitual brain network in tobacco dependence to provide a theoretical basis for the regulation and cessation of tobacco dependence.

METHODS

We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the Fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity (FC) of the habitual brain network in tobacco-dependent subjects and to evaluate the relationship between the FC level and tobacco selection preference behavior. In total, 29 male tobacco-dependent participants and 28 male nonsmoking participants were recruited. rs-fMRI was used to collect blood oxygen level-dependent signals of the participants in the resting and awake states. After rs-fMRI, all subjects completed cigarette/coin selection tasks (task 1 and task 2).

RESULTS

Compared with the control group, the tobacco dependence group showed increased fractional amplitude values of fALFF in the left posterior cingulate cortex and right parahippocampus. FC in the tobacco-dependent group was increased in the right inferior temporal gyrus, left middle frontal gyrus, left cingulated gyrus, and bilateral superior frontal gyrus, compared with that in the control group. Moreover, the preference selection behavior was associated with the enhancement of FC about parts of the brain regions in the habitual brain network of the tobacco-dependent participants. Thus, habitual network activity was significantly enhanced in tobacco-dependent participants in the resting state. Moreover, a positive correlation was found between the cigarette selection preference of the smokers and certain brain regions related to the habitual network.

DISCUSSION

This suggests that increased activity of the habitual brain network may be essential in the development of tobacco-dependent behavior.

Evaluating the resource allocation index as a potential fMRI-based biomarker for substance use disorder

BACKGROUND

There is a lack of neuroscience-based biomarkers for the diagnosis, treatment and monitoring of individuals with substance use disorders (SUD). The resource allocation index (RAI), a measure of the interrelationship between salience, executive control and default-mode brain networks (SN, ECN, and DMN), has been proposed as one such biomarker. However, the RAI has yet to be extensively tested in SUD samples.

METHODS

The present analysis compared RAI scores between individuals with stimulant and/or opioid use disorders (SUD; n = 139, abstinent 4-365 days) and healthy controls (HC; n = 56) who had completed resting-state functional magnetic resonance imaging (fMRI) scans within the context of the Tulsa 1000 cohort. First, we used independent component analysis (ICA) to identify the SN, ECN, and DMN and extract their time series data. Second, we used multiple permutations of automatically identified networks to compute RAI as reported in the fMRI literature.

RESULTS

First, the RAI as a metric depended substantially on the approach that was used to define the network components. Second, regardless of the selection of networks, after controlling for multiple testing there was no difference in RAI scores between SUD and HC. Third, the RAI was not associated with any substance use-related self-report measures.

CONCLUSION

Taken together, these findings do not provide evidence that RAI can be used as an fMRI-derived biomarker for the severity or diagnosis of individuals with SUD.

Deep Parametric Mixtures for Modeling the Functional Connectome

Functional connectivity between brain regions is often estimated by correlating brain activity measured by resting-state fMRI in those regions. The impact of factors (e.g, disorder or substance use) are then modeled by their effects on these correlation matrices in individuals. A crucial step in better understanding their effects on brain function could lie in estimating connectomes, which encode the correlation matrices across subjects. Connectomes are mostly estimated by creating a single average for a specific cohort, which works well for binary factors (such as sex) but is unsuited for continuous ones, such as alcohol consumption. Alternative approaches based on regression methods usually model each pair of regions separately, which generally produces incoherent connectomes as correlations across multiple regions contradict each other. In this work, we address these issues by introducing a deep learning model that predicts connectomes based on factor values. The predictions are defined on a simplex spanned across correlation matrices, whose convex combination guarantees that the deep learning model generates well-formed connectomes. We present an efficient method for creating these simplexes and improve the accuracy of the entire analysis by defining loss functions based on robust norms. We show that our deep learning approach is able to produce accurate models on challenging synthetic data. Furthermore, we apply the approach to the resting-state fMRI scans of 281 subjects to study the effect of sex, alcohol, and HIV on brain function.

Leveraging Neural Networks in Preclinical Alcohol Research

Alcohol use disorder is a pervasive healthcare issue with significant socioeconomic consequences. There is a plethora of neural imaging techniques available at the clinical and preclinical level, including magnetic resonance imaging and three-dimensional (3D) tissue imaging techniques. Network-based approaches can be applied to imaging data to create neural networks that model the functional and structural connectivity of the brain. These networks can be used to changes to brain-wide neural signaling caused by brain states associated with alcohol use. Neural networks can be further used to identify key brain regions or neural "hubs" involved in alcohol drinking. Here, we briefly review the current imaging and neurocircuit manipulation methods. Then, we discuss clinical and preclinical studies using network-based approaches related to substance use disorders and alcohol drinking. Finally, we discuss how preclinical 3D imaging in combination with network approaches can be applied alone and in combination with other approaches to better understand alcohol drinking.

The disengaging brain: Dynamic transitions from cognitive engagement and alcoholism risk

Human functional brain connectivity is usually measured either at "rest" or during cognitive tasks, ignoring life's moments of mental transition. We propose a different approach to understanding brain network transitions. We applied a novel independent component analysis of functional connectivity during motor inhibition (stop signal task) and during the continuous transition to an immediately ensuing rest. A functional network reconfiguration process emerged that: (i) was most prominent in those without familial alcoholism risk, (ii) encompassed brain areas engaged by the task, yet (iii) appeared only transiently after task cessation. The pattern was not present in a pre-task rest scan or in the remaining minutes of post-task rest. Finally, this transient network reconfiguration related to a key behavioral trait of addiction risk: reward delay discounting. These novel findings illustrate how dynamic brain functional reconfiguration during normally unstudied periods of cognitive transition might reflect addiction vulnerability, and potentially other forms of brain dysfunction.

Determining the number of states in dynamic functional connectivity using cluster validity indexes

BACKGROUND

Clustering analysis is employed in brain dynamic functional connectivity (dFC) to cluster the data into a set of dynamic states. These states correspond to different patterns of functional connectivity that iterate through time. Although several cluster validity index (CVI) methods to determine the best clustering partition exists, the appropriateness of methods to apply in the case of dynamic connectivity analysis has not been determined.

NEW METHOD

Currently employed indexes do not provide a crisp answer on what is the best number of clusters. In addition, there is a lack of CVI testing in the context of dFC data. This work tests a comprehensive set of twenty four cluster validity indexes applied to addiction data and suggest the best ones for clustering dynamic functional connectivity.

RESULTS

Out of the twenty four considered CVIs, Davies-Bouldin and Ray-Turi were the most suitable methods to find the number of clusters in both simulation and real data. The solution for these two CVIs is to find a local minimum critical point, which can be automated using computational algorithms.

COMPARISON WITH EXISTING METHODS

Elbow-Criterion, Silhouette and GAP-Statistic methods have been widely used in dFC studies. These methods are included among the tested CVIs where the performances of all twenty four CVIs are compared.

CONCLUSIONS

Davies-Bouldin and Ray-Turi CVIs showed better performance among a group of twenty four CVIs in determining the number of clusters to use in dFC analysis.

Altered habenula resting state functional connectivity in deprived veteran tobacco smokers: A pilot study

This study aimed to examine habenular resting state functional connectivity (RSFC) abnormalities in tobacco-smoking veterans. The authors explored RSFC in sated smokers (n = 3D 18), overnight deprived smokers (n = 3D 13), and nonsmoker controls (n = 3D 26). Seed-to-voxel analysis was used to explore RSFC in the habenula. Compared to sated smokers, deprived smokers demonstrated higher RSFC between the right habenula and two clusters of voxels: one in the right fusiform gyrus, and one in the left lingual gyrus. To study nicotine withdrawal, the authors used the Shiffman-Jarvik Withdrawal Questionnaire (SJWQ) score as a regressor and found higher RSFC between the right habenula and the left frontal pole in deprived compared to sated smokers. Right habenula RSFC distinguished between sated and deprived smokers and differentiated between sated and deprived smokers when using SJWQ as a regressor, suggesting a habenular role in tobacco withdrawal.