Prefrontal and limbic resting state brain network functional connectivity differs between nicotine-dependent smokers and non-smoking controls

Altered intrinsic neural timescales and neurotransmitter activity in males with tobacco use disorder

Previous researches of tobacco use disorder (TUD) has overlooked the hierarchy of cortical functions and single modality design separated the relationship between macroscopic neuroimaging aberrance and microscopic molecular basis. At present, intrinsic timescale gradient of TUD and its molecular features are not fully understood. Our study recruited 146 male subjects, including 44 heavy smokers, 50 light smokers and 52 non-smokers, then obtained their rs-fMRI data and clinical scales related to smoking. Intrinsic neural timescale (INT) method was performed to describe how long neural information was stored in a brain region by calculating the autocorrelation function (ACF) of each voxel to examine the difference in the ability of information integration among the three groups. Then, correlation analyses were conducted to explore the relationship between INT abnormalities and clinical scales of smokers. Finally, cross-modal JuSpace toolbox was used to investigate the association between INT aberrance and the expression of specific receptor/transporters. Compared to healthy controls, TUD subjects displayed decreased INT in control network (CN), default mode network (DMN), sensorimotor areas and visual cortex, and such trend of decreasing INT was more pronounced in heavy smokers. Moreover, various neurotransmitters (including dopaminergic, acetylcholine and μ-opioid receptors) were involved in the molecular mechanism of timescale decreasing and differed in heavy and light smokers. These findings supplied novel insights into the brain functional aberrance in TUD from an intrinsic neural dynamic perspective and confirm INT was a potential neurobiological marker. And also established the connection between macroscopic imaging aberrance and microscopic molecular changes in TUD.

Multimodal 7T imaging reveals enhanced functional coupling between salience and frontoparietal networks in young adult tobacco cigarette smokers

Tobacco cigarette smoking is associated with disrupted brain network dynamics in resting brain networks including the Salience (SN) and Fronto parietal (FPN). Unified multimodal methods [Resting state connectivity analysis, Diffusion Tensor Imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and cortical thickness analysis] were employed to test the hypothesis that the impact of cigarette smoking on the balance among these networks is due to alterations in white matter connectivity, microstructural architecture, functional connectivity and cortical thickness (CT) and that these metrics define fundamental differences between people who smoke and nonsmokers. Multimodal analyses of previously collected 7 Tesla MRI data via the Human Connectome Project were performed on 22 people who smoke (average number of daily cigarettes was 10 ± 5) and 22 age- and sex-matched nonsmoking controls. First, functional connectivity analysis was used to examine SN-FPN-DMN interactions between people who smoke and nonsmokers. The anatomy of these networks was then assessed using DTI and CT analyses while microstructural architecture of WM was analyzed using the NODDI toolbox. Seed-based connectivity analysis revealed significantly enhanced within network [p = 0.001 FDR corrected] and between network functional coupling of the salience and R-frontoparietal networks in people who smoke [p = 0.004 FDR corrected]. The network connectivity was lateralized to the right hemisphere. Whole brain diffusion analysis revealed no significant differences between people who smoke and nonsmokers in Fractional Anisotropy, Mean diffusivity and in neurite orienting and density. There were also no significant differences in CT in the hubs of these networks. Our results demonstrate that tobacco cigarette smoking is associated with enhanced functional connectivity, but anatomy is largely intact in young adults. Whether this enhanced connectivity is pre-existing, transient or permanent is not known. The observed enhanced connectivity in resting state networks may contribute to the maintenance of smoking frequency.

Commonality and variance of resting-state networks in common marmoset brains

Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrix jacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases.

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.

The interaction effects of age, APOE and common environmental risk factors on human brain structure

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

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.

Functional Domains of Substance Use and their Implications to Trauma: A Systematic Review of Neuroimaging Studies

Substance use disorder (SUD) is a significant health problem, and trauma exposure is a known risk factor for the escalation of substance use. However, the shared neural mechanisms through which trauma is associated with substance use are still unknown. Therefore, we systematically review neuroimaging studies focusing on three domains that may contribute to the overlapping mechanisms of SUD and trauma-reward salience, negative emotionality, and inhibition. Using PRISMA guidelines, we identified 45 studies utilizing tasks measuring these domains in alcohol, tobacco, and cannabis use groups. Greater reward, lesser regulation of inhibitory processes, and mixed findings of negative emotionality processes in individuals who use substances versus controls were found. Specifically, greater orbitofrontal cortex, ventral tegmental area, striatum, amygdala, and hippocampal activation was found in response to reward-related tasks, and reduced activation was found in the inferior frontal gyrus and hippocampus in response to inhibition-related tasks. Importantly, no studies in trauma-exposed individuals met our review criteria. Future studies examining the role of trauma-related factors are needed, and more studies should explore inhibition- and negative-emotionality domains in individuals who use substances to uncover clinically significant alterations in these domains that place an individual at greater risk for developing a SUD.

Acupuncture modulates the functional connectivity among the subcortical nucleus and fronto-parietal network in adolescents with internet addiction

BACKGROUND

Internet addiction (IA), recognized as a behavioral addiction, is emerging as a global public health problem. Acupuncture has been demonstrated to be effective in alleviating IA; however, the mechanism is not yet clear. To fill this knowledge gap, our study aimed to investigate the modulatory effects of acupuncture on the functional interactions among the addiction-related networks in adolescents with IA.

METHODS

Thirty individuals with IA and thirty age- and sex-matched healthy control subjects (HCs) were recruited. Subjects with IA were given a 40-day acupuncture treatment, and resting-state functional magnetic resonance imaging (fMRI) data were collected before and after acupuncture sessions. HCs received no treatment and underwent one fMRI scan after enrollment. The intergroup differences in functional connectivity (FC) among the subcortical nucleus (SN) and fronto-parietal network (FPN) were compared between HCs and subjects with IA at baseline. Then, the intragroup FC differences between the pre- and post-treatment were analyzed in the IA group. A multiple linear regression model was further employed to fit the FC changes to symptom relief in the IA group.

RESULTS

In comparison to HCs, subjects with IA exhibited significantly heightened FC within and between the SN and FPN at baseline. After 40 days of acupuncture treatment, the FC within the FPN and between the SN and FPN were significantly decreased in individuals with IA. Symptom improvement in subjects with IA was well fitted by the decrease in FC between the left midbrain and ventral prefrontal cortex and between the left thalamus and ventral anterior prefrontal cortex.

CONCLUSION

These findings confirmed the modulatory effects of acupuncture on the aberrant functional interactions among the SN and FPN, which may partly reflect the neurophysiological mechanism of acupuncture for IA.

Genetic and environmental influence on resting state networks in young male and female adults: a cartographer mapping study

We propose a unique, minimal assumption, approach based on variance analyses (compared with standard approaches) to investigate genetic influence on individual differences on the functional connectivity of the brain using 65 monozygotic and 65 dizygotic healthy young adult twin pairs' low-frequency oscillation resting state functional Magnetic Resonance Imaging (fMRI) data from the Human Connectome Project. Overall, we found high number of genetically-influenced functional (GIF) connections involving posterior to posterior brain regions (occipital/temporal/parietal) implicated in low-level processes such as vision, perception, motion, categorization, dorsal/ventral stream visuospatial, and long-term memory processes, as well as high number across midline brain regions (cingulate) implicated in attentional processes, and emotional responses to pain. We found low number of GIF connections involving anterior to anterior/posterior brain regions (frontofrontal > frontoparietal, frontotemporal, frontooccipital) implicated in high-level processes such as working memory, reasoning, emotional judgment, language, and action planning. We found very low number of GIF connections involving subcortical/noncortical networks such as basal ganglia, thalamus, brainstem, and cerebellum. In terms of sex-specific individual differences, individual differences in males were more genetically influenced while individual differences in females were more environmentally influenced in terms of the interplay of interactions of Task positive networks (brain regions involved in various task-oriented processes and attending to and interacting with environment), extended Default Mode Network (a central brain hub for various processes such as internal monitoring, rumination, and evaluation of self and others), primary sensorimotor systems (vision, audition, somatosensory, and motor systems), and subcortical/noncortical networks. There were >8.5-19.1 times more GIF connections in males than females. These preliminary (young adult cohort-specific) findings suggest that individual differences in the resting state brain may be more genetically influenced in males and more environmentally influenced in females; furthermore, standard approaches may suggest that it is more substantially nonadditive genetics, rather than additive genetics, which contribute to the differences in sex-specific individual differences based on this young adult (male and female) specific cohort. Finally, considering the preliminary cohort-specific results, based on standard approaches, environmental influences on individual differences may be substantially greater than that of genetics, for either sex, frontally and brain-wide. [Correction added on 10 May 2023, after first online publication: added: functional Magnetic Resonance Imaging. Added: individual differences in, twice. Added statement between furthermore … based on standard approaches.].

Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies

Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling has been increasingly applied for assessing whole brain network topological organization, yet its reproducibility remains controversial. In this study, we acquired three repeated resting-state fMRI scans from 16 healthy controls during a strictly controlled in-laboratory study and examined the test-retest reliability of seven global and three nodal brain network metrics using different data processing and modeling strategies. Among the global network metrics, the characteristic path length exhibited the highest reliability, whereas the network small-worldness performed the poorest. Nodal efficiency was the most reliable nodal metric, whereas betweenness centrality showed the lowest reliability. Weighted global network metrics provided better reliability than binary metrics, and reliability from the AAL90 atlas outweighed those from the Power264 parcellation. Although global signal regression had no consistent effects on the reliability of global network metrics, it slightly impaired the reliability of nodal metrics. These findings provide important implications for the future utility of graph theoretical modeling in brain network analyses.

Sleep variability over a 2-week period is associated with restfulness and intrinsic limbic network connectivity in adolescents

STUDY OBJECTIVES

Sleep duration and intraindividual variability in sleep duration undergo substantial changes in adolescence and impact brain and behavioral functioning. Although experimental work has linked acute sleep deprivation to heightened limbic responding and reduced regulatory control, there is limited understanding of how variability in sleep patterns might interact with sleep duration to influence adolescent functioning. This is important for optimal balancing of length and consistency of sleep. Here, we investigated how objective indices of sleep duration and variability relate to stress, restfulness, and intrinsic limbic network functioning in adolescents.

METHODS

A sample of 101 adolescents ages 14-18 reported their stressors, after which they wore wrist actigraph watches to monitor their sleep and rated their restfulness every morning over a 2-week period. They also completed a resting-state fMRI scan.

RESULTS

Adolescents reporting more stress experienced shorter sleep duration and greater sleep variability over the 2-week period. Longer nightly sleep duration was linked to feeling more rested the next morning, but this effect was reduced in adolescents with high cumulative sleep variability. Sleep variability showed both linear and quadratic effects on limbic connectivity: adolescents with high sleep variability exhibited more connectivity within the limbic network and less connectivity between the limbic and frontoparietal networks than their peers, effects which became stronger once variability exceeded an hour.

CONCLUSIONS

Results suggest that cumulative sleep variability is related to stress and limbic network connectivity and shows interactive effects with sleep duration, highlighting the importance of balancing length and consistency of sleep for optimal functioning in adolescence.

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.

Evidence from an fMRI study that dessert-flavored e-cigarettes engage taste-related, but not smoking-related, brain circuitry for female daily smokers

Regulations limiting the sale of flavored e-cigarette products are controversial for their potential to interfere with e-cigarette use as a cessation aid in addition to curbing youth use. Limited research suggests that flavor might enhance the addictive potential of e-cigarettes; however, the acute effects of flavored aerosols on brain function among humans have not been assessed. The present study aimed to isolate and compare the neural substrates of flavored and unflavored e-cigarette aerosols on brain function among nine female daily smokers. Participants inhaled aerosolized e-liquid with 36 mg/mL of nicotine with and without a strawberry-vanilla flavor while undergoing functional magnetic resonance imaging. We used general linear modeling to compare whole-brain mean neural activation and seed-to-voxel task-based functional connectivity between the flavored and unflavored inhalation runs. Contrary to our hypothesis, the flavored aerosol was associated with weaker activation than the unflavored aerosol in the brain stem and bilateral parietal-temporal-occipital region of the cortex. Instead, the flavor engaged taste-related brain regions while suppressing activation of the neural circuits typically engaged during smoking and nicotine administration. Alternatively, functional connectivity between subcortical dopaminergic brain seeds and cortical brain regions involved in motivation and reward salience were stronger during the flavored compared to unflavored aerosol run. The findings suggest that fruity and dessert-flavored e-cigarettes may dampen the reward experience of aerosol inhalation for smokers who initiate e-cigarette use by inhibiting activation of dopaminergic brain circuits. These preliminary findings may have implications for understanding how regulations on flavored e-cigarettes might impact their use as cessation aids. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Structural and functional brain alterations in Cushing's disease: A narrative review

Neurocognitive and psychiatric symptoms are non-negligible in Cushing's disease and are accompanied by structural and functional alterations of the brain. In this review, we have summarized multimodal neuroimaging and neurophysiological studies to highlight the current and historical understandings of the structural and functional brain alterations in Cushing's disease. Specifically, structural studies showed atrophy of the gray matter, loss of white matter integrity, and demyelination in widespread brain regions. Functional imaging studies have identified three major functional brain connectome networks influenced by hypercortisolemia: the limbic network, the default mode network, and the executive control network. After endocrinological remission, atrophy of gray matter regions and the compromised functional network activities were partially reversible, and the widespread white matter integrity alterations cannot recover in years. In conclusion, Cushing's disease patients display structural and functional brain connectomic alterations, which provides insights into the neurocognitive and psychiatric symptoms observed in this disease.

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.

Acute morphine administration, morphine dependence, and naloxone-induced withdrawal syndrome affect the resting-state functional connectivity and local field potentials of the rat prefrontal cortex

Opiates are among the widely abused substances worldwide. Also, the clinical use of opioids can cause unwanted and potentially severe consequences such as developing tolerance and dependence. This study simultaneously measured the changes induced after morphine dependence and naloxone-induced withdrawal syndrome on the resting-state functional connectivity (rsFC) and local field potential (LFP) power in the prefrontal cortex of the rat. The obtained results revealed that acute morphine administration significantly increased the LFP power in all frequency bands, as well as the rsFC strength of the prefrontal cortex, and naloxone injection reversed this effect. In contrast, chronic morphine administration reduced neural activity and general correlation values in intrinsic signals, as well as the LFP power in all frequency bands. In morphine-dependent rats, after each morphine administration, the LFP power in all frequency bands and the rsFC strength of the prefrontal cortex were increased, and these effects were further enhanced after naloxone precipitated withdrawal syndrome. The present study concludes that general correlation merely reflects the field activity of the local cortices imaged.

Similarities and differences between internet gaming disorder and tobacco use disorder: A large-scale network study

Studies have shown that internet gaming disorder (IGD) has the potential to be a type of addiction; however, direct comparisons (similarities and differences) between IGD and traditional addictions remain scarce, especially at the neuroimaging level. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 92 individuals with IGD, 96 individuals with tobacco use disorders (TUDs) and 107 individuals who served as healthy controls (HCs). Independent component analysis (ICA) was performed to explore the similarities and differences among these three groups; Granger causality analysis (GCA) was further performed based on the ICA results to determine potential neural features underlying the differences and similarities among the groups. The ICA results indicated significant differences in the subcortical network and cerebellar network. GCA results found that significant differences in bilateral caudate among three groups, and the efferents of dorsal frontostriatal circuit showed significant differences in insula among three groups, whereas efferents of ventral frontostriatal circuit showed significant differences in the medial prefrontal cortex (mPFC). Two kinds of addiction showed differences in thalamus and frontostriatal circuits, and similar changes found in cerebellum and mPFC regions. It suggested that addiction disorders have psychopathology features, and the craving and reward dysfunctions may be the key reasons. Although both substance addiction and behaviour addiction showed craving dysfunction in cerebellum, however, the key reward dysfunction of substance addiction was found in subcortical regions, whereas behaviour addiction located in cortical regions.

Comparison of frontostriatal circuits in adolescent nicotine addiction and internet gaming disorder

BACKGROUND

Recently, there has been significantly increased participation in online gaming and other addictive behaviors particularly in adolescents. Tendencies to avoid social interaction and become more involved in technology-based activities pose the danger of creating unhealthy addictions. Thus, the presence of relatively immature cognitive control and high risk-taking properties makes adolescence a period of major changes leading to an increased rate of emotional disorders and addiction.

AIMS

The critical roles of frontostriatal circuits in addiction have become the primary focus associated with reward in the striatum and cognitive control in the PFC. Internet gaming disorder (IGD) and nicotine addiction are currently becoming more and more serious.

METHODS

In the light of neuroimaging, the similarity between brain mechanisms causing substance use disorder (SUD) and IGD have been described in previous literature.

RESULTS

In particular, two distinct brain systems affect the way we act accounting for uncharacteristic neural function in addiction: the affective system comprises of the striatum driven by emotional, reward-related, and internal stimuli, and a cognitive system consisting of the prefrontal cortex (PFC) supporting the ventral affective system's actions via inhibitory control.

DISCUSSION AND CONCLUSION

Therefore, as a novel concept, we focused on the implication of frontostriatal circuits in nicotine addiction and IGD by reviewing the main findings from our studies compared to those of others. We hope that all of these neuroimaging findings can lead to effective intervention and treatment for addiction especially during this critical period.

Cannabis Use and Neuroadaptation: A Call for Δ 9 -Tetrahydrocannabinol Challenge Studies

Currently, the assessment of the neurobehavioral consequences of repeated cannabis use is restricted to studies in which brain function of chronic cannabis users is compared to that of non-cannabis using controls. The assumption of such studies is that changes in brain function of chronic users are caused by repeated and prolonged exposure to acute cannabis intoxication. However, differences in brain function between chronic cannabis users and non-users might also arise from confounding factors such as polydrug use, alcohol use, withdrawal, economic status, or lifestyle conditions. We propose a methodology that highlights the relevance of acute Δ⁹-tetrahydrocannabinol (THC) dosing studies for a direct assessment of neuroadaptations in chronic cannabis users. The approach includes quantification of neurochemical, receptor, and functional brain network changes in response to an acute cannabis challenge, as well as stratification of cannabis using groups ranging from occasional to cannabis-dependent individuals. The methodology allows for an evaluation of THC induced neuroadaptive and neurocognitive changes across cannabis use history, that can inform neurobiological models on reward driven, compulsive cannabis use.

Effects of Cigarette Smoking on Resting-State Functional Connectivity of the Nucleus Basalis of Meynert in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is the prodromal phase of Alzheimer’s disease (AD) and has a high risk of progression to AD. Cigarette smoking is one of the important modifiable risk factors in AD progression. Cholinergic dysfunction, especially the nucleus basalis of Meynert (NBM), is the converging target connecting smoking and AD. However, how cigarette smoking affects NBM connectivity in MCI remains unclear.

Objective: This study aimed to evaluate the interaction effects of condition (non-smoking vs. smoking) and diagnosis [cognitively normal (CN) vs. MCI] based on the resting-state functional connectivity (rsFC) of the NBM.

Methods: After propensity score matching, we included 86 non-smoking CN, 44 smoking CN, 62 non-smoking MCI, and 32 smoking MCI. All subjects underwent structural and functional magnetic resonance imaging scans and neuropsychological tests. The seed-based rsFC of the NBM with the whole-brain voxel was calculated. Furthermore, the mixed effect analysis was performed to explore the interaction effects between condition and diagnosis on rsFC of the NBM.

Results: The interaction effects of condition × diagnosis on rsFC of the NBM were observed in the bilateral prefrontal cortex (PFC), bilateral supplementary motor area (SMA), and right precuneus/middle occipital gyrus (MOG). Specifically, the smoking CN showed decreased rsFC between left NBM and PFC and increased rsFC between left NBM and SMA compared with non-smoking CN and smoking MCI. The smoking MCI showed reduced rsFC between right NBM and precuneus/MOG compared with non-smoking MCI. Additionally, rsFC between the NBM and SMA showed a significant negative correlation with Wechsler Memory Scale-Logical Memory (WMS-LM) immediate recall in smoking CN (r = −0.321, p = 0.041).

Conclusion: Our findings indicate that chronic nicotine exposure through smoking may lead to functional connectivity disruption between the NBM and precuneus in MCI patients. The distinct alteration patterns on NBM connectivity in CN smokers and MCI smokers suggest that cigarette smoking has different influences on normal and impaired cognition.

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.

Repetitive transcranial magnetic stimulation for smoking cessation: a pivotal multicenter double-blind randomized controlled trial

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation method increasingly used to treat psychiatric disorders, primarily depression. Initial studies suggest that rTMS may help to treat addictions, but evaluation in multicenter randomized controlled trials (RCTs) is needed. We conducted a multicenter double-blind RCT in 262 chronic smokers meeting DSM-5 criteria for tobacco use disorder, who had made at least one prior failed attempt to quit, with 68% having made at least three failed attempts. They received three weeks of daily bilat-eral active or sham rTMS to the lateral prefrontal and insular cortices, followed by once weekly rTMS for three weeks. Each rTMS session was administered following a cue-induced craving procedure, and participants were monitored for a total of six weeks. Those in abstinence were monitored for additional 12 weeks. The primary outcome measure was the four-week continuous quit rate (CQR) until Week 18 in the intent-to-treat efficacy set, as determined by daily smoking diaries and verified by urine cotinine measures. The trial was registered at ClinicalTrials.gov (NCT02126124). In the intent-to-treat analysis set (N=234), the CQR until Week 18 was 19.4% following active and 8.7% following sham rTMS (X² =5.655, p=0.017). Among completers (N=169), the CQR until Week 18 was 28.0% and 11.7%, respectively (X² =7.219, p=0.007). The reduction in cigarette consumption and craving was significantly greater in the active than the sham group as early as two weeks into treatment. This study establishes a safe treatment protocol that promotes smoking cessation by stimulating relevant brain circuits. It represents the first large multicenter RCT of brain stimulation in addiction medicine, and has led to the first clearance by the US Food and Drug Administration for rTMS as an aid in smok-ing cessation for adults.

Association between functional brain alterations and neuropsychological scales in male chronic smokers using resting-state fMRI

RATIONALE

Recent studies have demonstrated that cigarette smoking is related to changes in brain structure and function. However, few studies focus on functional brain differences between male chronic smokers and nonsmokers in both local spontaneous activity and whole-brain functional networks.

OBJECTIVES

Our study recruited 67 chronic smokers and 43 nonsmokers who underwent functional magnetic resonance imaging (fMRI) scans to investigate functional activity and connectivity alterations in chronic smokers.

METHODS

We used the mean fractional amplitude of the low-frequency fluctuation (mfALFF) and mean regional homogeneity (mReHo) methods to investigate resting-state spontaneous activity in chronic smokers and nonsmokers. The graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also used to investigate functional connectivity alterations.

RESULTS

Compared with nonsmokers, chronic smokers exhibited higher activation in the reward system and portions of the prefrontal cortex but lower activation in the default mode networks (DMN) and visual-related regions. In addition, correlation analysis was conducted to assess the associations between neuroimaging findings and the severity of nicotine dependence or expectations of smoking effects. Our results showed that certain brain regions correlated with the Fagerström Test for Nicotine Dependence (FTND), the positive aspect of the Drug Use Disorders Identification Test Extended (DUDIT-E), and the negative aspect of the DUDIT-E, especially in the attentional control networks and hippocampus. The graph theoretical analysis (GTA) results indicated chronic smokers exhibited a trend toward increased assortativity. Our network-based statistical (NBS) analysis revealed reduced functional connections between the subnetwork in the prefrontal cortex, olfactory cortex, angular gyrus, and cingulate gyrus of chronic smokers.

CONCLUSIONS

We concluded that chronic smokers have neural adaptations in local spontaneous activity but remain healthy brain functional networks.

The changes of brain functional networks in young adult smokers based on independent component analysis

Intrinsic functional connectivity (FC) networks, including the default mode network (DMN), central executive network (CEN), and salience network (SN), have been implicated in nicotine addiction. However, litter evidence exists about the abnormalities in the three networks in young adult smokers. Forty-eight young adult smokers and 49 age- and gender-matched non-smokers were recruited in the present study. Resting-state functional magnetic resonance imaging (fMRI) data were analyzed by a combination of independent component analysis (ICA) and dual regression to identify potential differences of FC patterns in the DMN, CEN, and SN. Compared to non-smokers, young adult smokers showed enhanced FC of the left posterior cingulate cortex (LPCC), right medial prefrontal cortex (RMPFC) and right precuneus within the DMN network, of the right dorsolateral prefrontal cortex (DLPFC) within the right CEN, and of the left anterior insula (LAI) within the SN. We also found increased FC between the DMN, CEN and key node of the SN (anterior insula, AI). Correlation analysis showed that the increased FC within the networks was significantly correlated with smoking behaviors (pack-years, smoking duration, FTND, first smoking age, and number of cigarettes per day). Our findings may provide additional evidence for conceptualizing the framework of nicotine addiction as a disease of intercommunicating brain networks.

Increased striatal functional connectivity is associated with improved smoking cessation outcomes: A preliminary study

The striatum is the critical area of reward processing and has been repeatedly linked to nicotine addiction. However, it remains unclear whether different smoking cessation outcomes (relapse or not) are associated with different functional connectivity changes of the striatum during smoking cessation treatment. A total of 30 treatment-seeking smokers were recruited in the study and underwent magnetic resonance imaging (MRI) scans immediately before and after a 12-week treatment with varenicline. After the 12-week treatment with varenicline, 14 subjects relapsed to smoking (relapsers), whereas 16 not relapsed (nonrelapsers). Changes in resting-state functional connectivity (rsFC) across groups and visits were assessed using repeated measures analysis of covariance (ANCOVA). Significant interaction effects were detected: (1) between left nucleus accumbens (NAc) and left orbitofrontal cortex (OFC), insula, inferior frontal gyrus (IFG), and bilateral precuneus; (2) between right NAc and left insula, IFG, and bilateral dorsolateral prefrontal cortex (DLPFC); and (3) between bilateral putamen and left precuneus. Post hoc region-of-interest analyses in brain areas showing interaction effects indicated significantly decreased rsFC after treatment compared with before treatment in relapsers but opposite longitudinal changes in nonrelapers. These novel findings suggest that increased striatal rsFC is associated with improved smoking cessation outcomes. These striatal functional circuits may serve as potential therapeutic targets for more efficacious treatment of nicotine addiction.

Altered resting functional connectivity patterns associated with problematic substance use and substance use disorders during adolescence

BACKGROUND

Adolescence is typified by increasing rates of substance use and the development of substance use disorders (SUD). Aberrant connectivity between cortical regions involved in executive control, and subcortical regions has been suggested to be associated with SUD and problematic substance use among adolescents. Few studies, however, have investigated system-level or whole-brain functional connectivity (FC) in order to test this hypothesis.

METHODS

In a sample of 114 adolescents (mean age = 17.62 years, SD = 1.23, 61F) from the community, the present study used resting-state functional magnetic resonance imaging and independent component analysis to study executive control-subcortical network (ECN-SCN) coupling in adolescent SUD (n=18) and problematic substance use (n=34). In addition, whole-brain FC analyses were also conducted.

RESULTS

Problematic substance use, but not SUD, was associated with increased negative ECN-SCN coupling (p = 0.026). The whole-brain FC analysis showed insula-associated hypoconnectivity in the SUD group (p = 0.037), which was negatively correlated with frequency of substance use.

CONCLUSIONS

Findings implicate different neural circuitry underlying adolescent SUD versus problematic use. Greater negative coupling between the SCN and ECN in adolescents with problematic substance use could underlie risk for future development of SUD or other mental health problems. Although we cannot infer directionality, hypoconnectivity within the insula in adolescents with SUD may indicate addiction-related alterations in interoceptive awareness or impairments in decision-making.

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.

Behavioral and brain signatures of substance use vulnerability in childhood

The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by developing generalizable models that predict early susceptibility. The aims of the current study were to identify and characterize behavioral and brain models of vulnerability to future substance use. Principal components analysis (PCA) of behavioral risk factors were used together with connectome-based predictive modeling (CPM) during rest and task-based functional imaging to generate predictive models in a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain & Cognitive Development (ABCD) study (NDA release 2.0.1). Dimensionality reduction (n = 9,437) of behavioral measures associated with substance use identified two latent dimensions that explained the largest amount of variance: risk-seeking (PC1; e.g., curiosity to try substances) and familial factors (PC2; e.g., family history of substance use disorder). Using cross-validated regularized regression in a subset of data (Year 1 Fast Track data; n>1,500), functional connectivity during rest and task conditions (resting-state; monetary incentive delay task; stop signal task; emotional n-back task) significantly predicted individual differences in risk-seeking (PC1) in held-out participants (partial correlations between predicted and observed scores controlling for motion and number of frames [r_p]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (r_p: 0.03-0.06). These results demonstrate a novel approach to understanding substance use vulnerability, which—together with mechanistic perspectives—may inform strategies aimed at early identification of risk for addiction.

Advances in biofeedback and neurofeedback studies on smoking

Smoking is a leading cause of morbidity and premature death constituting a global health challenge. Although, pharmacological and behavioral approaches comprise the mainstay of smoking cessation interventions, the efficacy and safety of pharmacotherapy is not demonstrated for some populations. Non-pharmacological approaches, such as biofeedback (BF) and neurofeedback (NF) could facilitate self-regulation of predisposing factors of relapse such as craving and stress. The current review aims to aggregate the existing evidence regarding the effects of BF and NF training on smokers. Relevant studies were identified through searching in Scopus, PubMed and Cochrane Library, and through hand-searching the references of screened articles. Peer-reviewed controlled and uncontrolled studies, where BF and/or NF training was administered, were included and evaluated according to PICOS framework. Narrative qualitative synthesis of ten eligible studies was performed, aggregated into three categories according to training provided. BF outcomes seem to be affected by smoking behavior prior to training; individualized EEG NF training holds promise for modulating craving-related response while minimizing the required number of sessions. Real-time fMRI NF studies concluded that nicotine-dependent individuals could modulate craving-related brain responses, while mixed results were revealed regarding smokers' ability to modulate brain responses related to resistance towards the urge to smoke. BF and NF training seem to facilitate modulation of autonomous and/or central nervous system activity while also transferring this learned self-regulation to behavioral outcomes. BF and NF training should a) address remaining issues on specificity and scientific validity, b) target diverse demographics, and c) produce robust reproducible methodologies and clinical guidelines for relevant health care providers, in order to be considered as viable complementary tools to standard smoking cessation care.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Intrinsic differences in insular circuits moderate the negative association between nicotine dependence and cingulate-striatal connectivity strength

The development of brain-based biomarkers to assess nicotine dependence severity and treatment efficacy are essential to improve the current marginally effective treatment outcomes. Cross-sectional resting state functional connectivity (rsFC) studies in humans identified a circuit between the dorsal anterior cingulate cortex and the ventral striatum that negatively correlated with increased nicotine dependence severity but was unaffected by acute nicotine administration, suggesting a trait marker of addiction. However, whether this trait circuit dysregulation is predispositional to or resultant from nicotine dependence is unclear. Using a rat model of nicotine dependence with longitudinal fMRI measurements, we assessed the relationship between ACC-striatal rsFC and nicotine dependence severity. Data-driven modularity-based parcellation of the rat medial prefrontal cortex (mPFC) combined with seed-based connectivity analysis with the striatum recapitulated the cingulate-striatum relationship observed in humans. Furthermore, the relationship between cingulate-striatal brain circuits and nicotine dependence severity as indexed by the intensity of precipitated withdrawal, was fully statistically moderated by a predispositional insular-frontal cortical functional circuit. These data suggest that the identified trans-species ACC-striatal circuit relationship with nicotine dependence severity is dysregulated following chronic nicotine administration-induced dependence and may be biased by individual differences in predispositional insula-based striatal-frontal circuits, highlighting the circuit's potential as a biomarker of dependence severity.

Resting-State Connectivity in Former, Current, and Never Smokers

INTRODUCTION

Understanding the neural mechanisms that support successful smoking cessation is vital to the development of novel treatments for nicotine dependence.

METHOD

To this end, we compared resting-state functional connectivity across three smoking groups: current, never, and former smokers. We used an independent component analysis (ICA) that allowed us to compare differences in intrinsic, large-scale networks across our groups. Using this technique, we were able to compare group differences across resting-state networks without the requirement of identifying coordinate-based regions of interest.

RESULTS

Overall, the ICA resulted in networks that were largely consistent with previous reports, including bilateral executive control networks, salience, and a default mode network. Group comparisons among the three groups revealed differences in three networks including sensorimotor, dorsal attention, and default mode networks, with differences localized to pre/postcentral gyrus, lateral occipital cortex, and superior parietal lobe. In all regions showing a difference, current smokers showed increased network amplitude compared to former and never smokers.

CONCLUSION

Although some theoretical models of recovery have suggested an important role of frontal cortex and cognitive control, the current results seem to suggest that reductions in posterior regions including superior parietal lobe and somatosensory cortex may play a key role in maintaining long-term abstinence from cigarettes.

IMPLICATIONS

The submitted research is a novel contribution to the study of successful nicotine abstinence, in part, because it includes individuals who have successfully overcome nicotine dependence. The use of ICA allowed for examination of large-scale resting-state networks throughout the brain without the need for specifying numerous regions of interest. This research supports the view that overcoming nicotine dependence may depend on reducing spontaneous activity in posterior regions of the brain rather than solely enhancing frontal control.

Distal Functional Connectivity of Known and Emerging Cortical Targets for Therapeutic Noninvasive Stimulation

Noninvasive stimulation is an emerging modality for the treatment of psychiatric disorders, including addiction. A crucial element in effective cortical target selection is its distal influence. We approached this question by examining resting-state functional connectivity patterns in known and potential stimulation targets in 145 healthy adults. We compared connectivity patterns with distant regions of particular relevance in the development and maintenance of addiction. We used stringent Bonferroni-correction for multiple comparisons. We show how the anterior insula, dorsal anterior cingulate, and ventromedial prefrontal cortex had opposing functional connectivity with striatum compared to the dorsomedial prefrontal cortex. However, the dorsolateral prefrontal cortex, the currently preferred target, and the presupplementary motor area had strongest negative connections to amygdala and hippocampus. Our findings highlight differential and opposing influences as a function of cortical site, underscoring the relevance of careful cortical target selection dependent on the desired effect on subcortical structures. We show the relevance of dorsal anterior cingulate and ventromedial prefrontal cortex as emerging cortical targets, and further emphasize the anterior insula as a potential promising target in addiction treatment, given its strong connections to ventral striatum, putamen, and substantia nigra.

Alterations in resting-state functional connectivity in substance use disorders and treatment implications

Substance use disorders (SUD) are diseases of the brain, characterized by aberrant functioning in the neural circuitry of the brain. Resting state functional connectivity (rsFC) can illuminate these functional changes by measuring the temporal coherence of low-frequency fluctuations of the blood oxygenation level-dependent magnetic resonance imaging signal in contiguous or non-contiguous regions of the brain. Because this data is easy to obtain and analyze, and therefore fairly inexpensive, it holds promise for defining biological treatment targets in SUD, which could help maximize the efficacy of existing clinical interventions and develop new ones. In an effort to identify the most likely "treatment targets" obtainable with rsFC we summarize existing research in SUD focused on 1) the relationships between rsFC and functionality within important psychological domains which are believed to underlie relapse vulnerability 2) changes in rsFC from satiety to deprived or abstinent states 3) baseline rsFC correlates of treatment outcome and 4) changes in rsFC induced by treatment interventions which improve clinical outcomes and reduce relapse risk. Converging evidence indicates that likely "treatment target" candidates, emerging consistently in all four sections, are reduced connectivity within executive control network (ECN) and between ECN and salience network (SN). Other potential treatment targets also show promise, but the literature is sparse and more research is needed. Future research directions include data-driven prediction analyses and rsFC analyses with longitudinal datasets that incorporate time since last use into analysis to account for drug withdrawal. Once the most reliable biological markers are identified, they can be used for treatment matching, during preliminary testing of new pharmacological compounds to establish clinical potential ("target engagement") prior to carrying out costly clinical trials, and for generating hypotheses for medication repurposing.

Preliminary analysis of resting state functional connectivity in young adults with subtypes of bipolar disorder

BACKGROUND

A precision medicine approach to bipolar disorder (BD) requires greater knowledge of neural mechanisms, especially within the BD phenotype. The present study evaluated differences in resting state functional connectivity (RSFC) between young adults followed longitudinally since childhood with full-threshold type I BD (BD-I)-characterized by distinct manic episodes-or a more sub-syndromal presentation of BD (BD Not Otherwise Specified [BD-NOS]), compared to one another and to healthy controls (HC). Independent Components Analysis (ICA), a multivariate data-driven method, and dual regression were used to explore whether connectivity within resting state networks (RSNs) differentiated the groups, especially for characteristic fronto-limbic alterations in BD.

METHODS

Young adults (ages 18-30) with BD-I (n = 28), BD-NOS (n = 14), and HCs (n = 52) underwent structural and RSFC neuroimaging. ICA derived 30 components from RSFC data; a subset of these components, representing well-characterized RSNs, was used for between-group analyses.

RESULTS

Participants with BD-I had significantly greater connectivity strength between the executive control network and right caudate vs. HCs. Participants with BD-NOS had significantly greater connectivity strength between the sensorimotor network and left precentral gyrus vs. HCs, which was significantly related to psychiatric symptoms.

LIMITATIONS

Limitations included small BD-NOS sample size and variation in BD mood state and medication status.

CONCLUSIONS

Results for BD-I participants support prior findings of fronto-limbic alterations characterizing BD. Alterations in the sensorimotor network for adults with BD-NOS aligns with the small but growing body of evidence that sensorimotor network alterations may represent a marker for vulnerability to BD. Further study is required to evaluate specificity.

Brain Function Network and Young Adult Smokers: A Graph Theory Analysis Study

Cigarette smoking is associated with abnormalities in the widespread inter-regional functional connectivity of the brain. However, few studies focused on the abnormalities in the topological organization of brain functional networks in young smokers. In the current study, resting-state functional magnetic resonance images were acquired from 30 young male smokers and 32 age-, gender-, and education-matched healthy male nonsmokers. A functional network was constructed by calculating the Pearson correlation coefficients among 246 subregions in the human Brainnetome Atlas. The topological parameters were compared between smokers and nonsmokers. The results showed that the functional network of both young smokers and nonsmokers had small-world topology. Compared to nonsmokers, young smokers exhibited a decreased clustering coefficient (C_p) and local network efficiency (E_local). C_p and E_local were negatively correlated with the duration of cigarette use. In addition, increased nodal efficiency (E_nodal) was mainly located in the prefrontal cortex (PFC), cingulate gyrus, insula, and caudate. Decreased connectivities among the PFC, cingulate gyrus, insula, basal ganglia (of specific node), and thalamus were also observed. In sum, we revealed the abnormal topological organization of brain functional networks in young smokers, which may improve our understanding of the neural mechanism of young smokers from a brain functional network topological organization perspective.

Altered Functional Connectivity in Resting State Networks in Tourette's Disorder

Introduction: Brain regions are anatomically and functionally interconnected in order to facilitate important functions like cognition and movement. It remains incompletely understood how brain connectivity contributes to the pathophysiology of Tourette's disorder (TD). By using resting-state functional MRI, we aimed to identify alterations in the default mode network (DMN), frontal-parietal network (FPN), sensori-motor network (SMN), and salience network (SN) in TD compared with healthy control (HC) subjects. Method: In 23 adult TD patients and 22 HC, 3T-MRI resting-state scans were obtained. Independent component analysis was performed comparing TD and HC to investigate connectivity patterns within and between resting-state networks. Results: TD patients showed higher involvement of the dorsal medial prefrontal cortex in the connectivity of the DMN and less involvement of the inferior parietal cortex in the connectivity of the FPN when compared to HC. Moreover, TD patients showed a stronger coupling between DMN and left FPN than HC. Finally, in TD patients, functional connectivity within DMN correlated negatively with tic severity. Conclusion: We tentatively interpret the increased functional connectivity within DMN in TD patients as compensatory to the lower functional connectivity within left FPN. The stronger coupling between DMN and left FPN, together with the finding that higher DMN intrinsic connectivity is associated with lower tic severity would indicate that DMN is recruited to exert motor inhibition.

Exploring the Neuroplastic Effects of Biofeedback Training on Smokers

Smoking and stress cooccur in different stages of a nicotine addiction cycle, affecting brain function and showing additive impact on different physiological responses. Resting-state functional connectivity has shown potential in identifying these alterations. Nicotine addiction has been associated with detrimental effects on functional integrity of the central nervous system, including the organization of resting-state networks. Prolonged stress may result in enhanced activation of the default mode network (DMN). Considering that biofeedback has shown promise in alleviating physiological manifestations of stress, we aimed to explore the possible neuroplastic effects of biofeedback training on smokers. Clinical, behavioral, and neurophysiological (resting-state EEG) data were collected from twenty-seven subjects before and after five sessions of skin temperature training. DMN functional cortical connectivity was investigated. While clinical status remained unaltered, the degree of nicotine dependence and psychiatric symptoms were significantly improved. Significant changes in DMN organization and network properties were not observed, except for a significant increase of information flow from the right ventrolateral prefrontal cortex and right temporal pole cortex towards other DMN components. Biofeedback aiming at stress alleviation in smokers could play a protective role against maladaptive plasticity of connectivity. Multiple sessions, individualized interventions and more suitable methods to promote brain plasticity, such as neurofeedback training, should be considered.

Emotional intelligence is associated with connectivity within and between resting state networks

Emotional intelligence (EI) is defined as an individual’s capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI.

Changes in resting state functional brain connectivity and withdrawal symptoms are associated with acute electronic cigarette use

Resting state functional brain connectivity (rsFC) may be an important neuromarker of smoking behavior. Prior research has shown, among cigarette smokers, that nicotine administration alters rsFC within frontal and parietal cortices involved in executive control, as well as striatal regions that drive reward processing. These changes in rsFC have been associated with reductions in withdrawal symptom severity. We currently have a limited understanding of how rsFC is affected by the use of electronic cigarettes (ecigs), an increasingly popular class of products, the members of which deliver nicotine with varying effectiveness. The current study used fMRI to determine the effects of ecig use on rsFC and withdrawal symptoms. Independent component, dual regression, and permutation analyses were conducted on rsFC collected from ecig users before and after an ecig use episode (n=9) that occurred after 14h of nicotine abstinence. Similar to the known effects of nicotine administration, ecig use decreased rsFC of two clusters in the right frontal pole and frontal medial cortex with an attentional control salience network, and decreased rsFC of five clusters in the left thalamus, insula, and brain stem with a reward network encompassing the striatum. Ecig use increased inverse coupling between the prefrontal reward network and the right frontoparietal executive control network. Reductions in craving and difficulty with concentration were correlated with decreases in coupling strength between reward and executive control networks. These preliminary results suggest that the effects of ecig use on rsFC are similar to those seen with nicotine administration in other forms. In order to gain insight into the addictive potential of ecigs, further research is needed to understand the neural influence of ecigs across the range of nicotine delivery within this class of products.

The Impact of Combinations of Alcohol, Nicotine, and Cannabis on Dynamic Brain Connectivity

Alcohol, nicotine, and cannabis are among the most commonly used drugs. A prolonged and combined use of these substances can alter normal brain wiring in different ways depending on the consumed cocktail mixture. Brain connectivity alterations and their change with time can be assessed using functional magnetic resonance imaging (fMRI) because of its spatial and temporal content. Here, we estimated dynamic functional network connectivity (dFNC) as derived from fMRI data to investigate the effects of single or combined use of alcohol, nicotine, and cannabis. Data from 534 samples were grouped according to their substance use combination as controls (CTR), smokers (SMK), drinkers (DRN), smoking-and-drinking subjects (SAD), marijuana users (MAR), smoking-and-marijuana users (SAM), marijuana-and-drinking users (MAD), and users of all three substances (ALL). The DRN group tends to exhibit decreased connectivity mainly in areas of sensorial and motor control, a result supported by the dFNC outcome and the alcohol use disorder identification test. This trend dominated the SAD group and in a weaker manner MAD and ALL. Nicotine consumers were characterized by an increment of connectivity between dorsal striatum and sensorimotor areas. Where possible, common and separate effects were identified and characterized by the analysis of dFNC data. Results also suggest that a combination of cannabis and nicotine have more contrasting effects on the brain than a single use of any of these substances. On the other hand, marijuana and alcohol might follow an additive effect trend. We concluded that all of the substances have an impact on brain connectivity, but the effect differs depending on the dFNC state analyzed.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

White matter integrity of central executive network correlates with enhanced brain reactivity to smoking cues

The attentional bias to smoking cues contributes to smoking cue reactivity and cognitive declines underlines smoking behaviors, which were probably associated with the central executive network (CEN). However, little is known about the implication of the structural connectivity of the CEN in smoking cue reactivity and cognitive control impairments in smokers. In the present study, the white matter structural connectivity of the CEN was quantified in 35 smokers and 26 non-smokers using the diffusion tensor imaging and deterministic fiber tractography methods. Smoking cue reactivity was evaluated using cue exposure tasks, and cognitive control performance was assessed by the Stroop task. Relative to non-smokers, smokers showed increased fractional anisotropy (FA) values of the bilateral CEN fiber tracts. The FA values of left CEN positively correlated with the smoking cue-induced activation of the dorsolateral prefrontal cortex and right middle occipital cortex in smokers. Meanwhile, the FA values of left CEN positively correlated with the incongruent errors during Stroop task in smokers. Collectively, the present study highlighted the role of the structural connectivity of the CEN in smoking cue reactivity and cognitive control performance, which may underpin the attentional bias to smoking cues and cognitive deficits in smokers. The multimodal imaging method by forging links from brain structure to brain function extended the notion that structural connections can modulate the brain activity in specific projection target regions. Hum Brain Mapp 38:6239-6249, 2017. © 2017 Wiley Periodicals, Inc.

Chronic Tobacco-Smoking on Psychopathological Symptoms, Impulsivity and Cognitive Deficits in HIV-Infected Individuals

HIV-infected individuals (HIV+) has 2-3 times the rate of tobacco smoking than the general population, and whether smoking may lead to greater psychiatric symptoms or cognitive deficits remains unclear. We evaluated the independent and combined effects of being HIV+ and chronic tobacco-smoking on impulsivity, psychopathological symptoms and cognition. 104 participants [27 seronegative (SN)-non-Smokers, 26 SN-Smokers, 29 HIV+ non-Smokers, 22 HIV+ Smokers] were assessed for psychopathology symptoms (Symptom Checklist-90, SCL-90), depressive symptoms (Center for Epidemiologic Studies-Depression Scale, CES-D), impulsivity (Barratt Impulsiveness Scale, BIS), decision-making (The Iowa Gambling Task, IGT, and Wisconsin Card Sorting Test, WCST), and cognition (seven neurocognitive domains). Both HIV+ and Smoker groups had higher SCL-90 and CES-D scores, with highest scores in HIV+ Smokers. On BIS, both HIV+ and Smokers had higher Total Impulsiveness scores, with higher behavioral impulsivity in Smokers, highest in HIV+ Smokers. Furthermore, across the four groups, HIV+ Smokers lost most money and made fewest advantageous choices on the IGT, and had highest percent errors on WCST. Lastly, HIV+ had lower z-scores on all cognitive domains, with the lowest scores in HIV+ Smokers. These findings suggest that HIV-infection and chronic tobacco smoking may lead to additive deleterious effects on impulsivity, psychopathological (especially depressive) symptoms and cognitive dysfunction. Although greater impulsivity may be premorbid in HIV+ and Smokers, the lack of benefits of nicotine in chronic Smokers on attention and psychopathology, especially those with HIV-infection, may be due to the negative effects of chronic smoking on dopaminergic and cardio-neurovascular systems. Tobacco smoking may contribute to psychopathology and neurocognitive disorders in HIV+ individuals.

Functional network connectivity predicts treatment outcome during treatment of nicotine use disorder

Altered resting state functional connectivity (rsFC) and functional network connectivity (FNC), which is a measure of coherence between brain networks, may be associated with nicotine use disorder (NUD). We hypothesized that higher connectivity between insula and 1) dorsal anterior cingulate cortex (dACC) and 2) dorsolateral prefrontal cortex (dlPFC) would predict better treatment outcomes. We also performed an exploratory analysis of the associations between FNC values between additional key frontal and striatal regions and treatment outcomes. One hundred and forty four individuals with NUD underwent a resting state session during functional MRI prior to randomization to treatment with varenicline (n=82) or placebo. Group independent component analysis (ICA) was utilized to extract individual subject components and time series from intrinsic connectivity networks in aforementioned regions, and FNC between all possible pairs were calculated. Higher FNC between insula and dACC (rho=0.21) was significantly correlated with lower levels of baseline smoking quantity but did not predict treatment outcome upon controlling for baseline smoking. Higher FNC between putamen and dACC, caudate and dACC, and caudate and dlPFC significantly predicted worse treatment outcome in participants reporting high subjective withdrawal before the scan. FNC between key regions hold promise as biomarkers to predict outcome in NUD.

Combining Multiple Resting-State fMRI Features during Classification: Optimized Frameworks and Their Application to Nicotine Addiction

Machine learning techniques have been applied to resting-state fMRI data to predict neurological or neuropsychiatric disease states. Existing studies have used either a single type of resting-state feature or a few feature types (<4) in the prediction model. However, resting-state data can be processed in many different ways, yielding different feature types containing complementary and/or novel information, leaving uncertain the most informative features to provide to the classifier. In this study, multiple resting-state features were calculated from two main analytical categories: local measures and network measures. Feature selection was adopted using an optimized grid-search approach selecting top ranked features from statistical tests. We then tested three optimized frameworks: feature combination, kernel combination, and classifier combination, all using the support vector machine as an elementary classifier, to combine these resting-state feature types. When applied to nicotine addiction, with a cohort size of 100 smokers and 100 non-smokers, via a 10-fold cross-validation procedure, the feature combination and the classifier combination achieved an accuracy of 75.5%, while the kernel combination achieved a 73.0% accuracy; all three combination frameworks improved classification performance compared to the single feature type based results (best accuracy 70.5%). This study not only reveals the discriminative power of resting-state data, but also demonstrates the efficiency of combining multiple features from one data phenotype to improve classification performance.

The left dorsolateral prefrontal cortex and caudate pathway: New evidence for cue-induced craving of smokers

Although the activation of the prefrontal cortex (PFC) and the striatum had been found in smoking cue induced craving task, whether and how the functional interactions and white matter integrity between these brain regions contribute to craving processing during smoking cue exposure remains unknown. Twenty-five young male smokers and 26 age- and gender-matched nonsmokers participated in the smoking cue-reactivity task. Craving related brain activation was extracted and psychophysiological interactions (PPI) analysis was used to specify the PFC-efferent pathways contributed to smoking cue-induced craving. Diffusion tensor imaging (DTI) and probabilistic tractography was used to explore whether the fiber connectivity strength facilitated functional coupling of the circuit with the smoking cue-induced craving. The PPI analysis revealed the negative functional coupling of the left dorsolateral prefrontal cortex (DLPFC) and the caudate during smoking cue induced craving task, which positively correlated with the craving score. Neither significant activation nor functional connectivity in smoking cue exposure task was detected in nonsmokers. DTI analyses revealed that fiber tract integrity negatively correlated with functional coupling in the DLPFC-caudate pathway and activation of the caudate induced by smoking cue in smokers. Moreover, the relationship between the fiber connectivity integrity of the left DLPFC-caudate and smoking cue induced caudate activation can be fully mediated by functional coupling strength of this circuit in smokers. The present study highlighted the left DLPFC-caudate pathway in smoking cue-induced craving in smokers, which may reflect top-down prefrontal modulation of striatal reward processing in smoking cue induced craving processing. Hum Brain Mapp 38:4644-4656, 2017. © 2017 Wiley Periodicals, Inc.

The impacts of pesticide and nicotine exposures on functional brain networks in Latino immigrant workers

Latino immigrants that work on farms experience chronic exposures to potential neurotoxicants, such as pesticides, as part of their work. For tobacco farmworkers there is the additional risk of exposure to moderate to high doses of nicotine. Pesticide and nicotine exposures have been associated with neurological changes in the brain. Long-term exposure to cholinesterase-inhibiting pesticides, such as organophosphates and carbamates, and nicotine place this vulnerable population at risk for developing neurological dysfunction. In this study we examined whole-brain connectivity patterns and brain network properties of Latino immigrant workers. Comparisons were made between farmworkers and non-farmworkers using resting-state functional magnetic resonance imaging data and a mixed-effects modeling framework. We also evaluated how measures of pesticide and nicotine exposures contributed to the findings. Our results indicate that despite having the same functional connectivity density and strength, brain networks in farmworkers had more clustered and modular structures when compared to non-farmworkers. Our findings suggest increased functional specificity and decreased functional integration in farmworkers when compared to non-farmworkers. Cholinesterase activity was associated with population differences in community structure and the strength of brain network functional connections. Urinary cotinine, a marker of nicotine exposure, was associated with the differences in network community structure. Brain network differences between farmworkers and non-farmworkers, as well as pesticide and nicotine exposure effects on brain functional connections in this study, may illuminate underlying mechanisms that cause neurological implications in later life.

Modulation of Brain Activity with Noninvasive Transcranial Direct Current Stimulation (tDCS): Clinical Applications and Safety Concerns

Transcranial direct current stimulation (tDCS) is a widely-used tool to induce neuroplasticity and modulate cortical function by applying weak direct current over the scalp. In this review, we first introduce the underlying mechanism of action, the brief history from discovery to clinical scientific research, electrode positioning and montages, and parameter setup of tDCS. Then, we review tDCS application in clinical samples including people with drug addiction, major depression disorder, Alzheimer's disease, as well as in children. This review covers the typical characteristics and the underlying neural mechanisms of tDCS treatment in such studies. This is followed by a discussion of safety, especially when the current intensity is increased or the stimulation duration is prolonged. Given such concerns, we provide detailed suggestions regarding safety procedures for tDCS operation. Lastly, future research directions are discussed. They include foci on the development of multi-tech combination with tDCS such as with TMS and fMRI; long-term behavioral and morphological changes; possible applications in other research domains, and more animal research to deepen the understanding of the biological and physiological mechanisms of tDCS stimulation.

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

Alcohol and nicotine intake result in neurological alterations at the circuit level. Resting state functional connectivity has shown great potential in identifying these alterations. However, current studies focus on specific seeds and leave out many brain regions where effects might exist. The present study uses a data driven technique for brain segmentation covering the whole brain. Functional magnetic-resonance-imaging (fMRI) data were collected from 188 subjects:51 non-substance consumption controls (CTR), 36 smoking-and-drinking subjects (SAD), 28 drinkers (DRN), and 73 smokers (SMK). Data were processed using group independent component analysis to derive resting state networks (RSN). The resting state functional network connectivity (rsFNC) was then calculated through correlation between time courses. One-way ANOVA tests were used to detect rsFNC differences among the four groups. A total of 50 ANOVA tests were significant after multi-comparison correction. Results delineate a general pattern of hypo-connectivity in the substance consumers. Precuneus, postcentral gyrus, insula and visual cortex were the main brain areas with rsFNC reduction suggesting reduced interoceptive awareness in drinkers. In addition, connectivity reduction between postcentral and one RSN covering right fusiform and lingual gyri showed significant association with severity of hazardous drinking. In smokers, connectivity changes agreed with the idea of a shift towards endogenous information processing, represented by the DMN. Hypo-connectivity between thalamus and putamen was observed in smokers. In contrast, the angular gyrus showed hyper-connectivity with the precuneus linked to smoking and significantly correlated with nicotine dependence severity. In spite of the presence of common effects, our results suggest that particular effects of alcohol and nicotine can be separated and identified. Results also suggest that concurrent use of both substances affects brain connectivity in a complex manner, requiring careful consideration of interaction effects.