Use of Tobacco Products and Suicide Attempts Among Elementary School-Aged Children.

Importance: The use of tobacco products, including e-cigarettes and vaping, has rapidly increased among children. However, despite consistent associations found between smoking cigarettes and suicidal behaviors among adolescents and adults, there are limited data on associations between emerging tobacco products and suicidal behaviors, especially among preadolescent children. Objective: To examine whether the use of tobacco products is associated with nonsuicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SAs) among preadolescent children. Design, Setting, and Participants: This cohort study, conducted from September 1, 2022, to September 5, 2023, included participants in the Adolescent Brain Cognitive Development study, a population-based cohort of 11 868 US children enrolled at 9 and 10 years of age. The cross-sectional investigation focused on 3-year periods starting from the baseline to year 2 of follow-up. Statistical analysis was performed from October 1, 2022, to June 30, 2023. Main Outcomes and Measures: Children's use of tobacco products was assessed based on youth reports, including lifetime experiences of various nicotine-related products, supplemented with hair toxicologic tests. Main outcomes were children's lifetime experiences of NSSI, SI, and SAs, assessed using the K-SADS-5 (Kiddie Schedule for Affective Disorders and Schizophrenia for the DSM-5). Multivariate logistic regression was conducted to examine the associations of the use of tobacco products with NSSI, SI, and SAs among the study participants. Sociodemographic, familial, and children's behavioral, temperamental, and clinical outcomes were adjusted in the analyses. Results: Of 8988 unrelated study participants (median age, 9.8 years [range, 8.9-11.0 years]; 4301 girls [47.9%]), 101 children (1.1%) and 151 children (1.7%) acknowledged lifetime use of tobacco products at baseline and at 18-month follow-up, respectively. After accounting for various suicide risk factors and potential confounders, children reporting use of tobacco products were at a 3 to 5 times increased risk of SAs (baseline: n = 153 [adjusted odds ratio (OR), 4.67; 95% CI, 2.35-9.28; false discovery rate (FDR)-corrected P < .001]; year 1: n = 227 [adjusted OR, 4.25; 95% CI, 2.33-7.74; FDR-corrected P < .001]; and year 2: n = 321 [adjusted OR, 2.85; 95% CI, 1.58-5.13; FDR-corrected P = .001]). Of all facets of impulsivity measures that were significant correlates of use of tobacco products, negative urgency was the only independent risk factor for SAs (adjusted OR, 1.52 [95% CI, 1.31-1.78]; FDR-corrected P < .001). In contrast, children's alcohol, cannabis, and prescription drug use were not associated with SAs. Conclusions and Relevance: This study of US children suggests that the increased risk of SAs, consistently reported for adolescents and adults who smoke cigarettes, extends to a range of emerging tobacco products and manifests among elementary school-aged children. Further investigations are imperative to clarify the underlying mechanisms and to implement effective preventive policies for children.

Data-driven connectivity profiles relate to smoking cessation outcomes.

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

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.

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

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

Enhanced decision-making in nicotine dependent individuals who abstain: A computational analysis using Hierarchical Drift Diffusion Modeling.

BACKGROUND: Variability in decision-making capacity and reward responsiveness may underlie differences in the ability to abstain from smoking. Computational modeling of choice behavior, as with the Hierarchical Drift Diffusion Model (HDDM), can help dissociate reward responsiveness from underlying components of decision-making. Here we used the HDDM to identify which decision-making or reward-related parameters, extracted from data acquired in a reward processing task, contributed to the ability of people who smoke that are not seeking treatment to abstain from cigarettes during a laboratory task. METHODS: 80 adults who smoke cigarettes completed the Probabilistic Reward Task (PRT) - a signal detection task with a differential reinforcement schedule - following smoking as usual, and the Relapse Analogue Task (RAT) - a task in which participants could earn money for delaying smoking up to 50min - after a period of overnight abstinence. Two cohorts were defined by the RAT; those who waited either 0-min (n=36) or the full 50-min (n=44) before smoking. RESULTS: PRT signal detection metrics indicated all subjects learned the task contingencies, with no differences in response bias or discriminability between the two groups. However, HDDM analyses indicated faster drift rates in 50-min vs. 0-min waiters. CONCLUSIONS: Relative to those who did not abstain, computational modeling indicated that people who abstained from smoking for 50min showed faster evidence accumulation during reward-based decision-making. These results highlight the importance of decision-making mechanisms to smoking abstinence, and suggest that focusing on the evidence accumulation process may yield new targets for treatment.

Evidence for Schizophrenia-Specific Pathophysiology of Nicotine Dependence.

Tobacco use is the top preventable cause of early mortality in schizophrenia. Over 60% of people with schizophrenia smoke, three times the general prevalence. The biological basis of this increased risk is not understood, and existing interventions do not target schizophrenia-specific pathology. We therefore used a connectome-wide analysis to identify schizophrenia-specific circuits of nicotine addiction. We reanalyzed data from two studies: In Cohort 1, 35 smokers (18 schizophrenia, 17 control) underwent resting-state fMRI and clinical characterization. A multivariate pattern analysis of whole-connectome data was used to identify the strongest links between cigarette use and functional connectivity. In Cohort 2, 12 schizophrenia participants and 12 controls were enrolled in a randomized, controlled crossover study of nicotine patch with resting-state fMRI. We correlated change in network functional connectivity with nicotine dose. In Cohort 1, the strongest (p < 0.001) correlate between connectivity and cigarette use was driven by individual variation in default mode network (DMN) topography. In individuals with greater daily cigarette consumption, we observed a pathological expansion of the DMN territory into the identified parieto-occipital region, while in individuals with lower daily cigarette consumption, this region was external to the DMN. This effect was entirely driven by schizophrenia participants. Given the relationship between DMN topography and nicotine use we observed in Cohort 1, we sought to directly test the impact of nicotine on this network using an independent second cohort. In Cohort 2, nicotine reduced DMN connectivity in a dose-dependent manner (R = -0.50; 95% CI -0.75 to -0.12, p < 0.05). In the placebo condition, schizophrenia subjects had hyperconnectivity compared to controls (p < 0.05). Nicotine administration normalized DMN hyperconnectivity in schizophrenia. We here provide direct evidence that the biological basis of nicotine dependence is different in schizophrenia and in non-schizophrenia populations. Our results suggest the high prevalence of nicotine use in schizophrenia may be an attempt to correct a network deficit known to interfere with cognition.

Nicotine acutely alters temporal properties of resting brain states.

BACKGROUND: Nicotine-dependent individuals have altered activity in neurocognitive networks such as the default mode (DMN), salience (SN) and central executive networks (CEN). One theory suggests that, among chronic tobacco smokers, nicotine abstinence drives more DMN-related internal processing while nicotine replacement suppresses DMN and enhances SN and CEN. Whether acute nicotine impacts network dynamics in non-smokers is, however, unknown. METHODS: In a randomized double-blind crossover study, 17 healthy non-smokers (8 females) were administered placebo and nicotine (2-mg lozenge) on two different days prior to collecting resting-state functional magnetic resonance imaging (fMRI). Previously defined brain states in 462 individuals that spatially overlap with well-characterized resting-state networks including the DMN, SN, and CEN were applied to compute state-specific dynamics at rest: total time spent in state, persistence in each state after entry, and frequency of state transitions. We examined whether nicotine acutely alters these resting-state dynamics. RESULTS: A significant drug-by-state interaction emerged; post-hoc analyses clarified that, relative to placebo, nicotine suppressed time spent in a frontoinsular-DMN state (posterior cingulate cortex, medial prefrontal cortex, anterior insula, striatum and orbitofrontal cortex) and enhanced time spent in a SN state (anterior cingulate cortex and insula). No significant findings were observed for persistence and frequency. CONCLUSIONS: In non-smokers, nicotine biases resting-state brain function away from the frontoinsular-DMN and toward the SN, which may reduce internally focused cognition and enhance salience processing. While past work suggests nicotine impacts DMN activity, the current work shows nicotinic influences on a specific DMN-like network that has been linked with rumination and depression.

Smoking-induced craving relief relates to increased DLPFC-striatal coupling in nicotine-dependent women.

BACKGROUND: Craving is a major contributor to drug-seeking and relapse. Although the ventral striatum (VS) is a primary neural correlate of craving, strategies aimed at manipulating VS function have not resulted in efficacious treatments. This incongruity may be because the VS does not influence craving in isolation. Instead, craving is likely mediated by communication between the VS and other neural substrates. Thus, we examined how striatal functional connectivity (FC) with key nodes of networks involved in addiction affects relief of craving, which is an important step in identifying viable treatment targets. METHODS: Twenty-four nicotine-dependent non-abstinent women completed two resting-state (rs) fMRI scans, one before and one following smoking a cigarette in the scanner, and provided craving ratings before and after smoking the cigarette. A seed-based approach was used to examine rsFC between the VS, putamen and germane craving-related brain regions; the dorsolateral prefrontal cortex (dlPFC), the posterior cingulate cortex, and the anterior ventral insula. RESULTS: Smoking a cigarette was associated with a decrease in craving. Relief of craving correlated with increases in right dlPFC- bilateral VS (r = 0.57, p = 0.003, corrected) as did increased right dlPFC-left putamen coupling (r = 0.62, p = 0.001, corrected). CONCLUSIONS: Smoking-induced relief of craving is associated with enhanced rsFC between the dlPFC, a region that plays a pivotal role in decision making, and the striatum, the neural structure underlying motivated behavior. These findings are highly consistent with a burgeoning literature implicating dlPFC-striatal interactions as a neurobiological substrate of craving.

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.

Caudate reactivity to smoking cues is associated with increased responding to monetary reward in nicotine-dependent individuals.

Quitting smoking is challenging in part because environmental smoking cues can trigger the desire to smoke. Neurobiological responses to smoking cues are often observed in reward-related brain regions such as the caudate and nucleus accumbens (NAc). While reward plays a well-established role in the formation of cue reactivity, whether general reward responsiveness contributes to individual differences in cue-reactivity among chronic smokers is unclear; establishing such link could provide insight into the mechanisms maintaining cue reactivity. The current study explored this relationship by assessing smoking cue reactivity during functional magnetic imaging followed by an out-of-scanner probabilistic reward task (PRT) in 24 nicotine-dependent smokers (14 women). In addition, owing to sex differences in cue reactivity and reward function, this same relationship was examined as a function of sex. Following recent smoking, greater reward responsiveness on the PRT was associated with enhanced left caudate reactivity to smoking cues. No relationship was found in any other striatal subregion. The positive relationship between reward responsiveness and caudate smoking cue reactivity was significant only in male smokers, fitting with the idea that males and females respond to the reinforcing elements of smoking cues differently. These findings are clinically relevant as they show that, following recent smoking, nicotine-dependent individuals who are more cue reactive are also more likely to be responsive to non-drug rewards, which may be useful for making individualized treatment decisions that involve behavioral reward contingencies.

Clinical Correlates of Smoking Status in Men and Women with Opioid Use Disorder.

Background: Smoking is highly prevalent in people with opioid use disorder (OUD) and is a significant contributor to morbidity and mortality in this population. However, little is known about the differences between those with OUD who do and do not smoke cigarettes. Objectives: Our aim was to investigate differences between treatment-seeking adults with OUD who did and did not smoke. Methods: Participants (N = 568; 30% female) completed a battery of self-report questionnaires including measures of current smoking status and number of cigarettes smoked per day as well as measures of clinical characteristics (e.g. craving, anxiety). Results: Of the total sample, 77% were current smokers. Multivariable logistic regression identified heroin use (OR = 2.20, 95% CI = 1.38, 3.53) and younger age (OR = 0.97, 95% CI = 0.95, 0.997) as strong correlates of smoking status; other characteristics were not significant. Older age and opioid craving were associated with more cigarettes smoked per day. Notably, these patterns differed for males and females; opioid craving (B = 0.62, SEB = 0.24) was associated with the number of cigarettes smoked among men, and anxiety (B = 0.39, SEB = 0.19) was associated with the number of cigarettes smoked among women. Conclusion: Adults with OUD who used heroin in the past month were more likely to be current smokers. No sex differences were observed in likelihood of smoking; however, the predictors of smoking status and severity differed between men and women.

The acute effects of nicotine on corticostriatal responses to distinct phases of reward processing.

Nicotine enhances the reinforcement of non-drug rewards by increasing nucleus accumbens (NAcc) reactivity to anticipatory cues. This anticipatory effect is selective as no clear evidence has emerged showing that nicotine acutely changes reward receipt reactivity. However, repeated rewarding experiences shift peak brain reactivity from hedonic reward outcome to the motivational anticipatory cue yielding more habitual cue-induced behavior. Given nicotine's influence on NAcc reactivity and connectivity, it is plausible that nicotine acutely induces this shift and alters NAcc functional connectivity during reward processing. To evaluate this currently untested hypothesis, a randomized crossover design was used in which healthy non-smokers were administered placebo and nicotine (2-mg lozenge). Brain activation to monetary reward anticipation and outcome was evaluated with functional magnetic resonance imaging. Relative to placebo, nicotine induced more NAcc reactivity to reward anticipation. Greater NAcc activation during anticipation was significantly associated with lower NAcc activation to outcome. During outcome, nicotine reduced NAcc functional connectivity with cortical regions including the anterior cingulate cortex, orbitofrontal cortex, and insula. These regions showed the same negative relationship between reward anticipation and outcome as noted in the NAcc. The current findings significantly improve our understanding of how nicotine changes corticostriatal circuit function and communication during distinct phases of reward processing and critically show that these alterations happen acutely following a single dose. The implications of this work explain nicotinic modulation of general reward function, which offer insights into the initial drive to smoke and the subsequent difficulty in cessation.

Craving and Cue Reactivity in Nicotine-Dependent Tobacco Smokers Is Associated With Different Insula Networks.

BACKGROUND: The insula has a well-established role in nicotine dependence and is a node of the salience network, which integrates internal and external information to guide behavior. Recent findings reveal that internal and external processing occurs in the ventral anterior insula (vAI) and dorsal anterior insula (dAI), respectively. Whether vAI/dAI network connectivity differentially reflects internally generated craving and externally triggered smoking cue reactivity was tested. METHODS: Thirty-six male and female nicotine-dependent individuals smoked 1 hour before functional magnetic resonance imaging. Baseline craving was measured, followed by resting-state and smoking cue reactivity scans and then another assessment of craving. Craving and cue reactivity interactions were measured by focusing on specific nodes of the salience network: the vAI/dAI and anterior cingulate cortex. RESULTS: Resting-state vAI/dAI networks overlapped with the prototypical salience network, yet they possessed distinct patterns, linking the vAI with nodes of the internally focused default mode network and the dAI with nodes of the external, goal-related frontoparietal network. Internally generated baseline craving was associated with enhanced vAI connectivity, whereas rostral anterior cingulate cortex reactivity to external smoking cues was associated with greater dAI connectivity. We also found that cue reactivity in the rostral anterior cingulate cortex was associated with a rise in subjective cue-induced craving, whereas baseline subjective craving did not influence brain cue reactivity. CONCLUSIONS: These data show that brain reactivity to smoking cues is associated with a subsequent increase in craving. In addition, separate insula networks have a role in an individual's vulnerability to internally related craving and externally triggered cue reactivity, which could guide the development of new, neurobiologically targeted therapies.

A Preliminary Examination of Nicotine-Free Electronic Cigarette Use During Cessation From Combustible Cigarettes.

Despite the availability of smoking cessation strategies, smoking cue-induced craving remains a relatively untreated relapse risk factor. Utilizing nicotine-free electronic cigarettes (e-cigarettes) to extinguish the motivational influence of smoking cues may be a viable approach to address cue reactivity. In this pilot study, 26 daily tobacco smokers used nicotine-free e-cigarettes while being maintained on daily transdermal sustained-release nicotine replacement therapy (NRT) to mitigate pharmacological withdrawal. Sensitivity to cue-induced craving, measured by the rise in craving after a visual cue exposure task, was assessed at a baseline visit after smoking as usual and again after 2 weeks of nicotine-free e-cigarette and NRT use. Participants' pattern and amount of tobacco cigarette smoking were evaluated on both visits and 1 month posttreatment. Cue-induced craving significantly decreased after the 2-week intervention, yet withdrawal scores increased during this time. One month after study completion, participants continued to report significantly lower overall cigarette craving and conventional tobacco cigarette use. Including the 34.8% that were totally abstinent, 65.2% reported smoking fewer than 10 cigarettes per week (compared to 87.2 per week at baseline for the entire group). A linear regression revealed that greater baseline cue-induced craving predicted better outcomes, whereas more withdrawal at the e-cigarette visit was related to more smoking at 1 month. This proof-of-concept pilot study suggests that the addition of ad libitum nicotine-free e-cigarettes to an existing strategy of transdermal NRT may attenuate cue-induced craving for tobacco smoking. A larger sample that is powered for detecting additional factors and longer-term outcomes is warranted.

Quitting starts in the brain: a randomized controlled trial of app-based mindfulness shows decreases in neural responses to smoking cues that predict reductions in smoking.

Current treatments for smoking yield suboptimal outcomes, partly because of an inability to reduce cue-induced smoking. Mindfulness training (MT) has shown preliminary efficacy for smoking cessation, yet its neurobiological target remains unknown. Our prior work with nonsmokers indicates that MT reduces posterior cingulate cortex (PCC) activity. In individuals who smoke, the PCC, consistently a main hub of the "default mode network," activates in response to smoking cues. In this randomized controlled trial, we tested the effects of app-delivered MT on PCC reactivity to smoking cues and whether individual differences in MT-mediated PCC changes predicted smoking outcomes. Smoking cue-induced PCC reactivity was measured using functional magnetic resonance imaging at baseline and 1 month after receiving smartphone app-based MT (n = 33) vs. an active control (National Cancer Institute's QuitGuide, n = 34). Whether individual differences in treatment-related changes in PCC activity predicted smoking behavior was assessed. The MT group demonstrated a significant correlation between a reduction in PCC reactivity to smoking cues and a decline in cigarette consumption (r = 0.39, p = 0.02). No association was found in the control group (r = 0.08, p = 0.65). No effects of group alone were found in PCC or cigarette reduction. Post hoc analysis revealed this association is sex specific (women, r = 0.49, p = 0.03; men: r = -0.08, p = 0.79). This initial report indicates that MT specifically reduces smoking cue-induced PCC activity in a subject-specific manner, and the reduction in PCC activity predicts a concurrent decline in smoking. These findings link the hypothesized behavioral effects of MT for smoking to neural mechanisms particularly in women. This lays the groundwork for identifying individuals who may benefit from targeted digital therapeutic treatments such as smartphone-based MT, yielding improved clinical outcomes.

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

BACKGROUND: Women experience greater difficulty quitting smoking than men, which may be explained by sex differences in brain circuitry underlying cognitive control. Prior work has linked reduced interhemispheric executive control network (ECN) coupling with poor executive function, shorter time to relapse, and greater substance use. Lower structural connectivity between a key ECN hub, the dorsolateral prefrontal cortex (DLPFC), and the dorsal striatum (DS) also contributes to less efficient cognitive control recruitment, and reduced intrahemispheric connectivity between these regions has been associated with smoking relapse. Therefore, sex differences were probed by evaluating interhemispheric ECN and intrahemispheric DLPFC-DS connectivity. To assess the potential sex by nicotine interaction, a pilot sample of non-smokers was evaluated following acute nicotine and placebo administration. METHODS: Thirty-five smokers (19 women) completed one resting state functional magnetic resonance imaging scan. Seventeen non-smokers (8 women) were scanned twice using a repeated measures design where they received 2 and 0 mg nicotine. RESULTS: In smokers, women had less interhemispheric ECN and DLPFC-DS coupling than men. In non-smokers, there was a drug x sex interaction where women, relative to men, had weaker ECN coupling following nicotine but not placebo administration. CONCLUSIONS: The current work indicates that nicotine-dependent women, versus men, have weaker connectivity in brain networks critically implicated in cognitive control. How these connectivity differences contribute to the behavioral aspects of smoking requires more testing. However, building on the literature, it is likely these deficits in functional connectivity contribute to the lower abstinence rates noted in women relative to men.

Nicotine normalizes cortico-striatal connectivity in non-smoking individuals with major depressive disorder.

Nicotine dependence and major depressive disorder (MDD) are highly comorbid, yet causal links between these prevalent disorders are unclear. One possible mechanism is that nicotine ameliorates MDD-related neurobiological dysfunction in specific networks. For instance, cortico-striatal circuitry is enhanced by nicotine, and such paths are disrupted in individuals with MDD. Specifically, MDD has been associated with reduced connectivity between the nucleus accumbens (NAc) and rostral anterior cingulate cortex (rACC) but enhanced connectivity between the dorsal striatum (DS) and dorsolateral prefrontal cortex (DLPFC). Determining whether nicotine normalizes these circuits in non-smokers with MDD may elucidate mechanisms underlying links between disorders. This was tested by administering placebo and a 2-mg dose of nicotine to unmedicated non-smokers with and without MDD prior to collecting resting-state functional magnetic imaging data using a cross-over design. On placebo, individuals with MDD showed significantly reduced NAc-rACC and a trend for enhanced DS-DLPFC functional connectivity relative to healthy controls. In MDD, acute nicotine administration normalized both pathways to the level of healthy controls, while having no impact on healthy controls. Nicotine's effects on NAc-rACC connectivity was influenced by anhedonia, consistent with the role of this network in reward and nicotine's ability to enhance reward deficiencies in MDD. These results indicate that nicotine normalizes dysfunctional cortico-striatal communication in unmedicated non-smokers with MDD. Nicotine's influence on these circuitries highlights a possible mechanism whereby individuals with MDD are more vulnerable to develop nicotine dependence. Findings suggest that nicotinic agents may have therapeutic effects on disrupted cortico-striatal connectivity.

Nicotine Increases Activation to Anticipatory Valence Cues in Anterior Insula and Striatum.

Introduction: Smoking is associated with significant morbidity and mortality. Understanding the neurobiology of the rewarding effects of nicotine promises to aid treatment development for nicotine dependence. Through its actions on mesolimbic dopaminergic systems, nicotine engenders enhanced responses to drug-related cues signaling rewards, a mechanism hypothesized to underlie the development and maintenance of nicotine addiction. Methods: We evaluated the effects of acute nicotine on neural responses to anticipatory cues signaling (nondrug) monetary reward or loss among 11 nonsmokers who had no prior history of tobacco smoking. In a double-blind, crossover design, participants completed study procedures while wearing nicotine or placebo patches at least 1 week apart. In each drug condition, participants underwent functional magnetic resonance imaging while performing the monetary incentive delay task and performed a probabilistic monetary reward task, probing reward responsiveness as measured by response bias toward a more frequently rewarded stimulus. Results: Nicotine administration was associated with enhanced activation, compared with placebo, of right fronto-anterior insular cortex and striatal regions in response to cues predicting possible rewards or losses and to dorsal anterior cingulate for rewards. Response bias toward rewarded stimuli correlated positively with insular activation to anticipatory cues. Conclusion: Nicotinic enhancement of monetary reward-related brain activation in the insula and striatum in nonsmokers dissociated acute effects of nicotine from effects on reward processing due to chronic smoking. Reward responsiveness predicted a greater nicotinic effect on insular activation to salient stimuli. Implications: Previous research demonstrates that nicotine enhances anticipatory responses to rewards in regions targeted by midbrain dopaminergic systems. The current study provides evidence that nicotine also enhances responses to rewards and losses in the anterior insula. A previous study found enhanced insular activation to rewards and losses in smokers and ex-smokers, a finding that could be due to nicotine sensitization or factors related to current or past smoking. Our finding of enhanced anterior insula response after acute administration of nicotine in nonsmokers provides support for nicotine-induced sensitization of insular response to rewards and losses.

Nicotine-induced activation of caudate and anterior cingulate cortex in response to errors in schizophrenia.

BACKGROUND: Nicotine improves attention and processing speed in individuals with schizophrenia. Few studies have investigated the effects of nicotine on cognitive control. Prior functional magnetic resonance imaging (fMRI) research demonstrates blunted activation of dorsal anterior cingulate cortex (dACC) and rostral anterior cingulate cortex (rACC) in response to error and decreased post-error slowing in schizophrenia. METHODS: Participants with schizophrenia (n = 13) and healthy controls (n = 12) participated in a randomized, placebo-controlled, crossover study of the effects of transdermal nicotine on cognitive control. For each drug condition, participants underwent fMRI while performing the stop signal task where participants attempt to inhibit prepotent responses to "go (motor activation)" signals when an occasional "stop (motor inhibition)" signal appears. Error processing was evaluated by comparing "stop error" trials (failed response inhibition) to "go" trials. Resting-state fMRI data were collected prior to the task. RESULTS: Participants with schizophrenia had increased nicotine-induced activation of right caudate in response to errors compared to controls (DRUG × GROUP effect: p corrected < 0.05). Both groups had significant nicotine-induced activation of dACC and rACC in response to errors. Using right caudate activation to errors as a seed for resting-state functional connectivity analysis, relative to controls, participants with schizophrenia had significantly decreased connectivity between the right caudate and dACC/bilateral dorsolateral prefrontal cortices. CONCLUSIONS: In sum, we replicated prior findings of decreased post-error slowing in schizophrenia and found that nicotine was associated with more adaptive (i.e., increased) post-error reaction time (RT). This proof-of-concept pilot study suggests a role for nicotinic agents in targeting cognitive control deficits in schizophrenia.

Neural Responses to Smoking Cues in Schizophrenia.

The high prevalence of nicotine dependence contributes to excess mortality in schizophrenia. Cue reactivity, or the encounter of drug-related cues or contexts, triggers craving, drug-seeking, and relapse. Prior functional magnetic resonance imaging (fMRI) research indicates that individuals with schizophrenia have blunted neural responses to rewarding stimuli in association with more severe negative symptoms. The objectives of this study are to determine if smokers with schizophrenia have altered neural reactivity to smoking cues compared with non-psychiatrically ill smokers and to evaluate the influence of negative symptoms on cue reactivity. Twenty smokers with schizophrenia and 19 control smokers underwent fMRI while viewing smoking-related and neutral cues. The primary analysis was group comparison of Smoking-Neutral contrast using whole-brain analysis (Pcorrected < .05). Smokers with schizophrenia had significantly greater baseline carbon monoxide levels and longer duration of smoking, suggesting more nicotine use. While both groups had greater brain reactivity to smoking vs neutral cues, smokers with schizophrenia had significantly decreased cue reactivity (Smoking-Neutral) compared to controls in bilateral frontal midline regions. There were significant negative correlations between negative symptoms and frontal midline reactivity. Despite greater nicotine use, smokers with schizophrenia exhibited decreased smoking cue-induced neural reactivity in frontal midline regions, suggesting that increased smoking and low cessation rates in schizophrenia are not primarily driven by responses to smoking-related cues. The finding of negative correlations between cue reactivity and negative symptoms is consistent with previous research demonstrating decreased neural responses to rewarding cues, particularly in patients with negative symptoms.