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

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.

Context matters: Neural processing of food-flavored e-cigarettes and the influence of smoking

E-cigarettes are harmful, addictive, and popular. In e-cigarettes, nicotine is often paired with food-flavors. How this pairing of nicotine and food cues influences neural processing warrants investigation, as in smokers, both types of cues activate similar brain regions. Additionally, while most e-cigarettes are sweet, savory e-cigarettes are seemingly absent, although savory flavors are commonly liked in food. To understand how smoking status and type of flavor modulate reactions to food-flavored e-cigarettes, in comparison to actual food, neural and subjective responses to food odors were measured in a 2 (sweet vs. savory odor) x2 (food vs. e-cigarette context) x2 (smokers vs. non-smokers) design in 22 occasional/light smokers and 25 non-smokers. During fMRI scanning, participants were exposed to sweet and savory odors and pictures creating the two contexts. Liking and wanting were repeatedly measured on a 100-unit visual-analogue-scale. Results show that sweet e-cigarettes were liked (Δ = 14.2 ± 1.7) and wanted (Δ = 39.5 ± 3.1) more than savory e-cigarettes, and their cues activated the anterior cingulate more (cluster-level qFDR = 0.003). Further, we observed context-dependent variations in insula response to odors (cluster-level qFDR = 0.023, and = 0.030). Savory odors in an e-cigarette context were wanted less than the same odors in a food-context (Δ = 32.8 ± 3.1). Smokers and non-smokers reacted similarly to flavored product cues. Our results indicate that the principles of flavor preference in food cannot directly be applied to e-cigarettes and that it is challenging to design sweet and savory e-cigarettes to appeal to smokers only.

Anhedonia in Nicotine Dependence

Prior findings indicate that trait anhedonia enhances the likelihood of becoming a tobacco smoker, and preliminary evidence suggests that smoking abstinence leads to anhedonic states in some individuals and situations, and nicotine administration reduces anhedonic states. Nevertheless, many vital questions exist concerning relationships between anhedonia and nicotine dependence, including situational and individual difference factors that may moderate the strength of these associations. This chapter provides a critical review of the literature assessing relationships of anhedonia to nicotine dependence and the effects of acute nicotine through the lenses of the Research Domain Criteria's (RDoC) Positive Valence Systems (NIMH, RDoC changes to the matrix (CMAT) workgroup update: proposed positive valence domain revisions. A report by the national advisory mental health council workgroup on changes to the research domain criteria matrix, 2018) and the Situation x Trait Affective Response (STAR) model of nicotine's effects and nicotine dependence (Gilbert, Smoking individual differences, psychopathology, and emotion. Taylor and Francis, Washington, DC, 1995; Gilbert, Hum Psychopharmacol Clin Exp 12:S89-S102, 1997). The effects of nicotine and nicotine withdrawal on subjective, behavioral, and brain indices vary across the three RDoC Positive Valences Systems (Reward Responsiveness, Reward Learning, and Reward Valuation) in a manner that supports the research and potential clinical utility of using RDoC criteria and the STAR model to guide research and clinical innovation. We provide a revision of the STAR model that incorporates the three RDoC Positive Valence Systems with evidence that nicotine's effects on hedonic and affective processes vary as a function of the dominance/salience of (1) situational hedonic and affective cues and task/active coping cues, and (2) state executive functioning level/capacity and state reward sensitivity such that these effects of nicotine are maximal during states of suboptimal cognitive functioning and reward sensitivity, combined with low situational stimulus salience and low task-related cues/demands.

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.

Transdiagnostic neuroimaging of reward system phenotypes in ADHD and comorbid disorders

ADHD is a disorder characterized by changes in the reward system and which is highly comorbid with other mental disorders, suggesting common neurobiological pathways. Transdiagnostic neuroimaging findings could help to understand whether a dysregulated reward pathway might be the actual link between ADHD and its comorbidities. We here synthesize ADHD neuroimaging findings on the reward system with findings in obesity, depression, and substance use disorder including their comorbid appearance regarding neuroanatomical features (structural MRI) and activation patterns (resting-state and functional MRI). We focus on findings from monetary-incentive-delay (MID) and delay-discounting (DD) tasks and then review data on striatal connectivity and volumetry. Next, for better understanding of comorbidity in adult ADHD, we discuss these neuroimaging features in ADHD, obesity, depression and substance use disorder and ask whether ADHD heterogeneity and comorbidity are reflected by a common dysregulation in the reward system. Finally, we highlight conceptual issues related to heterogeneous paradigms, different phenotyping, longitudinal prediction and highlight some promising future directions for using striatal reward functioning as a clinical biomarker.

Subtypes of inhibitory and reward activation associated with substance use variation in adolescence: A latent profile analysis of brain imaging data

The present study identified subgroups based on inhibitory and reward activation, two key neural functions involved in risk-taking behavior, and then tested the extent to which subgroup differences varied by age, sex, behavioral and familial risk, and substance use. Participants were 145 young adults (18-21 years old; 40.0% female) from the Michigan Longitudinal Study. Latent profile analysis (LPA) was used to establish subgroups using task-based brain activations. Demographic and substance use differences between subgroups were then examined in logistic regression analyses. Whole-brain task activations during a functional magnetic resonance imaging go/no-go task and monetary incentive delay task were used to identify beta weights as input for LPA modeling. A four-class model showed the best fit with the data. Subgroups were categorized as: (1) low inhibitory activation/moderate reward activation (39.7%), (2) moderate inhibitory activation/low reward activation (22.7%), (3) moderate inhibitory activation/high reward activation (25.2%), and (4) high inhibitory activation/high reward activation (12.4%). Compared with the other subgroups, Class 2 was older, less likely to have parental alcohol use disorder, and had less alcohol use. Class 4 was the youngest and had greater marijuana use. Classes 1 and 3 did not differ significantly from the other subgroups. These findings demonstrate that LPA applied to brain activations can be used to identify distinct neural profiles that may explain heterogeneity in substance use outcomes and may inform more targeted substance use prevention and intervention efforts.

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.

Multidimensional Intersection of Nicotine, Gene Expression, and Behavior

The cholinergic system plays a crucial role in nervous system function with important effects on developmental processes, cognition, attention, motivation, reward, learning, and memory. Nicotine, the reinforcing component of tobacco and e-cigarettes, directly acts on the cholinergic system by targeting nicotinic acetylcholine receptors (nAChRs) in the brain. Activation of nAChRs leads to a multitude of immediate and long-lasting effects in specific cellular populations, thereby affecting the addictive properties of the drug. In addition to the direct actions of nicotine in binding to and opening nAChRs, the subsequent activation of circuits and downstream signaling cascades leads to a wide range of changes in gene expression, which can subsequently alter further behavioral expression. In this review, we provide an overview of the actions of nicotine that lead to changes in gene expression and further highlight evidence supporting how these changes can often be bidirectional, thereby inducing subsequent changes in behaviors associated with further drug intake.