Brain Network Dynamics Study for Smoking Relapse Prevention

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Penn State University

Disqualifiers: Pacemakers, Metallic objects, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

150 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to understand why people who try to quit smoking often start again, focusing on the brain's activity leading up to a smoking lapse (a slip back into smoking). Researchers will use fMRI (a type of brain scan) to observe changes in brain patterns just before someone smokes during a quit attempt. The study includes a laboratory task that models smoking lapse behavior to simulate real-life situations. Individuals who smoke at least six cigarettes daily and have done so for the past year might be a good fit for this study. As an unphased study, this trial offers a unique opportunity to contribute to groundbreaking research on smoking cessation.

Do I have to stop taking my current medications for the trial?

The trial protocol does not specify whether you need to stop taking your current medications. However, you must refrain from using nicotine for 12 hours before the lab visit.

What prior data suggests that this fMRI method is safe for studying smoking lapse behavior?

Research shows that the fMRI smoking lapse task is generally safe for participants. fMRI, or functional magnetic resonance imaging, is a common tool used to observe brain activity. It is non-invasive, meaning it doesn't involve surgery or entering the body.

Studies have found that most people handle fMRI well, and it doesn't cause any long-term effects. Some participants might feel a bit uncomfortable during the scan because they need to lie still inside a machine. The machine can also be noisy, but this is normal for fMRI scans. These issues are temporary and usually not serious.

Overall, the fMRI smoking lapse task employs methods widely used in research, with safety records indicating they are safe for people. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores how brain activity can predict and potentially prevent smoking relapses. Unlike traditional methods that focus on behavioral therapy or medication, this approach uses an fMRI smoking lapse task to study brain network dynamics. The hope is that by understanding how the brain responds during moments of potential relapse, more personalized and effective interventions can be developed. This method could pave the way for innovative strategies that target the neural underpinnings of addiction, offering new hope for those trying to quit smoking.

What evidence suggests that this fMRI smoking lapse task is effective for preventing smoking relapse?

This trial will use an fMRI smoking lapse task to study brain activity related to smoking relapses. Research has shown that fMRI, a type of brain scan, can reveal brain patterns that appear just before a person smokes again. By examining these patterns, researchers aim to discover why individuals resume smoking after attempting to quit. Understanding these brain signals might lead to better relapse prevention methods. Early findings suggest this method could be a promising tool to help people quit smoking by targeting specific brain activities. ^{1 3 6 7 8}

Are You a Good Fit for This Trial?

This trial is for smokers aged 21-65 who have smoked at least six cigarettes daily over the past year and can speak English fluently. They must pass an MRI safety screening and show a carbon monoxide level above 10 ppm to confirm smoking status. Those unwilling to abstain from nicotine for 12 hours before lab visits or with risks related to MRIs, like pacemakers or metallic objects in their body, cannot join.

Inclusion Criteria

I am between 21 and 65 years old.

Participants must be fluent English speakers

Participants must pass an MRI safety screening

Exclusion Criteria

Individuals will be excluded if they report that they are not willing to refrain from using nicotine for 12 hours before the experimental lab visit

Individuals will be excluded if they have any known risk from exposure to high-field strength magnetic fields (e.g., pacemakers), any irremovable metallic foreign objects in their body (e.g., braces), or a questionable history of metallic fragments that are likely to create artifact on the MRI scans

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Pre-Scan Abstinence

Participants abstain from cigarettes for 12 hours before completing the fMRI lapse paradigm

12 hours

fMRI Lapse Paradigm

Participants undergo an fMRI scan to measure brain activity during a lapse task, including an in-scanner delay period and a post-scan ad-lib period

1 day

1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after the fMRI task

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Laboratory task modeling smoking lapse behavior

Trial Overview The study uses fMRI scans while participants perform tasks that simulate situations leading to a smoking lapse. It aims to identify brain activity patterns linked to the urge of smoking and understand mental processes preceding a lapse, which could help prevent relapses.

How Is the Trial Designed?

Group I: fMRI smoking lapse task Experimental Treatment 1 Intervention

Who Is Running the Clinical Trial?

Penn State University

Lead Sponsor

Trials

380

Recruited

131,000+

Published Research Related to This Trial

In a study of 21 nicotine-dependent women, those who were more likely to relapse after a quit attempt showed increased brain reactivity to smoking-related images, particularly in areas associated with emotion and motor planning, indicating a heightened vulnerability to relapse.

The research found that fMRI and attentional bias measurements could predict relapse outcomes with 79% accuracy, suggesting that these methods could help identify smokers at risk before they attempt to quit, allowing for more personalized and effective treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Brain reactivity to smoking cues prior to smoking cessation predicts ability to maintain tobacco abstinence. Janes, AC., Pizzagalli, DA., Richardt, S., et al.[2022]

In a study of 144 individuals with nicotine use disorder (NUD), higher functional network connectivity (FNC) between the insula and dorsal anterior cingulate cortex (dACC) was associated with lower baseline smoking levels, suggesting a potential biomarker for nicotine dependence.

However, higher FNC between certain brain regions (putamen and dACC, caudate and dACC, caudate and dorsolateral prefrontal cortex) predicted worse treatment outcomes, particularly in participants experiencing high withdrawal symptoms, indicating that brain connectivity may influence treatment efficacy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Functional network connectivity predicts treatment outcome during treatment of nicotine use disorder. Wilcox, CE., Calhoun, VD., Rachakonda, S., et al.[2019]

A study using functional MRI on 38 nicotine-deprived smokers found that those who successfully resisted smoking after exposure to cigarette cues showed significant functional connectivity between the left anterior insula and the dorsolateral prefrontal cortex.

This research highlights the importance of brain connectivity patterns over mere activation levels in understanding why some smokers can resist the urge to smoke during the critical first 24 hours of quitting.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The first day is always the hardest: Functional connectivity during cue exposure and the ability to resist smoking in the initial hours of a quit attempt. Zelle, SL., Gates, KM., Fiez, JA., et al.[2018]

A study using male Sprague Dawley rats identified that differences in brain connectivity, particularly in an insular-frontal module, can predict the severity of nicotine dependence after exposure to nicotine, suggesting that these brain network characteristics may serve as biomarkers for addiction risk.

The research highlights the importance of understanding individual differences in brain circuitry before drug exposure, which could lead to targeted interventions to prevent nicotine dependence in susceptible individuals.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Intrinsic Insular-Frontal Networks Predict Future Nicotine Dependence Severity. Hsu, LM., Keeley, RJ., Liang, X., et al.[2020]

In a study of 125 participants, smokers showed increased thalamic volume compared to nonsmokers, with relapsers having even greater volume than nonrelapsers, suggesting structural changes in the thalamus may be linked to smoking relapse.

Decreased resting state functional connectivity between the thalamus and precuneus was found in relapsers, and both thalamic volume and connectivity measures could predict smoking relapse with 75.7% accuracy, indicating their potential as biomarkers for personalized treatment in nicotine addiction.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Increased thalamic volume and decreased thalamo-precuneus functional connectivity are associated with smoking relapse. Wang, C., Wang, S., Shen, Z., et al.[2021]

A study involving 57 smokers used resting-state fMRI to identify brain connectivity differences between those who relapsed after quitting and those who successfully abstained, revealing that relapsers had increased functional connectivity in key brain areas like the dorsolateral prefrontal cortex (DLPFC).

The findings suggest that by analyzing brain connectivity patterns, it is possible to predict relapse vulnerability with 80.7% accuracy, which could lead to more personalized and effective smoking cessation treatments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Increased network centrality as markers of relapse risk in nicotine-dependent individuals treated with varenicline. Shen, Z., Huang, P., Wang, C., et al.[2018]

In a study of smokers undergoing treatment with varenicline, differences in spontaneous brain activity were observed between those who successfully quit smoking and those who relapsed, suggesting that brain function may influence cessation outcomes.

Specifically, relapsers showed decreased spontaneous brain activity in the posterior cingulate cortex and increased activity in the superior temporal gyrus, indicating that these brain regions could be potential predictors of smoking relapse.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Altered spontaneous activity of posterior cingulate cortex and superior temporal gyrus are associated with a smoking cessation treatment outcome using varenicline revealed by regional homogeneity. Wang, C., Shen, Z., Huang, P., et al.[2018]

A study involving 17 daily smokers used fMRI to explore how brain systems related to cognitive control affect the ability to resist smoking after 12 hours of abstinence.

Findings suggest that when the default mode system and frontoparietal system are less segregated, it may weaken a person's ability to resist the urge to smoke, highlighting the importance of brain activity patterns in smoking lapse behavior.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The feasibility of an in-scanner smoking lapse paradigm to examine the neural correlates of lapses. Lydon-Staley, DM., MacLean, RR., Falk, EB., et al.[2023]

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT05572671

Linking Brain Network Dynamics to Imminent Smoking ... Functional magnetic resonance imaging (fMRI) is a promising method for characterizing the psychological processes that lead to smoking lapses because it ...

2. withpower.com withpower.com/trial/phase-smoking-11-2022-1b99f

Brain Network Dynamics Study for Smoking Relapse ... The studies focus on functional connectivity and brain activity related to smoking relapse and cessation, using fMRI to identify neural patterns associated with ...

3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11950297/

Regulation of craving and underlying resting-state neural ... This laboratory study examined associations between regulation of craving (ROC) efficacy and smoking lapse, utilized functional connectivity multivariate ...

4. wilsonlab.la.psu.edu wilsonlab.la.psu.edu/linking-brain-dynamics/

Linking Brain Network Dynamics to Smoking-Related Behavior Thus, characterizing why lapses occur is essential to understanding and preventing smoking relapse. Functional magnetic resonance imaging (fMRI) is a promising ...

5. link.springer.com link.springer.com/article/10.3758/s13415-023-01070-y

Testing the efficacy of real-time fMRI neurofeedback for ... The current proof-of-concept study tested if real-time fMRI neurofeedback training augments the ability to upregulate responses in reward-related brain areas.

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC3742373/

Brain fMRI Responses to Smoking-Related Images Prior to ... These data suggest that during extended smoking abstinence, fMRI reactivity to smoking versus neutral stimuli persists in brain areas involved in attention.

7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC2732001/

Developing human laboratory models of smoking lapse ... This paper outlines a three-stage process for the development of a smoking lapse model for the purpose of medication screening.

8. karger.com karger.com/ear/article/doi/10.1159/000546112/926189/Changes-in-inhibition-related-brain-function-and?searchresult=1

Changes in Inhibition-Related Brain Function and ... The overall aim of this study – to identify, and validate through a holdout set, brain and behavioral predictors of smoking relapse – was ...