Linking Brain Network Dynamics to Imminent Smoking Lapse Risk and Behavior

Launched by PENN STATE UNIVERSITY · Oct 5, 2022

Keywords

ClinConnect Summary

This clinical trial is studying why some people who are trying to quit smoking end up using cigarettes again, specifically looking at what happens in the brain just before a lapse, or a moment when someone gives in and smokes a cigarette. Researchers will use a special type of brain imaging called fMRI to see how brain activity changes during these critical moments. By understanding these changes, the study aims to help find better ways to support people in quitting smoking for good.

To participate in this trial, individuals must be between 21 and 65 years old, speak English fluently, and have been smoking at least six cigarettes a day for the past year. They will need to undergo a safety screening for the MRI and must be willing to refrain from using nicotine for 12 hours before their visit. Participants will have the chance to contribute to important research that could lead to improved smoking cessation strategies, helping many others in their journey to quit smoking.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Participants must be between the ages of 21 and 65.
• • Participants must be fluent English speakers.
• • Participants must pass an MRI safety screening.
• • Participants must report smoking at least six cigarettes per day continuously for at least the 12 preceding months.
• • Participants must have a baseline expired-air carbon monoxide exceeding 10 parts per million in order to verify smoking status.
• 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.