Grant Number:	5R21CA190093-02 Interpret this number
Primary Investigator:	Wilson, Stephen
Organization:	Pennsylvania State University, The
Project Title:	(PQA1) Fmri Neurofeedback and Descision-Making in Habitual Cigarette Smokers
Fiscal Year:	2015

DESCRIPTION (provided by applicant): Cigarette smoking is the leading preventable cause of cancer in the United States. Helping smokers quit thus is one of the most effective means for reducing cancer burden in this country. Because most smokers find it incredibly difficult to stop smoking, enhancing the motivation to remain abstinent from cigarettes is widely seen as an essential step for improving their chances of success. Attempting to motivate quitting smokers to remain abstinent using nondrug rewards (e.g., money) is a particularly common intervention strategy. Although the use of nondrug rewards to aide quitting smokers is grounded in sound behavioral principles, mounting evidence indicates that nondrug rewards may be the least effective at reinforcing abstinence precisely when they are needed most (i.e., when smokers are tempted by an opportunity to smoke). Namely, simply anticipating having access to cigarettes in the near future appears to dampen the response to nondrug rewards in brain regions supporting reward valuation and motivational processing. This blunting is associated with a corresponding decrease in the willingness to resist smoking for a nondrug incentive, thus directly undermining the effectiveness of reward-based approaches to promoting cigarette abstinence. The proposed research addresses RFA-CA-13-017 (PQA1): Research Answers to NCI's Provocative Questions-Group A (PQA1) by testing the novel hypothesis that increasing brain responses to nondrug rewards may be an effective way to enhance the influence that such stimuli have on behavior in smokers. We propose to examine this idea using a technique called real-time functional magnetic resonance imaging (fMRI) neurofeedback. Real-time fMRI neurofeedback is a type of biofeedback that involves training individuals to control brain responses by presenting them with information about ongoing brain activity. Daily smokers (n=90) will be randomly assigned to three groups (intervention, sham neurofeedback control, and no feedback control; n=30 each). Those in the intervention group will receive valid real-time fMRI neurofeedback aimed at training them to volitionally increase activity in brain reward regions. The control groups will undergo nearly identical procedures but receive sham [placebo] neurofeedback and no neurofeedback, respectively. We hypothesize that only smokers provided with valid neurofeedback will learn to reliably and voluntarily increase activation in reward-related brain regions using cognitive strategies (Aim 1). We predict that this learning will be durable, such tha smokers will be able to continue using cognitive strategies to increase reward-related brain activity after neurofeedback is removed (Aim 2). We also predict that this learning will be functional, such that clinically-relevant decision making (the willingness to choose a nondrug reward over smoking) is influenced when smokers use the same strategies outside of the scanner (Aim 3). If successful, the proposed study will open new avenues for using neurofeedback to expedite scientific discovery and facilitate the development of effective smoking interventions that can be used by smokers on a broad scale.




Testing the efficacy of real-time fMRI neurofeedback for training people who smoke daily to upregulate neural responses to nondrug rewards.
Authors: Chung Y.I. , White R. , Geier C.F. , Johnston S.J. , Smyth J.M. , Delgado M.R. , McKee S.A. , Wilson S.J. .
Source: Cognitive, Affective & Behavioral Neuroscience, 2023 Apr; 23(2), p. 440-456.
EPub date: 2023-02-14 00:00:00.0.
PMID: 36788202
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Effects Of Cognitive Load On Neural And Behavioral Responses To Smoking-cue Distractors
Authors: MacLean R.R. , Nichols T.T. , LeBreton J.M. , Wilson S.J. .
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PMID: 27012714
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EPub date: 2016-04-11 00:00:00.0.
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