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. 2010 Apr 15;67(8):722-9.
doi: 10.1016/j.biopsych.2009.12.034. Epub 2010 Feb 20.

Brain reactivity to smoking cues prior to smoking cessation predicts ability to maintain tobacco abstinence

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Brain reactivity to smoking cues prior to smoking cessation predicts ability to maintain tobacco abstinence

Amy C Janes et al. Biol Psychiatry. .

Erratum in

  • Biol Psychiatry. 2010 May 15;67(10):1002

Abstract

Background: Developing the means to identify smokers at high risk for relapse could advance relapse prevention therapy. We hypothesized that functional magnetic resonance imaging (fMRI) reactivity to smoking-related cues, measured before a quit attempt, could identify smokers with heightened relapse vulnerability.

Methods: Before quitting smoking, 21 nicotine-dependent women underwent fMRI during which smoking-related and neutral images were shown. These smokers also were tested for possible attentional biases to smoking-related words using a computerized emotional Stroop (ES) task previously found to predict relapse. Smokers then made a quit attempt and were grouped based on outcomes (abstinence vs. slip: smoking > or = 1 cigarette after attaining abstinence). Prequit fMRI and ES measurements in these groups were compared.

Results: Slip subjects had heightened fMRI reactivity to smoking-related images in brain regions implicated in emotion, interoceptive awareness, and motor planning and execution. Insula and dorsal anterior cingulate cortex (dACC) reactivity induced by smoking images correlated with an attentional bias to smoking-related words. A discriminant analysis of ES and fMRI data predicted outcomes with 79% accuracy. Additionally, smokers who slipped had decreased fMRI functional connectivity between an insula-containing network and brain regions involved in cognitive control, including the dACC and dorsal lateral prefrontal cortex, possibly reflecting reduced top-down control of cue-induced emotions.

Conclusions: These findings suggest that the insula and dACC are important substrates of smoking relapse vulnerability. The data also suggest that relapse-vulnerable smokers can be identified before quit attempts, which could enable personalized treatment, improve tobacco-dependence treatment outcomes, and reduce smoking-related morbidity and mortality.

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Figures

Figure 1
Figure 1
Whole-brain analysis of pre-quit brain reactivity to smoking-related versus neutral images compared between subjects who did and did not slip. Subjects who slipped exhibited greater fMRI reactivity in several brain areas (see Table S1 in Supplement 1), including the right anterior insula (t(19)=2.86, cluster corrected, p 0.005). Talairach (55) coordinates: x=35, y=18, z=0. A = anterior, S = superior, R = right.
Figure 2
Figure 2
Functional connectivity analyses. Top: The pre-quit network was identified in 21 subjects and contained bilateral insula and anterior cingulate cortex (cross hairs positioned in the anterior insula; Talairach (57) coordinates: x=−38, y=13, z=−6, t(20)=7.80, Bonferroni corrected p=0.01; Table S2 in Supplement 1). Bottom: pre-quit network connectivity difference between slip (N=9) versus abstinence (N=12) subjects in dorsal anterior cingulate and other brain areas (Table S3 in Supplement 1. Talairach (55) coordinates for the dACC: x=0. y=13, z=26, t(20)=2.85, cluster corrected, p 0.005). A = anterior, S = superior, R = right.

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