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Related Experiment Video

Updated: Apr 20, 2026

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

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Working memory-related neural activity predicts future smoking relapse.

James Loughead¹, E Paul Wileyto², Kosha Ruparel²

¹Center for Interdisciplinary Research on Nicotine Addiction, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.

Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology

|December 4, 2014

Summary

Brain activity during smoking abstinence can predict relapse. Specific changes in the dorsolateral prefrontal cortex and posterior cingulate cortex signal predict early smoking relapse.

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Area of Science:

Neuroscience
Addiction Research
Cognitive Psychology

Background:

Smoking cessation is challenging, with relapse being common.
Cognitive impairments, especially in executive function, during brief abstinence contribute to relapse.
Predictive biomarkers for smoking relapse are needed to improve treatment outcomes.

Purpose of the Study:

To investigate if working memory-related brain activity during abstinence predicts smoking relapse.
To determine if neuroimaging measures improve prediction beyond clinical and behavioral factors.
To identify specific brain regions and activity patterns associated with early smoking relapse.

Main Methods:

Eighty treatment-seeking smokers underwent functional magnetic resonance imaging (fMRI) during a working memory task under satiety and 24-hour abstinence conditions.
Blood oxygen level-dependent (BOLD) signal changes were analyzed in regions including the dorsolateral prefrontal cortex (DLPFC) and posterior cingulate cortex (PCC).
Relapse within 7 days was biochemically verified using cotinine levels, and predictive models were validated using resampling techniques.

Main Results:

Smoking relapse was predicted by increased withdrawal symptoms, decreased left DLPFC activation, and increased PCC BOLD signal change during abstinence compared to satiety.
A model combining these neuroimaging and clinical predictors achieved an 81% area under the curve in receiver operating characteristic analysis.
This neuroimaging-based model significantly outperformed a model using only clinical variables.

Conclusions:

Decreased left DLPFC activation and reduced PCC suppression during abstinence are potential prognostic markers for early smoking relapse.
Neuroimaging of working memory function offers a promising avenue for predicting relapse in smokers undergoing cessation treatment.
Integrating brain activity measures with clinical data can enhance the prediction of smoking relapse outcomes.