# Targeting Foundational Memory Processes in Nicotine Addiction: A Translational Clinical Neuroscience Study of a Retrieval-Extinction Intervention to Reduce Craving & Smoking Behavior

> **NIH NIH R01** · MEDICAL UNIVERSITY OF SOUTH CAROLINA · 2020 · $547,192

## Abstract

PROJECT SUMMARY: We recently published results from a NIDA-funded study of a brief behavioral
treatment that was designed to reduce the troublesome cravings that smokers encounter when they attempt to
quit smoking. This intervention was based on a growing body of neuroscience studies showing that memories
for prior learning can be retrieved by the presentation of cues involved in that learning. Once retrieved, the
memories enter into a brief period of vulnerability, during which they can be modified, but after which they are
reconsolidated (restabilized) back into long-term storage. The treatment potential of this phenomenon was
initially demonstrated in a Science report in which inpatient heroin addicts were briefly exposed to cues
associated with heroin use in order to prompt the heroin use memories into a vulnerable state. Once the
memories were in this state, the heroin addicts received extinction training consisting of protracted exposure to
heroin associated cues. It was argued that extinction would change the memories such that the cues would no
longer be associated with heroin administration and reward. Remarkably, after just two sessions of retrieval-
extinction training (RET), the investigators found that craving in response to heroin cues was substantially
reduced for up to 6-months post-treatment. This effect was observed relative to a control group that received
retrieval involving non-heroin cues, followed by extinction. These impressive initial findings led us to replicate
and extend the study in cigarette smokers. In our study, one group of smokers received two sessions of RET
with smoking cues whereas a control group received the same training except that retrieval consisted of brief
exposure to neutral, smoking-unrelated cues. Craving and other reactions to familiar and novel smoking cues
were assessed in test sessions performed 24-hrs, 2-weeks and 1-month after intervention; smoking behavior
was also assessed over 1-month follow-up. Remarkably, at 1-month follow-up, craving to both familiar and
novel smoking cues was significantly lower in the group receiving R-E training vs. control. Even more striking
was the 25% reduction in the number of cigarettes smoked per day in the RET group vs. control. [Also of
significance was suggestive evidence that, relative to control participants, more participants in the RET group
achieved a 60% reduction in smoking (from pretreatment levels)]. The proposed project will replicate and
extend these findings by 1) increasing the dose of intervention so as to bolster the observed treatment effects,
2) employing brain imaging methods to identify patterns of brain activity uniquely associated with the
intervention and potentially predictive of treatment outcome, 3) adding a control group that will enhance
understanding of the effects of RET, and 4) extending follow-up period to more completely document the long-
term effects of RET. Positive findings from this study could lead to the development of ...

## Key facts

- **NIH application ID:** 9920121
- **Project number:** 5R01DA043587-03
- **Recipient organization:** MEDICAL UNIVERSITY OF SOUTH CAROLINA
- **Principal Investigator:** Michael E Saladin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $547,192
- **Award type:** 5
- **Project period:** 2018-07-15 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9920121

## Citation

> US National Institutes of Health, RePORTER application 9920121, Targeting Foundational Memory Processes in Nicotine Addiction: A Translational Clinical Neuroscience Study of a Retrieval-Extinction Intervention to Reduce Craving & Smoking Behavior (5R01DA043587-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9920121. Licensed CC0.

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