# A Novel, Memory-Updating Technique to Attenuate Responding to High Calorie Food Cues, Food Intake, and Body Weight among Individuals with Overweight/Obesity > **NIH NIH K23** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $167,454 ## Abstract PROJECT SUMMARY/ABSTRACT Dr. Lisa Germeroth is an emerging clinical scientist aiming to develop a line of research on mechanisms driving obesity and novel methods to initiate and sustain weight loss. This K23 proposes research and training that allows the PI to develop the requisite skills to become an independent clinical scientist in obesity. Research will be conducted at the U. of Pittsburgh, which provides a strong research environment, multidisciplinary collaborators, and professional development support for the PI’s career path. The mentorship team is comprised of experts in behavioral obesity intervention and food intake assessment (Dr. Michele Levine; Primary Mentor), and ecological momentary assessment (EMA) methodology and longitudinal analysis (Dr. Meredith Wallace; Co- Mentor), along with strategically-selected consultants. Through coursework, workshops, experiential training, and readings, mentors and institutional resources will facilitate the PI’s competence in understanding mechanisms driving obesity, applying behavioral techniques to address these mechanisms, and using EMA to evaluate real-world behavior change. This K23 aims to evaluate the effects of retrieval-extinction (R-E) training, a technique targeting fundamental memory processes that associate cues with reward, on high calorie food cue- reactivity, food intake, and body weight among those with overweight/obesity. R-E training involves “retrieving” cue-reward associative memories, bringing them into a labile state and providing an opportunity to be updated through a time-limited process of reconsolidation. By administering extinction training during reconsolidation, research has indicated that unstable cue-reward memories can be modified to produce lasting effects on reduced drug cue-reactivity and use. To examine the effects of R-E training on high calorie food cue-reactivity and intake, 150 adults with overweight/obesity who are motivated to lose weight will complete baseline lab food cue-reactivity and intake tasks. Participants will be randomized to R-E training or an extinction control. R-E training will occur on two consecutive days and follow-up lab food cue-reactivity assessments at 24-hr, 2-week, 1- and 3-month follow-up. Weight will be assessed at each session and in-lab food intake at 1- and 3-months. Phone food recalls will be conducted throughout the study. A subset of participants (n=75) will complete an EMA pilot reporting naturally-occurring food cues, craving, and food intake. The PI will document the effects of R-E training on food cue-reactivity and intake in the lab and real-world (Aim 1), examine food cue-reactivity as a mechanism through which R-E training affects food intake (Aim 2), and explore associations between lab and real-world cue-elicited craving and food intake, and the effect of R-E training on weight (Exploratory Aims). These aims build on the PI’s clinical psychology background and contribute novel data on an innovative technique to re... ## Key facts - **NIH application ID:** 9882258 - **Project number:** 5K23DK117994-02 - **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH - **Principal Investigator:** Lisa J Germeroth - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $167,454 - **Award type:** 5 - **Project period:** 2019-04-01 → 2020-10-02 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9882258 ## Citation > US National Institutes of Health, RePORTER application 9882258, A Novel, Memory-Updating Technique to Attenuate Responding to High Calorie Food Cues, Food Intake, and Body Weight among Individuals with Overweight/Obesity (5K23DK117994-02). Retrieved via AI Analytics 2026-06-02 from https://api.ai-analytics.org/grant/nih/9882258. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*