Hamed Ekhtiari1, Rayus Kuplicki2, Asheema Pruthi3, Martin Paulus2. 1. Laureate Institute of Brain Research, 6655 South Yale Ave, Tulsa, OK, 74136, United States. Electronic address: hekhtiari@laureateinstitute.org. 2. Laureate Institute of Brain Research, 6655 South Yale Ave, Tulsa, OK, 74136, United States. 3. Laureate Institute of Brain Research, 6655 South Yale Ave, Tulsa, OK, 74136, United States; School of Community Medicine, University of Oklahoma, 4502 E 41st, Tulsa, OK, 74135, United States.
Abstract
INTRODUCTION: Drug cue reactivity (DCR) is widely used in experimental settings for both assessment and intervention. There is no validated database of pictorial cues available for methamphetamine and opioids. METHODS: 360 images in three-groups (methamphetamine, opioid and neutral (control)) matched for their content (objects, hands, faces and actions) were selected in an initial development phase. 28 participants with a history of both methamphetamine and opioid use (37.71 ± 8.11 years old, 12 female) with over six months of abstinence were asked to rate images for craving, valence, arousal, typicality and relatedness. RESULTS: All drug images were differentiated from neutral images. Drug related images received higher arousal and lower valence ratings compared to neutral images (craving (0-100) for neutral (11.5 ± 21.9), opioid (87.7 ± 18.5) and methamphetamine (88 ± 18), arousal (1-9) for neutral (2.4 ± 1.9), opioid (4.6 ± 2.7) and methamphetamine (4.6 ± 2.6), and valence (1-9) for neutral (4.8 ± 1.3), opioid (4.4 ± 1.9) and methamphetamine (4.4 ± 1.8)). There is no difference between methamphetamine and opioid images in craving, arousal and valence. There is a significant positive relationship between the amount of time that participants spent on drug-related images and the craving they reported for the image. Every 10 points of craving were associated with an increased response time of 383 ms. Three image sets were automatically selected for equivalent fMRI tasks (methamphetamine and opioids) from the database (tasks are available at github). CONCLUSION: The methamphetamine and opioid cue database (MOCD) provides a resource of validated images/tasks for future DCR studies. Additionally, researchers can select several sets of unique but equivalent images based-on their psychological/physical characteristics for multiple assessments/interventions.
INTRODUCTION: Drug cue reactivity (DCR) is widely used in experimental settings for both assessment and intervention. There is no validated database of pictorial cues available for methamphetamine and opioids. METHODS: 360 images in three-groups (methamphetamine, opioid and neutral (control)) matched for their content (objects, hands, faces and actions) were selected in an initial development phase. 28 participants with a history of both methamphetamine and opioid use (37.71 ± 8.11 years old, 12 female) with over six months of abstinence were asked to rate images for craving, valence, arousal, typicality and relatedness. RESULTS: All drug images were differentiated from neutral images. Drug related images received higher arousal and lower valence ratings compared to neutral images (craving (0-100) for neutral (11.5 ± 21.9), opioid (87.7 ± 18.5) and methamphetamine (88 ± 18), arousal (1-9) for neutral (2.4 ± 1.9), opioid (4.6 ± 2.7) and methamphetamine (4.6 ± 2.6), and valence (1-9) for neutral (4.8 ± 1.3), opioid (4.4 ± 1.9) and methamphetamine (4.4 ± 1.8)). There is no difference between methamphetamine and opioid images in craving, arousal and valence. There is a significant positive relationship between the amount of time that participants spent on drug-related images and the craving they reported for the image. Every 10 points of craving were associated with an increased response time of 383 ms. Three image sets were automatically selected for equivalent fMRI tasks (methamphetamine and opioids) from the database (tasks are available at github). CONCLUSION: The methamphetamine and opioid cue database (MOCD) provides a resource of validated images/tasks for future DCR studies. Additionally, researchers can select several sets of unique but equivalent images based-on their psychological/physical characteristics for multiple assessments/interventions.
Authors: Mehran Zare-Bidoky; Arshiya Sangchooli; Hamed Ekhtiari; Amy C Janes; Marc J Kaufman; Jason A Oliver; James J Prisciandaro; Torsten Wüstenberg; Raymond F Anton; Patrick Bach; Alex Baldacchino; Anne Beck; James M Bjork; Judson Brewer; Anna Rose Childress; Eric D Claus; Kelly E Courtney; Mohsen Ebrahimi; Francesca M Filbey; Dara G Ghahremani; Peyman Ghobadi Azbari; Rita Z Goldstein; Anna E Goudriaan; Erica N Grodin; J Paul Hamilton; Colleen A Hanlon; Peyman Hassani-Abharian; Andreas Heinz; Jane E Joseph; Falk Kiefer; Arash Khojasteh Zonoozi; Hedy Kober; Rayus Kuplicki; Qiang Li; Edythe D London; Joseph McClernon; Hamid R Noori; Max M Owens; Martin P Paulus; Irene Perini; Marc Potenza; Stéphane Potvin; Lara Ray; Joseph P Schacht; Dongju Seo; Rajita Sinha; Michael N Smolka; Rainer Spanagel; Vaughn R Steele; Elliot A Stein; Sabine Steins-Loeber; Susan F Tapert; Antonio Verdejo-Garcia; Sabine Vollstädt-Klein; Reagan R Wetherill; Stephen J Wilson; Katie Witkiewitz; Kai Yuan; Xiaochu Zhang; Anna Zilverstand Journal: Nat Protoc Date: 2022-02-04 Impact factor: 17.021
Authors: Hamed Ekhtiari; Antonio Verdejo-Garcia; Scott J Moeller; Mehran Zare-Bidoky; Alexander Mario Baldacchino; Martin Paulus Journal: Front Psychiatry Date: 2020-11-26 Impact factor: 4.157