Open AccessToward Precision Medicine for Smoking Cessation: Developing a Neuroimaging-Based Classification Algorithm to Identify Smokers at Higher Risk for Relapse
Author(s) -
David W. Frank,
Paul M. Cinciripini,
Menton M. Deweese,
Maher KaramHage,
George Kypriotakis,
Caryn Lerman,
Jason D. Robinson,
Rachel F. Tyndale,
Damon J. Vidrine,
Francesco Versace
Publication year - 2019
Publication title -
nicotine and tobacco research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.338
H-Index - 113
eISSN - 1469-994X
pISSN - 1462-2203
DOI - 10.1093/ntr/ntz211
Subject(s) - abstinence , neuroimaging , smoking cessation , addiction , medicine , clinical psychology , psychology , psychiatry , pathology
By improving our understanding of the neurobiological mechanisms underlying addiction, neuroimaging research is helping to identify new targets for personalized treatment interventions. When trying to quit, smokers with larger electrophysiological responses to cigarette-related, compared with pleasant, stimuli ("C > P") are more likely to relapse than smokers with the opposite brain reactivity profile ("P > C").