Data-driven connectivity profiles relate to smoking cessation outcomes
Data-driven connectivity profiles relate to smoking cessation outcomes is a scholarly work, published in 2024 in ''Neuropsychopharmacology''. The main subjects of the publication include medicine, salience, drug withdrawal, cognition, Network analysis, connectome, default mode network, psychology, resting-state fMRI, (−)-nicotine, smoking cessation, neuroscience, and addiction. The study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt.