Prefrontal and limbic resting state brain network functional connectivity differs between nicotine-dependent smokers and non-smoking controls

• Published in: Drug and alcohol dependence 2012-10, Vol.125 (3), p.252-259
• Main Authors: Janes, Amy C, Nickerson, Lisa D, Frederick, Blaise deB, Kaufman, Marc J
• Format: Article
• Language: English
• Subjects: Addictive behaviors; Adult; Adult and adolescent clinical studies; Biological and medical sciences; Biological markers; Cortex; Cues; Diagnostic and Statistical Manual of Mental Disorders; Drug addiction; Female; Functional connectivity; Humans; Image Processing, Computer-Assisted; Limbic; Limbic System - drug effects; Limbic System - physiology; Magnetic Resonance Imaging; Male; Medical sciences; Middle Aged; Nerve Net - drug effects; Nerve Net - physiology; Parietal Lobe - drug effects; Parietal Lobe - physiology; Prefrontal cortex; Prefrontal Cortex - drug effects; Prefrontal Cortex - physiology; Principal Component Analysis; Psychiatry; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Reactivity; Regression Analysis; Rest - physiology; Resting; Resting state; Smoker-Nonsmoker interactions; Smoking; Smoking - physiopathology; Smoking - psychology; Tobacco smoking; Tobacco Use Disorder - physiopathology; Tobacco Use Disorder - psychology; Tobacco, tobacco smoking; Toxicology
• ISSN: 0376-8716; 1879-0046
• DOI: 10.1016/j.drugalcdep.2012.02.020

Abstract Background Brain dysfunction in prefrontal cortex (PFC) and dorsal striatum (DS) contributes to habitual drug use. These regions are constituents of brain networks thought to be involved in drug addiction. To investigate whether networks containing these regions differ between nicotine dependent female smokers and age-matched female non-smokers, we employed functional MRI (fMRI) at rest. Methods Data were processed with independent component analysis (ICA) to identify resting state networks (RSNs). We identified a subcortical limbic network and three discrete PFC networks: a medial prefrontal cortex (mPFC) network and right and left lateralized fronto-parietal networks common to all subjects. We then compared these RSNs between smokers and non-smokers using a dual regression approach. Results Smokers had greater coupling versus non-smokers between left fronto-parietal and mPFC networks. Smokers with the greatest mPFC–left fronto-parietal coupling had the most DS smoking cue reactivity as measured during an fMRI smoking cue reactivity paradigm. This may be important because the DS plays a critical role in maintaining drug-cue associations. Furthermore, subcortical limbic network amplitude was greater in smokers. Conclusions Our results suggest that prefrontal brain networks are more strongly coupled in smokers, which could facilitate drug-cue responding. Our data also are the first to document greater reward-related network fMRI amplitude in smokers. Our findings suggest that resting state PFC network interactions and limbic network amplitude can differentiate nicotine-dependent smokers from controls, and may serve as biomarkers for nicotine dependence severity and treatment efficacy.