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Drug Alcohol Depend. 2012 Oct 1;125(3):252-9. doi: 10.1016/j.drugalcdep.2012.02.020. Epub 2012 Mar 27.

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

Author information

1
Brain Imaging Center, McLean Hospital, Department of Psychiatry, Harvard Medical School, Belmont, MA 02478, USA. ajanes@mclean.harvard.edu

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.

PMID:
22459914
PMCID:
PMC3389311
DOI:
10.1016/j.drugalcdep.2012.02.020
[Indexed for MEDLINE]
Free PMC Article
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