Abstract
Addicts are often vulnerable to drug use in the presence of drug cues, which elicit significant drug cue reactivity. Mounting neuroimaging evidence suggests an association between functional magnetic resonance imaging connectivity networks and smoking cue reactivity; however, there is still little understanding of the electroencephalography (EEG) coherence basis of smoking cue reactivity. We therefore designed two independent experiments wherein nicotine-dependent smokers performed a smoking cue reactivity task during EEG recording. Experiment I showed that a low-theta EEG coherence network occurring 400–600 ms after onset during long-range (mainly between frontal and parieto-occipital) scalp regions, which was involved in smoking cue reactivity. Moreover, the average coherence of this network was significantly correlated with participants’ level of cigarette craving. In experiment II, we tested an independent group of smokers and demonstrated that the low-theta coherence network significantly predicted changes in individuals’ cigarette craving. Thus, the low-theta EEG coherence in smokers’ brains might be a biomarker of smoking cue reactivity and can predict addiction behavior.
Highlights
Nicotine addiction is a psychiatric disorder that is one of the leading causes of avoidable morbidity and mortality globally [1]
In experiment I, we found that smoking cue reactivity was related to increased low-theta (3–5 Hz) coherence at 400–600 ms after stimulus onset in long-range scalp regions
We investigated the EEG coherence basis of smoking cue reactivity using the classical smoking cue reactivity task
Summary
Nicotine addiction is a psychiatric disorder that is one of the leading causes of avoidable morbidity and mortality globally [1]. Functional magnetic resonance imaging (fMRI) studies have shown that smoking cue reactivity involves many brain regions, including the anterior cingulate cortex, the superior frontal gyrus, the posterior cingulate cortex, etc. This suggests that the brain connectivity network is an important. EEG coherence, as a measure of the brain network, which involves calculating the linear relationship between two electrode signals based on their cross-spectrum and estimating the synchronization between neural populations at a high temporal resolution, is believed to reflect functional cortical connectivity at the centimeter scale [13].
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