Background Developing means to identify smokers at high risk for relapse could advance relapse prevention therapy. We hypothesized that functional magnetic resonance imaging (fMRI) reactivity to smoking-related cues, measured prior to a quit attempt, could identify smokers with heightened relapse vulnerability. Methods Twenty-one nicotine-dependent women underwent fMRI prior to quitting smoking, during which smoking-related and neutral images were shown. These smokers also were tested for possible attentional biases to smoking-related words using a computerized emotional Stroop (ES) task previously found to predict relapse. Smokers then made a quit attempt and were grouped based on outcomes (abstinence versus slip: smoking 1 cigarette after attaining abstinence). Pre-quit fMRI and ES measurements in these groups were compared. Results Slip subjects had heightened fMRI reactivity to smoking-related images in brain regions implicated in emotion, interoceptive awareness, and motor planning and execution. Smoking cue-induced insula and dorsal anterior cingulate cortex (dACC) reactivity correlated with an attentional bias to smoking-related words. A discriminant analysis of ES and fMRI data predicted outcomes with 79% accuracy. Additionally, smokers who slipped had decreased fMRI functional connectivity between an insula-containing network and brain regions involved in cognitive control, including the dACC and dorsal lateral prefrontal cortex, possibly reflecting reduced top-down control of smoking-related cue-induced emotions. Conclusions These findings suggest that the insula and dACC are important substrates of smoking relapse vulnerability. The data also suggest that relapse-vulnerable smokers can be identified prior to quit attempts, which could enable personalized treatment, improve tobacco-dependence treatment outcomes, and reduce smoking-related morbidity and mortality.

Alarm substances are airborne chemical signals, released by an individual into the environment, which communicate emotional stress between conspecifics. Here we tested whether humans, like other mammals, are able to detect emotional stress in others by chemosensory cues. Sweat samples collected from individuals undergoing an acute emotional stressor, with exercise as a control, were pooled and presented to a separate group of participants (blind to condition) during four experiments. In an fMRI experiment and its replication, we showed that scanned participants showed amygdala activation in response to samples obtained from donors undergoing an emotional, but not physical, stressor. An odor-discrimination experiment suggested the effect was primarily due to emotional, and not odor, differences between the two stimuli. A fourth experiment investigated behavioral effects, demonstrating that stress samples sharpened emotion-perception of ambiguous facial stimuli. Together, our findings suggest human chemosensory signaling of emotional stress, with neurobiological and behavioral effects.

Postpartum depression (PPD) affects up to 1 in 8 women. The early postpartum period is characterized by a downward physiological shift from relatively elevated levels of sex steroids during pregnancy to diminished levels after parturition. Sex steroids influence functional brain connectivity in healthy non-puerperal subjects. This study tests the hypothesis that PPD is associated with attenuation of resting-state functional connectivity (rs-fc) within corticolimbic regions implicated in depression and alterations in neuroactive steroid concentrations as compared to healthy postpartum women. Subjects (n=32) were prospectively evaluated during pregnancy and in the postpartum with repeated plasma neuroactive steroid measurements and mood and psychosocial assessments. Healthy comparison subjects (HCS) and medication-free subjects with unipolar PPD (PPD) were examined using functional magnetic resonance imaging (fMRI) within 9 weeks of delivery. We performed rs-fc analysis with seeds placed in the anterior cingulate cortex (ACC), and bilateral amygdalae (AMYG), hippocampi (HIPP) and dorsolateral prefrontal cortices (DLPFC). Postpartum rs-fc and perinatal neuroactive steroid plasma concentrations, quantified by liquid chromatography/mass spectrometry, were compared between groups. PPD subjects showed attenuation of connectivity for each of the tested regions (i.e. ACC, AMYG, HIPP and DLPFC) and between corticocortical and corticolimbic regions vs. HCS. Perinatal concentrations of pregnanolone, allopregnanolone and pregnenolone were not different between groups. This is the first report of a disruption in the rs-fc patterns in medication-free subjects with PPD. This disruption may contribute to the development of PPD, at a time of falling neuroactive steroid concentrations.

A proton MR spectral editing technique employing a spatially localized, double-quantum filter (DQF) was used to measure gamma-aminobutyric acid (GABA) in the human brain at 1.5 T. The double-quantum method provided robust, single-shot suppression of uncoupled resonances from choline, creatine, and NAA and allowed detection of the gamma CH2 GABA (3.0 ppm) resonance with 30% efficiency. Spatial localization of the GABA measurement was achieved by incorporating PRESS localization within the double-quantum excitation and detection sequence. A calibration technique was developed to adjust the relative phases of the RF pulses to maximize the in vivo double-quantum detection efficiency for an arbitrary voxel location. The sequence efficiency, degree of suppression of uncoupled reasonances, and characterization of the in vivo DQF technique was examined in phantom experiments and in a study of the occipital lobe of 10 normal subjects. The ratio of the 3.0-ppm GABA resonance to the 3.0-ppm creatine resonance was found to be 0.20 +/- 0.05 (SD).

A novel, two-dimensional, J-resolved chemical-shift imaging sequence was used to collect gamma-aminobutyric acid (GABA) spectroscopic imaging data on six healthy subjects at 4 T. Using image segmentation and a linear-regression analysis relating brain GABA level to tissue-type, a consistent and significant (n = 6, p < 0.01) elevation of mean GABA levels was measured in the cortical grey matter (0.96 +/- 0.24 mm) compared with white matter (0.44 +/- 0.16 mm) across all six subjects. The results suggest an approximately two-fold elevation of GABA levels in cortical grey matter compared with white matter in vivo. Our findings are consistent with ex vivo studies in the literature of both animal and human brain and demonstrate the significant potential of this technique for detecting and quantifying tissue-specific neurochemical pathology in vivo.

The insula plays a critical role in maintaining nicotine dependence and reactivity to smoking cues. More broadly, the insula and the dorsal anterior cingulate cortex (dACC) are key nodes of the salience network (SN), which integrates internal and extrapersonal information to guide behavior. Thus, insula-dACC interactions may be integral in processing salient information such as smoking cues that facilitate continued nicotine use. We evaluated functional magnetic resonance imaging (fMRI) data from nicotine-dependent participants during rest, and again when they viewed smoking-related images. Greater insula-dACC coupling at rest was significantly correlated with enhanced smoking cue-reactivity in brain areas associated with attention and motor preparation, including the visual cortex, right ventral lateral prefrontal cortex, and the dorsal striatum. In an independent cohort, we found that insula-dACC connectivity was stable over 1-h delay and was not influenced by changes in subjective craving or expired carbon monoxide, suggesting that connectivity strength between these regions may be a trait associated with heightened cue-reactivity. Finally, we also showed that insula reactivity to smoking cues correlates with a rise in cue-reactivity throughout the entire SN, indicating that the insula's role in smoking cue-reactivity is not functionally independent, and may actually represent the engagement of the entire SN. Collectively, these data provide a more network-level understanding of the insula's role in nicotine dependence and shows a relationship between inherent brain organization and smoking cue-reactivity.

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.

Attentional bias for drug-related stimuli, as measured by emotional Stroop (ES) tasks, is predictive of treatment outcomes for tobacco smoking and other abused drugs. Characterizing relationships between smoking-related attentional bias and brain reactivity to smoking images may help identify neural substrates critical to relapse vulnerability. To this end, we investigated putative relations between interference effects in an offline smoking ES task and functional MRI (fMRI) measures of brain reactivity to smoking versus neutral images in women smokers. Positive correlations were found between attentional bias and reactivity to smoking images in brain areas involved in emotion, memory, interoception, and visual processing including the amygdala, hippocampus, parahippocampal gyrus, insula, and occipital cortex. These findings suggest that smokers with elevated attentional biases to smoking-related stimuli may more readily shift attention away from other external stimuli and toward smoking stimuli-induced internal states and emotional memories. Such attentional shifts may contribute to increased interference by smoking cues, possibly increasing relapse vulnerability. Treatments capable of inhibiting shifts to drug cue-induced memories and internal states may lead to personalized tobacco dependence treatment for smokers with high attentional bias to smoking-related stimuli.