Amy C. Janes

Brain reactivity to smoking cues prior to smoking cessation predicts ability to maintain tobacco abstinence.

BACKGROUND Developing the 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 before a quit attempt, could identify smokers with heightened relapse vulnerability. METHODS Before quitting smoking, 21 nicotine-dependent women underwent fMRI 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 vs. slip: smoking > or = 1 cigarette after attaining abstinence). Prequit 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. Insula and dorsal anterior cingulate cortex (dACC) reactivity induced by smoking images 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 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 before quit attempts, which could enable personalized treatment, improve tobacco-dependence treatment outcomes, and reduce smoking-related morbidity and mortality.

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

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.

Neural Substrates of Attentional Bias for Smoking-Related Cues: An fMRI Study

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 in identifying neural substrates critical to relapse vulnerability. To this end, we investigated putative relationships between interference effects in an offline smoking ES task and functional MRI (fMRI) measures of brain reactivity to smoking vs 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.

Brain fMRI reactivity to smoking-related images before and during extended smoking abstinence.

Reactivity to smoking-related cues may play a role in the maintenance of smoking behavior and may change depending on smoking status. Whether smoking cue-related functional MRI (fMRI) reactivity differs between active smoking and extended smoking abstinence states currently is unknown. We used fMRI to measure brain reactivity in response to smoking-related versus neutral images in 13 tobacco-dependent subjects before a smoking cessation attempt and again during extended smoking abstinence (52 +/- 11 days) aided by nicotine replacement therapy. Prequit smoking cue induced fMRI activity patterns paralleled those reported in prior smoking cue reactivity fMRI studies. Greater fMRI activity was detected during extended smoking abstinence than during the pre-quit [corrected] assessment subcortically in the caudate nucleus and cortically in prefrontal (BA 6, 8, 9, 10, 44, 46), [corrected] primary somatosensory (BA 1, 2, 3), temporal (BA 22), [corrected] parietal (BA 5, 7, 40), occipital (BA 17, 18), [corrected] and posterior cingulate (BA 31) cortex. These data suggest that during extended smoking abstinence, fMRI reactivity to smoking versus neutral stimuli persists in brain areas involved in attention, somatosensory processing, motor planning, and conditioned cue responding. In some brain regions, fMRI smoking cue reactivity is increased during extended smoking abstinence in comparison to the prequit state, which may contribute to persisting relapse vulnerability.

Insula–Dorsal Anterior Cingulate Cortex Coupling is Associated with Enhanced Brain Reactivity to Smoking Cues

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.

Altered intrinsic functional coupling between core neurocognitive networks in Parkinson's disease

Parkinsons disease (PD) is largely attributed to disruptions in the nigrostriatal dopamine system. These neurodegenerative changes may also have a more global effect on intrinsic brain organization at the cortical level. Functional brain connectivity between neurocognitive systems related to cognitive processing is critical for effective neural communication, and is disrupted across neurological disorders. Three core neurocognitive networks have been established as playing a critical role in the pathophysiology of many neurological disorders: the default-mode network (DMN), the salience network (SN), and the central executive network (CEN). In healthy adults, DMN–CEN interactions are anti-correlated while SN–CEN interactions are strongly positively correlated even at rest, when individuals are not engaging in any task. These intrinsic between-network interactions at rest are necessary for efficient suppression of the DMN and activation of the CEN during a range of cognitive tasks. To identify whether these network interactions are disrupted in individuals with PD, we used resting state functional magnetic resonance imaging (rsfMRI) to compare between-network connectivity between 24 PD participants and 20 age-matched controls (MC). In comparison to the MC, individuals with PD showed significantly less SN–CEN coupling and greater DMN–CEN coupling during rest. Disease severity, an index of striatal dysfunction, was related to reduced functional coupling between the striatum and SN. These results demonstrate that individuals with PD have a dysfunctional pattern of interaction between core neurocognitive networks compared to what is found in healthy individuals, and that interaction between the SN and the striatum is even more profoundly disrupted in those with greater disease severity.

Striatal Morphology is Associated with Tobacco Cigarette Craving

The striatum has a clear role in addictive disorders and is involved in drug-related craving. Recently, enhanced striatal volume was associated with greater lifetime nicotine exposure, suggesting a bridge between striatal function and structural phenotypes. To assess this link between striatal structure and function, we evaluated the relationship between striatal morphology and this brain region’s well-established role in craving. In tobacco smokers, we assessed striatal volume, surface area, and shape using a new segmentation methodology coupled with local shape indices. Striatal morphology was then related with two measures of craving: state-based craving, assessed by the brief questionnaire of smoking urges (QSU), and craving induced by smoking-related images. A positive association was found between left striatal volume and surface area with both measures of craving. A more specific relationship was found between both craving measures and the dorsal, but not in ventral striatum. Evaluating dorsal striatal subregions showed a single relationship between the caudate and QSU. Although cue-induced craving and the QSU were both associated with enlarged striatal volume and surface area, these measures were differentially associated with global or more local striatal volumes. We also report a connection between greater right striatal shape deformations and cue-induced craving. Shape deformations associated with cue-induced craving were specific to striatal subregions involved in habitual responding to rewarding stimuli, which is relevant given the habitual nature of cue-induced craving. The current findings confirm a relationship between striatal function and morphology and suggest that variation in striatal morphology may be a biomarker for craving severity.

An Increase in Tobacco Craving Is Associated with Enhanced Medial Prefrontal Cortex Network Coupling

Craving is a key aspect of drug dependence that is thought to motivate continued drug use. Numerous brain regions have been associated with craving, suggesting that craving is mediated by a distributed brain network. Whether an increase in subjective craving is associated with enhanced interactions among brain regions was evaluated using resting state functional magnetic imaging (fMRI) in nicotine dependent participants. We focused on craving-related changes in the orbital and medial prefrontal cortex (OMPFC) network, which also included the subgenual anterior cingulate cortex (sgACC) extending into the ventral striatum. Brain regions in the OMPFC network are not only implicated in addiction and reward, but, due to their rich anatomic interconnections, may serve as the site of integration across craving-related brain regions. Subjective craving and resting state fMRI were evaluated twice with an ∼1 hour delay between the scans. Cigarette craving was significantly increased at the end, relative to the beginning of the scan session. Enhanced craving was associated with heightened coupling between the OMPFC network and other cortical, limbic, striatal, and visceromotor brain regions that are both anatomically interconnected with the OMPFC, and have been implicated in addiction and craving. This is the first demonstration confirming that an increase in craving is associated with enhanced brain region interactions, which may play a role in the experience of craving.

Effects of autoshaping procedures on 3H-8-OH-DPAT-labeled 5-HT1a binding and 125I-LSD-labeled 5-HT2a binding in rat brain

Effects of experience with Pavlovian autoshaping procedures on lever-press autoshaping conditioned response (CR) performance and 3H-8-OH-DPAT-labeled binding of 5-HT(1a) receptors as well as 125I-LSD-labeled binding of 5-HT(2a) receptors were evaluated in four groups of male Long-Evans hooded rats. Two groups of rats (Group Paired High CR and Group Paired Low CR) received Pavlovian autoshaping procedures wherein the presentation of a lever (conditioned stimulus, CS) was followed by the response-independent presentation of food (unconditioned stimulus, US). Rats in Group Paired High CR (n=12) showed more rapid CR acquisition and higher asymptotic levels of lever-press autoshaping CR performance relative to rats in Group Low CR (n=12). Group Omission (n=9) received autoshaping with an omission contingency, such that performing the lever-press autoshaping CR resulted in the cancellation the food US, while Group Random (n=9) received presentations of lever CS and food US randomly with respect to one another. Though Groups Omission and Random did not differ in lever-press autoshaping CR performance, Group Omission showed significantly lower levels of 3H-8-OH-DPAT-labeled 5-HT(1a) binding in post-synaptic areas (frontal cortex, septum, caudate putamen), as well as significantly higher plasma corticosterone levels than Group Random. In addition, Group Random showed higher levels of 3H-8-OH-DPAT-labeled 5-HT(1a) binding in pre-synaptic somatodendritic autoreceptors on dorsal raphe nucleus relative to each of the other three groups. Autoradiographic analysis of 125I-LSD-labeled 5-HT(2a) receptor binding revealed no significant differences between Groups Paired High CR and Paired Low CR or between Groups Omission and Random in any brain regions.

Can apparent resting state connectivity arise from systemic fluctuations

It is widely accepted that the fluctuations in resting state blood oxygenation level dependent (BOLD) functional MRI (fMRI) reflect baseline neuronal activation through neurovascular coupling; this data is used to infer functional connectivity in the human brain during rest. Consistent activation patterns, i.e., resting state networks (RSN) are seen across groups, conditions, and even species. In this study, we show that some of these patterns can also be generated from the dynamic, systemic, non-neuronal physiological low frequency oscillations (sLFOs) in the BOLD signal alone. We have previously used multimodal imaging to demonstrate the wide presence of the same sLFOs in the brain (BOLD) and periphery with different time delays. This study shows that these sLFOs from BOLD signals alone can give rise to stable spatial patterns, which can be detected during resting state analyses. We generated synthetic resting state data for 11 subjects based only on subject-specific, dynamic sLFO information obtained from resting state data using concurrent peripheral optical imaging or a novel recursive procedure. We compared the results obtained by performing a group independent component analysis (ICA) on this synthetic data (i.e., the result from simulation) to the results obtained from analysis of the real data. ICA detected most of the eight well-known RSNs, including visual, motor, and default mode networks (DMNs), in both the real and the synthetic data sets. These findings suggest that RSNs may reflect, to some extent, vascular anatomy associated with systemic fluctuations, rather than neuronal connectivity.