Potential Contribution of Aromatase Inhibition to the Effects of Nicotine and Related Compounds on the Brain

Cigarette smoking continues to be a major public health problem, and while smoking rates in men have shown some decrease over the last few decades, smoking rates among girls and young women are increasing. Practically all of the important aspects of cigarette smoking and many effects of nicotine are sexually dimorphic (reviewed by Pogun and Yararbas, 2009). Women become addicted more easily than men, while finding it harder to quit. Nicotine replacement appears to be less effective in women. This may be linked to the observation that women are more sensitive than men to non-nicotine cues or ingredients in cigarettes. The reasons for these sex differences are mostly unknown. Several lines of evidence suggest that many of the reported sex differences related to cigarette smoking may stem from the inhibitory effects of nicotine and other tobacco alkaloids on estrogen synthesis via the enzyme aromatase (cyp19a gene product). Aromatase is the last enzyme in estrogen biosynthesis, catalyzing the conversion of androgens to estrogens. This review provides a summary of experimental evidence supporting brain aromatase as a potential mediator and/or modulator of nicotine actions in the brain, contributing to sex differences in smoking behavior. Additional research on the interaction between tobacco smoke, nicotine, and aromatase may help devise new, sex specific methods for prevention and treatment of smoking addiction

The feeling of anger: From brain networks to linguistic expressions.

This review of the neuroscience of anger is part of The Human Affectome Project, where we attempt to map anger and its components (i.e., physiological, cognitive, experiential) to the neuroscience literature (i.e., genetic markers, functional imaging of human brain networks) and to linguistic expressions used to describe anger feelings. Given the ubiquity of anger in both its normative and chronic states, specific language is used in humans to express states of anger. Following a review of the neuroscience literature, we explore the language that is used to convey angry feelings, as well as metaphors reflecting inner states of anger experience. We then discuss whether these linguistic expressions can be mapped on to the neural circuits during anger experience and to distinct components of anger. We also identify relationships between anger components, brain networks, and other affective research relevant to motivational states of dominance and basic needs for safety

Methylphenidate Attenuates Limbic Brain Inhibition after Cocaine-Cues Exposure in Cocaine Abusers

Dopamine (phasic release) is implicated in conditioned responses. Imaging studies in cocaine abusers show decreases in striatal dopamine levels, which we hypothesize may enhance conditioned responses since tonic dopamine levels modulate phasic dopamine release. To test this we assessed the effects of increasing tonic dopamine levels (using oral methylphenidate) on brain activation induced by cocaine-cues in cocaine abusers. Brain metabolism (marker of brain function) was measured with PET and 18FDG in 24 active cocaine abusers tested four times; twice watching a Neutral video (nature scenes) and twice watching a Cocaine-cues video; each video was preceded once by placebo and once by methylphenidate (20 mg). The Cocaine-cues video increased craving to the same extent with placebo (68%) and with methylphenidate (64%). In contrast, SPM analysis of metabolic images revealed that differences between Neutral versus Cocaine-cues conditions were greater with placebo than methylphenidate; whereas with placebo the Cocaine-cues decreased metabolism (p<0.005) in left limbic regions (insula, orbitofrontal, accumbens) and right parahippocampus, with methylphenidate it only decreased in auditory and visual regions, which also occurred with placebo. Decreases in metabolism in these regions were not associated with craving; in contrast the voxel-wise SPM analysis identified significant correlations with craving in anterior orbitofrontal cortex (p<0.005), amygdala, striatum and middle insula (p<0.05). This suggests that methylphenidate's attenuation of brain reactivity to Cocaine-cues is distinct from that involved in craving. Cocaine-cues decreased metabolism in limbic regions (reflects activity over 30 minutes), which contrasts with activations reported by fMRI studies (reflects activity over 2–5 minutes) that may reflect long-lasting limbic inhibition following activation. Studies to evaluate the clinical significance of methylphenidate's blunting of cue-induced limbic inhibition may help identify potential benefits of this medication in cocaine addiction

Disrupted Functional Connectivity with Dopaminergic Midbrain in Cocaine Abusers

Background: Chronic cocaine use is associated with disrupted dopaminergic neurotransmission but how this disruption affects overall brain function (other than reward/motivation) is yet to be fully investigated. Here we test the hypothesis that cocaine addicted subjects will have disrupted functional connectivity between the midbrain (where dopamine neurons are located) and cortical and subcortical brain regions during the performance of a sustained attention task. Methodology/Principal Findings: We measured brain activation and functional connectivity with fMRI in 20 cocaine abusers and 20 matched controls. When compared to controls, cocaine abusers had lower positive functional connectivity of midbrain with thalamus, cerebellum, and rostral cingulate, and this was associated with decreased activation in thalamus and cerebellum and enhanced deactivation in rostral cingulate. Conclusions/Significance: These findings suggest that decreased functional connectivity of the midbrain interferes with the activation and deactivation signals associated with sustained attention in cocaine addicts

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine

Modeling Neuronal Interactivity using Dynamic Bayesian Networks

Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active brain. However, interactivity between functional brain regions, is still little studied. In this paper, we contribute a novel framework for modeling the interactions between multiple active brain regions, using Dynamic Bayesian Networks (DBNs) as generative models for brain activation patterns. This framework is applied to modeling of neuronal circuits associated with reward. The novelty of our framework from a Machine Learning perspective lies in the use of DBNs to reveal the brain connectivity and interactivity. Such interactivity models which are derived from fMRI data are then validated through a group classification task. We employ and compare four different type