Cannabis Affects Cerebellar Volume and Sleep Differently in Men and Women.

Background: There are known sex differences in behavioral and clinical outcomes associated with drugs of abuse, including cannabis. However, little is known about how chronic cannabis use and sex interact to affect brain structure, particularly in regions with high cannabinoid receptor expression, such as the cerebellum, amygdala, and hippocampus. Based on behavioral data suggesting that females may be particularly vulnerable to the effects of chronic cannabis use, we hypothesized lower volumes in these regions in female cannabis users. We also hypothesized poorer sleep quality among female cannabis users, given recent findings highlighting the importance of sleep for many outcomes related to cannabis use disorder. Methods: Using data from the Human Connectome Project, we examined 170 chronic cannabis users (>100 lifetime uses and/or a lifetime diagnosis of cannabis dependence) and 170 controls that we attempted to match on age, sex, BMI, race, tobacco use, and alcohol use. We performed group-by-sex ANOVAs, testing for an interaction in subcortical volumes, and in self-reported sleep quality (Pittsburgh Sleep Questionnaire Inventory). Results: After controlling for total intracranial volume and past/current tobacco usage, we found that cannabis users relative to controls had smaller cerebellum volume and poorer sleep quality, and these effects were driven by the female cannabis users (i.e., a group-by-sex interaction). Among cannabis users, there was an age of first use-by-sex interaction in sleep quality, such that females with earlier age of first cannabis use tended to have more self-reported sleep issues, whereas this trend was not present among male cannabis users. The amygdala volume was smaller in cannabis users than in non-users but the group by sex interaction was not significant. Conclusions: These data corroborate prior findings that females may be more sensitive to the neural and behavioral effects of chronic cannabis use than males. Further work is needed to determine if reduced cerebellar and amygdala volumes contribute to sleep impairments in cannabis users.

Elevated thalamic glutamate levels and reduced water diffusivity in alcohol use disorder: Association with impulsivity.

Alcohol induces neuroinflammation but its role in cognitive impairment and impulsivity in alcohol use disorder (AUD) has been poorly investigated. We used proton magnetic resonance spectroscopy to measure brain glutamate (Glu) levels and diffusion-weighted imaging to measure functional anisotropy (FA) in the thalamus and ventral anterior cingulate cortex (vACC) in 15 recently detoxified patients with AUD and 14 matched controls. Compared to controls, AUD patients showed higher Glu levels (p = 0.04) and lower FA in the thalamus (p = 0.04) but not in the vACC. In AUD, thalamic Glu levels (r = 0.62, p = 0.019) and FA (r=-0.55, p = 0.034) were associated with severity of drinking (drinks/week). Compared to controls, AUD patients showed higher scores on Conners' Adult ADHD Rating Scale for impulsivity (p = 0.03), which correlated with glutamate levels in the thalamus (r = 0.58, p = 0.03) and vACC (r = 0.55, p = 0.036). In a second cohort of AUD patients (n = 32), Glu in dorsal ACC (dACC) also correlated with Barrett Impulsiveness Scale total score (r = 0.43, p = 0.014). We interpret the elevated thalamic Glu levels and the parallel reduction in FA in AUD-which correlated with drinking severity-as possible evidence of neurotoxicity from neuroinflammation. The association of Glu with impulsivity suggests that neurotoxic effects of chronic alcohol exposure in the thalamus and dACC may contribute to impulsivity.

Association Between Reduced Brain Glucose Metabolism and Cortical Thickness in Alcoholics: Evidence of Neurotoxicity.

BACKGROUND: Excessive alcohol consumption is associated with reduced cortical thickness (CT) and lower cerebral metabolic rate of glucose (CMRGlu), but the correlation between these 2 measures has not been investigated. METHODS: We tested the association between CT and cerebral CMRGlu in 19 participants with alcohol use disorder (AUD) and 20 healthy controls. Participants underwent 2-Deoxy-2-[18F]fluoroglucose positron emission tomography to map CMRGlu and magnetic resonance imaging to assess CT. RESULTS: Although performance accuracy on a broad range of cognitive domains did not differ significantly between AUD and HC, AUD had widespread decreases in CT and CMRGlu. CMRGlu, normalized to cerebellum (rCMRGlu), showed significant correlation with CT across participants. Although there were large group differences in CMRGlu (>17%) and CT (>6%) in medial orbitofrontal and BA 47, the superior parietal cortex showed large reductions in CMRGlu (~17%) and minimal CT differences (~2.2%). Though total lifetime alcohol (TLA) was associated with CT and rCMRGlu, the causal mediation analysis revealed significant direct effects of TLA on rCMRGlu but not on CT, and there were no significant mediation effects of TLA, CT, and rCMRGlu. CONCLUSIONS: The significant correlation between decrements in CT and CMRGlu across AUD participants is suggestive of alcohol-induced neurotoxicity, whereas the findings that the most metabolically affected regions in AUD had minimal atrophy and vice versa indicates that changes in CT and CMRGlu reflect distinct responses to alcohol across brain regions.

Essential Control of the Function of the Striatopallidal Neuron by Pre-coupled Complexes of Adenosine A2A-Dopamine D2 Receptor Heterotetramers and Adenylyl Cyclase.

The central adenosine system and adenosine receptors play a fundamental role in the modulation of dopaminergic neurotransmission. This is mostly achieved by the strategic co-localization of different adenosine and dopamine receptor subtypes in the two populations of striatal efferent neurons, striatonigral and striatopallidal, that give rise to the direct and indirect striatal efferent pathways, respectively. With optogenetic techniques it has been possible to dissect a differential role of the direct and indirect pathways in mediating "Go" responses upon exposure to reward-related stimuli and "NoGo" responses upon exposure to non-rewarded or aversive-related stimuli, respectively, which depends on their different connecting output structures and their differential expression of dopamine and adenosine receptor subtypes. The striatopallidal neuron selectively expresses dopamine D2 receptors (D2R) and adenosine A2A receptors (A2AR), and numerous experiments using multiple genetic and pharmacological in vitro, in situ and in vivo approaches, demonstrate they can form A2AR-D2R heteromers. It was initially assumed that different pharmacological interactions between dopamine and adenosine receptor ligands indicated the existence of different subpopulations of A2AR and D2R in the striatopallidal neuron. However, as elaborated in the present essay, most evidence now indicates that all interactions can be explained with a predominant population of striatal A2AR-D2R heteromers forming complexes with adenylyl cyclase subtype 5 (AC5). The A2AR-D2R heteromer has a tetrameric structure, with two homodimers, which allows not only multiple allosteric interactions between different orthosteric ligands, agonists, and antagonists, but also the canonical Gs-Gi antagonistic interaction at the level of AC5. We present a model of the function of the A2AR-D2R heterotetramer-AC5 complex, which acts as an integrative device of adenosine and dopamine signals that determine the excitability and gene expression of the striatopallidal neurons. The model can explain most behavioral effects of A2AR and D2R ligands, including the psychostimulant effects of caffeine. The model is also discussed in the context of different functional striatal compartments, mainly the dorsal and the ventral striatum. The current accumulated knowledge of the biochemical properties of the A2AR-D2R heterotetramer-AC5 complex offers new therapeutic possibilities for Parkinson's disease, schizophrenia, SUD and other neuropsychiatric disorders with dysfunction of dorsal or ventral striatopallidal neurons.

Dynamic brain glucose metabolism identifies anti-correlated cortical-cerebellar networks at rest.

It remains unclear whether resting state functional magnetic resonance imaging (rfMRI) networks are associated with underlying synchrony in energy demand, as measured by dynamic 2-deoxy-2-[18F]fluoroglucose (FDG) positron emission tomography (PET). We measured absolute glucose metabolism, temporal metabolic connectivity (t-MC) and rfMRI patterns in 53 healthy participants at rest. Twenty-two rfMRI networks emerged from group independent component analysis (gICA). In contrast, only two anti-correlated t-MC emerged from FDG-PET time series using gICA or seed-voxel correlations; one included frontal, parietal and temporal cortices, the other included the cerebellum and medial temporal regions. Whereas cerebellum, thalamus, globus pallidus and calcarine cortex arose as the strongest t-MC hubs, the precuneus and visual cortex arose as the strongest rfMRI hubs. The strength of the t-MC linearly increased with the metabolic rate of glucose suggesting that t-MC measures are strongly associated with the energy demand of the brain tissue, and could reflect regional differences in glucose metabolism, counterbalanced metabolic network demand, and/or differential time-varying delivery of FDG. The mismatch between metabolic and functional connectivity patterns computed as a function of time could reflect differences in the temporal characteristics of glucose metabolism as measured with PET-FDG and brain activation as measured with rfMRI.

Brain Network Dynamics Adhere to a Power Law.

The temporal dynamics of complex networks such as the Internet are characterized by a power scaling between the temporal mean and dispersion of signals at each network node. Here we tested the hypothesis that the temporal dynamics of the brain networks are characterized by a similar power law. This realization could be useful to assess the effects of randomness and external modulators on the brain network dynamics. Simulated data using a well-stablished random diffusion model allowed us to predict that the temporal dispersion of the amplitude of low frequency fluctuations (ALFF) and that of the local functional connectivity density (lFCD) scale with their temporal means. We tested this hypothesis in open-access resting-state functional magnetic resonance imaging datasets from 66 healthy subjects. A robust power law emerged from the temporal dynamics of ALFF and lFCD metrics, which was insensitive to the methods used for the computation of the metrics. The scaling exponents (ALFF: 0.8 ± 0.1; lFCD: 1.1 ± 0.1; mean ± SD) decreased with age and varied significantly across brain regions; multimodal cortical areas exhibited lower scaling exponents, consistent with a stronger influence of external inputs, than limbic and subcortical regions, which exhibited higher scaling exponents, consistent with a stronger influence of internal randomness. Findings are consistent with the notion that external inputs govern neuronal communication in the brain and that their relative influence differs between brain regions. Further studies will assess the potential of this metric as biomarker to characterize neuropathology.

Temporal Evolution of Brain Functional Connectivity Metrics: Could 7 Min of Rest be Enough?

Unaccounted temporal dynamics of resting-state functional connectivity (FC) metrics challenges their potential as biomarkers for clinical applications in neuroscience. Here we studied the scan time required to reach stable values for various FC metrics including seed-voxel correlations and spatial independent component analyses (sICA), and for the local functional connectivity density (lFCD), a graph theory metric. By increasing the number of time points included in the analysis, we assessed the effects of scan time on convergence of accuracy, sensitivity, specificity, reproducibility, and reliability of these FC metrics. The necessary scan time to attenuate the effects of the temporal dynamics by 80% varied across connectivity metrics and was shorter for lFCD (7 min) than for FC (11 min) or for sICA (10 min). Findings suggest that the scan time required to achieve stable FC is metric-dependent, with lFCD being the most resilient metric to the effects of temporal dynamics. Thus, the lFCD metric could be particularly useful for pediatric and patient populations who may not tolerate long scans.

Induced magnetic field gradients and forces in the human head in MRI.

PURPOSE: To map the induced magnetic field gradients and estimate the magnetic force in the human head during magnetic resonance imaging at 4 Tesla (T). MATERIALS AND METHODS: The magnetic field distribution in the human head was measured using two gradient-echo experiments with different echo times. The phase of the complex image ratio removed the wrapping artifact, characteristic of phase images, and was used to map the magnetic field distribution and calculate the accurate maps of the magnetic field gradients in the human head. RESULTS: The time-independent gradient fields induced by air/tissue interfaces in the head can be 50 times larger than those resulting from the magnetic field inhomogeneity of the MRI magnet. However, the associated magnetic force in the brain is by far smaller than the gravitational force. CONCLUSION: The induced gradient fields increase the magnetic force on tissues. However, even for tissue components with large magnetic susceptibility such as iron-containing proteins, this force is negligible compared with the gravitational force. Therefore, this study suggests that static and uniform magnetic fields do not have a significant risk for the tissues in the head.

Macrovascular contribution in activation patterns of working memory.

Brain activation maps of blood oxygenation level dependent (BOLD) signals during functional magnetic resonance imaging (fMRI) are sensitive to unwanted contributions from large vessels. Most BOLD-fMRI studies are based on a stimulus-correlated modulation of the MRI signal amplitude that is sensitive to desired microvascular effects and unwanted macrovascular effects. Aiming to suppress macrovascular effects in activation patterns, this BOLD-fMRI study evaluates brain activation during a verbal working memory task (2-back) in healthy volunteers (n=18) using the amplitude and phase components of the MRI signal. The use of the first time point as a phase reference allowed us to eliminate phase wrapping artifacts and increase the statistical power of 'phase' activation, and this information was used to filter out voxels with significant macrovascular (i.e., draining and pial veins) contribution in 'amplitude' activation patterns. Across subjects, the task produced large modulations of the relative phase in the occipital, dorsolateral prefrontal, and parietal cortices, suggesting a common distribution of draining veins in these regions across subjects, and in the rostral frontal cortex, probably associated to stimulus-correlated motion of the head. The phase filtering method partially suppressed BOLD responses in the superior and lateral prefrontal, parietal, and occipital cortices; therefore the commonly reported brain activation in these cortices during working memory tasks may include significant macrovascular contributions. This study suggests that the phase information embedded in the MRI signal can be used to suppress unwanted macrovascular contributions in fMRI studies.

Echo planar imaging at 4 Tesla with minimum acoustic noise.

PURPOSE: To minimize the acoustic sound pressure levels of single-shot echo planar imaging (EPI) acquisitions on high magnetic field MRI scanners. MATERIALS AND METHODS: The resonance frequencies of gradient coil vibrations, which depend on the coil length and the elastic properties of the materials in the coil assembly, were measured using piezoelectric transducers. The frequency of the EPI-readout train was adjusted to avoid the frequency ranges of mechanical resonances. RESULTS: Our MRI system exhibited two sharp mechanical resonances (at 720 and 1220 Hz) that can increase vibrational amplitudes up to six-fold. A small adjustment of the EPI-readout frequency made it possible to reduce the sound pressure level of EPI-based perfusion and functional MRI scans by 12 dB. CONCLUSION: Normal vibrational modes of MRI gradient coils can dramatically increase the sound pressure levels during echo planar imaging (EPI) scans. To minimize acoustic noise, the frequency of EPI-readout trains and the resonance frequencies of gradient coil vibrations need to be different.