Impact of cannabis use on brain metabolism using 31P and 1H magnetic resonance spectroscopy.

PURPOSE: This prospective cross-sectional study investigated the influence of regular cannabis use on brain metabolism in young cannabis users by using combined proton and phosphorus magnetic resonance spectroscopy. METHODS: The study was performed in 45 young cannabis users aged 18-30, who had been using cannabis on a regular basis over a period of at least 2 years and in 47 age-matched controls. We acquired 31P MRS data in different brain regions at 3T with a double-resonant 1H/31P head coil, anatomic images, and 1H MRS data with a standard 20-channel 1H head coil. Absolute concentration values of proton metabolites were obtained via calibration from tissue water as an internal reference, whereas a standard solution of 75 mmol/l KH2PO4 was used as an external reference for the calibration of phosphorus signals. RESULTS: We found an overall but not statistically significant lower concentration level of several proton and phosphorus metabolites in cannabis users compared to non-users. In particular, energy-related phosphates such as adenosine triphosphate (ATP) and inorganic phosphate (Pi) were reduced in all regions under investigation. Phosphocreatine (PCr) showed lowered values mainly in the left basal ganglia and the left frontal white matter. CONCLUSION: The results suggest that the increased risk of functional brain disorders observed in long-term cannabis users could be caused by an impairment of the energy metabolism of the brain, but this needs to be verified in future studies.

Functional correlates of neurological soft signs in heavy cannabis users.

Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination, sensorimotor integration and complex motor task performance. Abnormal NSS levels can also be detected in non-dependent individuals with heavy cannabis use (HCU), yet very little is known about the functional correlates underlying such deficits. Here, we used resting-state functional magnetic resonance imaging (MRI) to investigate associations between NSS and intrinsic neural activity (INA) in HCU (n = 21) and controls (n = 26). Compared with controls, individuals with HCU showed significantly higher NSS across all investigated subdomains. Three of these subdomains, that is, motor coordination, sensorimotor integration and complex motor task behaviour, were associated with specific use-dependent variables, particularly age of onset of cannabis use and current cannabis use. Between-group comparisons of INA revealed lower regional homogeneity (ReHo) in left precentral gyrus, left inferior occipital gyrus, right triangular pat of the inferior frontal gyrus and right precentral gyrus in HCU compared with controls. In addition, HCU showed also higher ReHo in right cerebellum and left postcentral gyrus compared with controls. Complex motor task behaviour in HCU was significantly related to INA in postcentral, inferior frontal and occipital cortices. Our findings indicate abnormal ReHo in HCU in regions associated with sensorimotor, executive control and visuomotor-integration processes. Importantly, we show associations between ReHo, cannabis-use behaviour and execution of complex motor tasks. Given convergent findings in manifest psychotic disorders, this study suggests an HCU endophenotype that may present with a cumulative risk for psychosis.

Multimodal MRI data fusion reveals distinct structural, functional and neurochemical correlates of heavy cannabis use.

Heavy cannabis use (HCU) is frequently associated with a plethora of cognitive, psychopathological and sensorimotor phenomena. Although HCU is frequent, specific patterns of abnormal brain structure and function underlying HCU in individuals presenting without cannabis-use disorder or other current and life-time major mental disorders are unclear at present. This multimodal magnetic resonance imaging (MRI) study examined resting-state functional MRI (rs-fMRI) and structural MRI (sMRI) data from 24 persons with HCU and 16 controls. Parallel independent component analysis (p-ICA) was used to examine covarying components among grey matter volume (GMV) maps computed from sMRI and intrinsic neural activity (INA), as derived from amplitude of low-frequency fluctuations (ALFF) maps computed from rs-fMRI data. Further, we used JuSpace toolbox for cross-modal correlations between MRI-based modalities with nuclear imaging derived estimates, to examine specific neurotransmitter system changes underlying HCU. We identified two transmodal components, which significantly differed between the HCU and controls (GMV: p = 0.01, ALFF p = 0.03, respectively). The GMV component comprised predominantly cerebello-temporo-thalamic regions, whereas the INA component included fronto-parietal regions. Across HCU, loading parameters of both components were significantly associated with distinct HCU behavior. Finally, significant associations between GMV and the serotonergic system as well as between INA and the serotonergic, dopaminergic and µ-opioid receptor system were detected. This study provides novel multimodal neuromechanistic insights into HCU suggesting co-altered structure/function-interactions in neural systems subserving cognitive and sensorimotor functions.

Structural correlates of sensorimotor dysfunction in heavy cannabis users.

Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination and sensorimotor integration. Whether such abnormalities may also apply to non-dependent individuals with heavy cannabis use (HCU) is unknown, as much as the neural correlates underlying such deficits. In this study, we investigated associations between NSS and gray matter volume (GMV) in males with HCU and male controls. Twenty-four persons with HCU and 17 controls were examined using standardized assessment of NSS and structural magnetic resonance imaging (MRI) at 3 T. GMV was calculated using voxel-based morphometry algorithms provided by the Computational Anatomy Toolbox (CAT12). Individuals with HCU showed higher NSS total scores compared to controls. In particular, significant NSS-subdomain effects were found for "motor coordination" (MoCo), "complex motor tasks" (CoMT), and "hard signs" (HS) expression in HCU (p < 0.05, Bonferroni-corrected). Compared to controls, persons with HCU showed significant NSS/GMV interactions in putamen and inferior frontal cortex (MoCo), right cerebellum (CoMT) and middle and superior frontal cortices, and bilateral precentral cortex and thalamus (HS). In between-group analyses, individuals with HCU showed lower GMV in the right anterior orbital and precentral gyrus, as well as higher GMV in the right superior frontal gyrus and left supplementary motor cortex compared to controls. The data support the notion of abnormal sensorimotor performance associated with HCU. The data also provide a neuromechanistic understanding of such deficits, particularly with respect to aberrant cortical-thalamic-cerebellar-cortical circuit.

Cognition and Cortical Thickness in Heavy Cannabis Users.

INTRODUCTION: Acute and long-term adverse effects of heavy cannabis use (HCU) on neurocognitive function have been suggested, as much as regional changes of brain volume. However, little is known about the relationship between impaired cognition and brain structure in individuals with HCU. OBJECTIVE: Here, we investigated associations between cognition and cortical thickness (CT) in males with HCU and male controls. METHODS: Twenty-six individuals with HCU and 20 controls were examined using a comprehensive neuropsychological test battery and high-resolution structural MRI at 3T. CT was calculated using the Computational Anatomy Toolbox (CAT12). RESULTS: Individuals with HCU differed from controls with respect to verbal learning performance and verbal working memory only. Individuals with HCU showed reduced CT in medial temporal, orbitofrontal, and cingulate regions, as well as in areas of the middle temporal and fusiform cortex (peak voxel family-wise error-corrected p < 0.001, followed by empirically determined correction for spatial extent) compared to HC. Verbal learning performance was associated with right entorhinal and left orbitofrontal CT reductions. Entorhinal CT was also significantly associated with amount and frequency of current weekly cannabis use. CONCLUSIONS: The data support the notion of domain-specific cognitive impairment in individuals with HCU and provide a neuromechanistic understanding of such deficits, particularly with respect to abnormal CT in brain areas associated with long-term memory processing.

Mindfulness-based interventions modulate structural network strength in patients with opioid dependence.

Mindfulness-based interventions (MBI) are increasingly used in the treatment of patients with mental disorders, in particular in individuals presenting with affective disorders or in patients exhibiting abnormal levels of impulsive behavior. MBI have been also offered to patients with substance use disorders, where such treatment options may yield considerable clinical effects. Neural effects associated with MBI have been increasingly acknowledged, but is unknown whether MBI exert specific effects on brain structure in patients with substance use disorders. In this study, we investigated 19 inpatients with opioid dependence receiving treatment-as-usual (TAU, n = 9) or additional MBI (n = 10). Structural magnetic resonance imaging data were acquired before and after four weeks of treatment. Source-based morphometry was used to investigate modulation of structural networks after treatment. Both treatment modalities led to significant clinical improvement. Patients receiving MBI showed a significant change in distress tolerance levels. An increase in bilateral striatal/insular and prefrontal/cingulate network strength was found in patients receiving MBI compared to individuals receiving TAU. Prefrontal/cingulate cortical network strength was associated with impulsivity levels. These findings suggest that MBI can have a recognizable role in treatment of substance use disorders and that neural effects of MBI may be captured in terms of frontostriatal structural network change.