Dissociable effects of cannabis with and without cannabidiol on the human brain's resting-state functional connectivity.

BACKGROUND: Two major constituents of cannabis are Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). THC is the main psychoactive component; CBD may buffer the user against the harmful effects of THC. AIMS: We examined the effects of two strains of cannabis and placebo on the human brain's resting-state networks using fMRI. METHODS: Seventeen healthy volunteers (experienced with cannabis, but not regular users) underwent three drug treatments and scanning sessions. Treatments were cannabis containing THC (Cann-CBD; 8 mg THC), cannabis containing THC with CBD (Cann+CBD; 8 mg THC + 10 mg CBD), and matched placebo cannabis. Seed-based resting-state functional connectivity analyses were performed on three brain networks: the default mode (DMN; defined by positive connectivity with the posterior cingulate cortex: PCC+), executive control (ECN; defined by negative connectivity with the posterior cingulate cortex: PCC-) and salience (SAL; defined by positive connectivity with the anterior insula: AI+) network. RESULTS: Reductions in functional connectivity (relative to placebo) were seen in the DMN (PCC+) and SAL (AI+) networks for both strains of cannabis, with spatially dissociable effects. Across the entire salience network (AI+), Cann-CBD reduced connectivity relative to Cann+CBD. The PCC in the DMN was specifically disrupted by Cann-CBD, and this effect correlated with subjective drug effects, including feeling 'stoned' and 'high'. CONCLUSIONS: THC disrupts the DMN, and the PCC is a key brain region involved in the subjective experience of THC intoxication. CBD restores disruption of the salience network by THC, which may explain its potential to treat disorders of salience such as psychosis and addiction.

A comprehensive evaluation of increasing temporal resolution with multiband-accelerated protocols and effects on statistical outcome measures in fMRI.

Accelerated functional Magnetic Resonance Imaging (fMRI) with 'multiband' protocols is now relatively widespread. These protocols can be used to dramatically reduce the repetition time (TR) and produce a time-series sampled at a higher temporal resolution, which may produce benefits in the statistical methods typically used to analyse fMRI data. We tested the effects of higher temporal resolutions for fMRI on statistical outcome measures in a comprehensive manner on two different MRI scanner platforms. Spatial resolution was maintained at a constant of 3 mm isotropic voxels, and an in-plane acceleration factor of 2 was used for all experiments. Experiment 1 tested a range of acceleration factors (1-6) against a standard EPI protocol on a single composite task that mapped a number of basic sensory, motor, and cognitive networks. Experiment 2 compared the standard protocol with acceleration factors of 2 and 3 on both resting-state and two task paradigms (an N-back task, and faces/places task), with a number of different analysis approaches. Results from experiment 1 showed modest but relatively inconsistent effects of the higher sampling rate on statistical outcome measures. Experiment 2 showed strong benefits of the multiband protocols on results derived from resting-state data, but more varied effects on results from the task paradigms. Notably, the multiband protocols were superior when Multi-Voxel Pattern Analysis was used to interrogate the faces/places data, but showed less benefit in conventional General Linear Model analyses of the same data. In general, ROI-derived measures of statistical effects benefitted only modestly from higher sampling resolution, with greater effects seen when using a measure of the top range of statistical values. Across both experiments, results from the two scanner platforms were broadly comparable. The statistical benefits of high temporal resolution fMRI with multiband protocols may therefore depend on a number of factors, including the nature of the investigation (resting-state vs. task-based), the experimental design, the particular statistical outcome measure, and the type of analysis used.

Investigating the neural correlates of smoking: Feasibility and results of combining electronic cigarettes with fMRI.

Cigarette addiction is driven partly by the physiological effects of nicotine, but also by the distinctive sensory and behavioural aspects of smoking, and understanding the neural effects of such processes is vital. There are many practical difficulties associated with subjects smoking in the modern neuroscientific laboratory environment, however electronic cigarettes obviate many of these issues, and provide a close simulation of smoking tobacco cigarettes. We have examined the neural effects of 'smoking' electronic cigarettes with concurrent functional Magnetic Resonance Imaging (fMRI). The results demonstrate the feasibility of using these devices in the MRI environment, and show brain activation in a network of cortical (motor cortex, insula, cingulate, amygdala) and sub-cortical (putamen, thalamus, globus pallidus, cerebellum) regions. Concomitant relative deactivations were seen in the ventral striatum and orbitofrontal cortex. These results reveal the brain processes involved in (simulated) smoking for the first time, and validate a novel approach to the study of smoking, and addiction more generally.