Neurovascular Uncoupling: Multimodal Imaging Delineates the Acute Effects of 3,4-Methylenedioxymethamphetamine.

Psychedelic compounds such as 3,4-methylenedioxymethamphetamine (MDMA) have attracted increasing interest in recent years because of their therapeutic potential in psychiatric disorders. To understand the acute effects of psychedelic drugs in vivo, blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI) has been widely used. In particular, fMRI studies have suggested that MDMA leads to inhibition of brain activity, challenging previous hypotheses indicating mainly excitatory effects based, among others, on increased metabolism shown by F-FDG functional PET (fPET).

Striatal and prefrontal D2R and SERT distributions contrastingly correlate with default-mode connectivity.

Although brain research has taken important strides in recent decades, the interaction and coupling of its different physiological levels is still not elucidated. Specifically, the molecular substrates of resting-state functional connectivity (rs-FC) remain poorly understood. The aim of this study was elucidating interactions between dopamine D2 receptors (D2R) and serotonin transporter (SERT) availabilities in the striatum (CPu) and medial prefrontal cortex (mPFC), two of the main dopaminergic and serotonergic projection areas, and the default-mode network.

Elucidating the complementarity of resting-state networks derived from dynamic [F]FDG and hemodynamic fluctuations using simultaneous small-animal PET/MRI.

Functional connectivity (FC) and resting-state network (RSN) analyses using functional magnetic resonance imaging (fMRI) have evolved into a growing field of research and have provided useful biomarkers for the assessment of brain function in neurological disorders. However, the underlying mechanisms of the blood oxygen level-dependant (BOLD) signal are not fully resolved due to its inherent complexity. In contrast, [F]fluorodeoxyglucose positron emission tomography ([F]FDG-PET) has been shown to provide a more direct measure of local synaptic activity and may have additional value for the readout and interpretation of brain connectivity.

Interregional causal influences of brain metabolic activity reveal the spread of aging effects during normal aging.

During healthy brain aging, different brain regions show anatomical or functional declines at different rates, and some regions may show compensatory increases in functional activity. However, few studies have explored interregional influences of brain activity during the aging process. We proposed a causality analysis framework combining high dimensionality independent component analysis (ICA), Granger causality, and least absolute shrinkage and selection operator regression on longitudinal brain metabolic activity data measured by Fludeoxyglucose positron emission tomography (FDG-PET).

Functional resting-state brain connectivity is accompanied by dynamic correlations of application-dependent [F]FDG PET-tracer fluctuations.

Brain function is characterized by a convolution of various biochemical and physiological processes, raising the interest whether resting-state functional connectivity derived from hemodynamic scales shows underlying metabolic synchronies. Increasing evidence suggests that metabolic connectivity based on glucose consumption associated PET recordings may serve as a marker of cognitive functions and neuropathologies. However, to what extent fMRI-derived resting-state brain connectivity can also be characterized based on dynamic fluctuations of glucose metabolism and how metabolic connectivity is influenced by [F]FDG pharmacokinetics remains unsolved.