This study used resting state functional magnetic resonance imaging (rsfMRI) to investigate whole brain networks in patients with persistent postural perceptual dizziness (PPPD). We compared rsfMRI data from 38 patients with PPPD and 38 healthy controls using whole brain and region of interest analyses. We examined correlations among connectivity and clinical variables and tested the ability of a machine learning algorithm to classify subjects using rsfMRI results. Patients with PPPD showed: (a) increased connectivity of subcallosal cortex with left superior lateral occipital cortex and left middle frontal gyrus, (b) decreased connectivity of left hippocampus with bilateral central opercular cortices, left posterior opercular cortex, right insular cortex and cerebellum, and (c) decreased connectivity between right nucleus accumbens and anterior left temporal fusiform cortex. After controlling for anxiety and depression as covariates, patients with PPPD still showed decreased connectivity between left hippocampus and right inferior frontal gyrus, bilateral temporal lobes, bilateral insular cortices, bilateral central opercular cortex, left parietal opercular cortex, bilateral occipital lobes and cerebellum (bilateral lobules VI and V, and left I-IV). Dizziness handicap, anxiety, and depression correlated with connectivity in clinically meaningful brain regions. The machine learning algorithm correctly classified patients and controls with a sensitivity of 78.4%, specificity of 76.9%, and area under the curve = 0.88 using 11 connectivity parameters. Patients with PPPD showed reduced connectivity among the areas involved in multisensory vestibular processing and spatial cognition, but increased connectivity in networks linking visual and emotional processing. Connectivity patterns may become an imaging biomarker of PPPD.

Our results suggest that the breakdown of DMN connectivity may occur in the early stage of MCI.

We present a wide-field quantitative label-free imaging of mouse brain tissue slices with sub-micrometre resolution, employing holographic microscopy and an automated scanning platform. From the measured light field images, scattering coefficients and anisotropies are quantitatively retrieved by using the modified the scattering-phase theorem, which enables access to structural information about brain tissues. As a proof of principle, we demonstrate that these scattering parameters enable us to quantitatively address structural alteration in the brain tissues of mice with Alzheimer’s disease.

Background/Aims: Endothelial glycocalyx refers to the proteoglycan or glycoprotein layer of vessel walls and has critical physiological functions. Cerebral glycocalyx may have additional functions considering the blood-brain barrier and other features. However, the assessment of it has only been performed ex vivo, which includes processes presumably damaging the glycocalyx layer. Here we visualize and characterize the cerebral endothelial glycocalyx in vivo. Methods: We visualized and quantified the cerebral endothelial glycocalyx in vivo under a 2-photon microscope by tagging glycocalyx and vessel lumen with wheat germ agglutinin lectin and dextran, respectively. The radial intensity was analyzed to measure the thickness of the cerebral endothelial glycocalyx in each vessel type. Results: Cerebral arteries and capillaries have an intact endothelial glycocalyx, but veins and venules do not. The thickness of the glycocalyx layer in pial arteries, penetrating arteries, and capillaries was different; however, it was not correlated with the vessel diameter within each vessel type. Conclusion: We characterized the distribution of the cerebral endothelial glycocalyx in vivo. Compared to the results from ex vivo studies, the layer is thicker, indicating that the layer may be damaged in ex vivo systems. We also observed an inhomogeneous cerebral endothelial glycocalyx distribution that might reflect the functional heterogeneity of the vessel type.