The theory on the glymphatic convection mechanism of cerebrospinal fluid holds that cardiac pulsations in part pump cerebrospinal fluid from the peri-arterial spaces through the extracellular tissue into the peri-venous spaces facilitated by aquaporin water channels. Since cardiac pulses cannot be the sole mechanism of glymphatic propulsion, we searched for additional cerebrospinal fluid pulsations in the human brain with ultra-fast magnetic resonance encephalography. We detected three types of physiological mechanisms affecting cerebral cerebrospinal fluid pulsations: cardiac, respiratory, and very low frequency pulsations. The cardiac pulsations induce a negative magnetic resonance encephalography signal change in peri-arterial regions that extends centrifugally and covers the brain in &1 Hz cycles. The respiratory &0.3 Hz pulsations are centripetal periodical pulses that occur dominantly in peri-venous areas. The third type of pulsation was very low frequency (VLF 0.001-0.023 Hz) and low frequency (LF 0.023-0.73 Hz) waves that both propagate with unique spatiotemporal patterns. Our findings using critically sampled magnetic resonance encephalography open a new view into cerebral fluid dynamics. Since glymphatic system failure may precede protein accumulations in diseases such as Alzheimer's dementia, this methodological advance offers a novel approach to image brain fluid dynamics that potentially can enable early detection and intervention in neurodegenerative diseases.

Chemical exchange saturation transfer (CEST) and spin-locking (SL) experiments were both able to probe the exchange process between protons of nonequivalent chemical environments. To compare the characteristics of the CEST and SL approaches in the study of chemical exchange effects, we performed CEST and SL experiments at varied pH and concentrated metabolite phantoms with exchangeable amide, amine, and hydroxyl protons at 9.4 T. Our results show that: (i) on-resonance SL is most sensitive to chemical exchanges in the intermediate-exchange regime and is able to detect hydroxyl and amine protons on a millimolar concentration scale. Off-resonance SL and CEST approaches are sensitive to slow-exchanging protons when an optimal SL or saturation pulse power matches the exchanging rate, respectively. Recently, there has been an increasing number of in vivo studies that have used the chemical exchange (CE) effect to probe the tissue microenvironment and provide novel imaging contrasts that are not available from conventional MRI techniques. Most of these studies adopted either a chemical exchange saturation transfer (CEST) or a spinlocking (SL) approach to detect contrast in tissue pH or the population of labile protons, which have a Larmor frequency different from water. Ideally, a CE-sensitive imaging contrast should have good sensitivity and vary monotonically with pH and linearly with labile proton concentration. The CE contrast is determined by many parameters, such as the exchange rate between water and labile protons (k ex ), the difference in their Larmor frequencies (d), the populations of the exchangeable protons, water T 1 , and the magnetic field strength (B 0 ). The CE effect in MRI is also highly sensitive to a ratio of k ex to d. k ex /d, which indicates the CE kinetics, is usually divided into three regimes: slow (k ex /d ( 1), intermediate (k ex /d $ 1), and fast exchange (k ex /d ) 1). CEST techniques are mostly applied at the slow-or slow-to intermediate-exchange regime (1,2), whilereas the CE is often assumed to occur at the fast-exchange regime for SL applications (3,4).In CEST studies that are based upon endogenous contrast, selective off-resonance irradiation of labile protons of protein or peptide side chains attenuates the water signal via exchange between these labile protons and bulk water. The signal intensity as a function of irradiation frequency, often referred to as the Z-spectrum, can be expressed by the magnetization transfer ratio (MTR):where V is the frequency offset with respect to water. In practice, the conventional non-CE magnetization transfer effect and direct water saturation (or the so-called spillover effect) also affect the Z-spectrum, and these effects are assumed to be symmetrical around the water resonance frequency. To minimize these non-CE contributions, CEST contrast in MRI is usually extracted from two images-one acquired with off-resonance irradiation on the targeted labile proton and the other as a control with opposite offset frequency from the water (5). The norma...

We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture.

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Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, ‘ground truth’ validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how “functional connectivity” from fMRI and “tractographic connectivity” from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.

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The findings indicate that sequences are suitable for quantitative in vivo assessment of articular cartilage at 3 T. Magn Reson Med 77:1265-1275, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm 2 ). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture.