To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach.

C-type lectin-like receptor 2 (CLEC-2) is considered as a potential drug target in settings of wound healing, inflammation, and infection. A potential barrier to this is evidence that CLEC-2 and its ligand podoplanin play a critical role in preventing lymphatic vessel blood filling in mice throughout life. In this study, this aspect of CLEC-2/podoplanin function is investigated in more detail using new and established mouse models of CLEC-2 and podoplanin deficiency, and models of acute and chronic vascular remodeling. We report that CLEC-2 expression on platelets is not required to maintain a barrier between the blood and lymphatic systems in unchallenged mice, post-development. However, under certain conditions of chronic vascular remodeling, such as during tumorigenesis, deficiency in CLEC-2 can lead to lymphatic vessel blood filling. These data provide a new understanding of the function of CLEC-2 in adult mice and confirm the essential nature of CLEC-2-driven platelet activation in vascular developmental programs. This work expands our understanding of how lymphatic blood filling is prevented by CLEC-2-dependent platelet function and provides a context for the development of safe targeting strategies for CLEC-2 and podoplanin.

Brodmann's 100-year-old summary map has been widely used for cortical localization in neuroscience. There is a pressing need to update this map using non-invasive, high-resolution and reproducible data, in a way that captures individual variability. We demonstrate here that standard HARDI data has sufficiently diverse directional variation among grey matter regions to inform parcellation into distinct functional regions, and that this variation is reproducible across scans. This characterization of the signal variation as non-random and reproducible is the critical condition for successful cortical parcellation using HARDI data. This paper is a first step towards an individual cortex-wide map of grey matter microstructure, The gray/white matter and pial boundaries were identified on the high-resolution structural MRI images. Two HARDI data sets were collected from each individual and aligned with the corresponding structural image. At each vertex point on the surface tessellation, the diffusion-weighted signal was extracted from each image in the HARDI data set at a point, half way between gray/white matter and pial boundaries. We then derived several features of the HARDI profile with respect to the local cortical normal direction, as well as several fully orientationally invariant features. These features were taken as a fingerprint of the underlying grey matter tissue, and used to distinguish separate cortical areas. A support-vector machine classifier, trained on three distinct areas in repeat 1 achieved 80-82% correct classification of the same three areas in the unseen data from repeat 2 in three volunteers. Though gray matter anisotropy has been mostly overlooked hitherto, this approach may eventually form the foundation of a new cortical parcellation method in living humans. Our approach allows for further studies on the consistency of HARDI based parcellation across subjects and comparison with independent microstructural measures such as ex-vivo histology.

The subthalamic nucleus (STN) is a small, glutamatergic nucleus situated in the diencephalon. A critical component of normal motor function, it has become a key target for deep brain stimulation in the treatment of Parkinson's disease. Animal studies have demonstrated the existence of three functional sub-zones but these have never been shown conclusively in humans. In this work, a data driven method with diffusion weighted imaging demonstrated that three distinct clusters exist within the human STN based on brain connectivity profiles. The STN was successfully sub-parcellated into these regions, demonstrating good correspondence with that described in the animal literature. The local connectivity of each sub-region supported the hypothesis of bilateral limbic, associative and motor regions occupying the anterior, mid and posterior portions of the nucleus respectively. This study is the first to achieve in-vivo, non-invasive anatomical parcellation of the human STN into three anatomical zones within normal diagnostic scan times, which has important future implications for deep brain stimulation surgery.

Diffusion tensor imaging is widely used in research and clinical applications, but still suffers from substantial artifacts. Here, we focus on vibrations induced by strong diffusion gradients in diffusion tensor imaging, causing an echo shift in k-space and consequential signal-loss. We refined the model of vibration-induced echo shifts, showing that asymmetric k-space coverage in widely used Partial Fourier acquisitions results in locally differing signal loss in images acquired with reversed phase encoding direction (blip-up/blip-down). We implemented a correction of vibration artifacts in diffusion tensor imaging using phase-encoding reversal (COVIPER) by combining blip-up and blip-down images, each weighted by a function of its local tensor-fit error. COVIPER was validated against low vibration reference data, resulting in an error reduction of about 72% in fractional anisotropy maps. COVIPER can be combined with other corrections based on phase encoding reversal, providing a comprehensive correction for eddy currents, susceptibility-related distortions and vibration artifact reduction.

Decision making requires integrating knowledge gathered from personal experiences with advice from others. The neural underpinnings of the process of arbitrating between information sources has not been fully elucidated. In this study, we formalized arbitration as the relative precision of predictions, afforded by each learning system, using hierarchical Bayesian modeling. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and/or self-sampled outcomes. Decision confidence, as measured by the number of points participants wagered on their predictions, varied with our definition of arbitration as a ratio of precisions. Functional neuroimaging demonstrated that arbitration signals were independent of decision confidence and involved modality-specific brain regions. Arbitrating in favor of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain, whereas arbitrating in favor of social information engaged the ventromedial prefrontal cortex and the amygdala. These findings indicate that relative precision captures arbitration between social and individual learning systems at both behavioral and neural levels.

Megakaryocytes (MKs), the precursors of blood platelets, are large, polyploid cells residing mainly in the bone marrow. We have previously shown that balanced signaling of the Rho GTPases RhoA and Cdc42 is critical for correct MK localization at bone marrow sinusoids in vivo. Using conditional RhoA/Cdc42 double-knockout (DKO) mice, we reveal here that RhoA/Cdc42 signaling is dispensable for the process of polyploidization in MKs but essential for cytoplasmic MK maturation. Proplatelet formation is virtually abrogated in the absence of RhoA/Cdc42 and leads to severe macrothrombocytopenia in DKO animals. The MK maturation defect is associated with downregulation of myosin light chain 2 (MLC2) and β1-tubulin, as well as an upregulation of LIM kinase 1 and cofilin-1 at both the mRNA and protein level and can be linked to impaired MKL1/SRF signaling. Our findings demonstrate that MK endomitosis and cytoplasmic maturation are separately regulated processes, and the latter is critically controlled by RhoA/Cdc42.

Myelin has long been the target of neuroimaging research. However, most available techniques can only provide a voxel-averaged estimate of myelin content. In the human brain, white matter fiber pathways connecting different brain areas and carrying different functions often cross each other in the same voxel. A measure that can differentiate the degree of myelination of crossing fibers would provide a more specific marker of myelination.

Physiological processes-such as, the brain's resting-state electrical activity or hemodynamic fluctuations-exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for the topology of multifractal metrics free of the masking effect of the underlying random noise.

Cortical area parcellation is a challenging problem that is often approached by combining structural imaging (e.g., quantitative T1, diffusion-based connectivity) with functional imaging (e.g., task activations, topological mapping, resting state correlations). Diffusion MRI (dMRI) has been widely adopted to analyse white matter microstructure, but scarcely used to distinguish grey matter regions because of the reduced anisotropy there. Nevertheless, differences in the texture of the cortical 'fabric' have long been mapped by histologists to distinguish cortical areas. Reliable area-specific contrast in the dMRI signal has previously been demonstrated in selected occipital and sensorimotor areas. We expand upon these findings by testing several diffusion-based feature sets in a series of classification tasks. Using Human Connectome Project (HCP) 3T datasets and a supervised learning approach, we demonstrate that diffusion MRI is sensitive to architectonic differences between a large number of different cortical areas defined in the HCP parcellation. By employing a surface-based cortical imaging pipeline, which defines diffusion features relative to local cortical surface orientation, we show that we can differentiate areas from their neighbours with higher accuracy than when using only fractional anisotropy or mean diffusivity. The results suggest that grey matter diffusion may provide a new, independent source of information for dividing up the cortex.

Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM) classification methods we aimed to investigate whether MRI data, collected in adolescence, could be used to predict whether an individual had been born preterm or at term. To this end we collected T1-weighted anatomical MRI data from 143 individuals (69 controls, mean age 14.6y). The inclusion criteria for those born preterm were birth weight ≤ 1500g and gestational age < 37w. A linear SVM was trained on the grey matter segment of MR images in two different ways. First, all the individuals were used for training and classification was performed by the leave-one-out method, yielding 93% correct classification (sensitivity = 0.905, specificity = 0.942). Separately, a random half of the available data were used for training twice and each time the other, unseen, half of the data was classified, resulting 86% and 91% accurate classifications. Both gestational age (R = -0.24, p<0.04) and birth weight (R = -0.51, p < 0.001) correlated with the distance to decision boundary within the group of individuals born preterm. Statistically significant correlations were also found between IQ (R = -0.30, p < 0.001) and the distance to decision boundary. Those born small for gestational age did not form a separate subgroup in these analyses. The high rate of correct classification by the SVM motivates further investigation. The long-term goal is to automatically and non-invasively predict the outcome of preterm-born individuals on an individual basis using as early a scan as possible.

During critical periods of food shortage or variable climatic conditions, the choice of an appropriate host can increase the survival and reproductive performance of parasites. In turn, one of the unique adaptations to periodical food shortages is hibernation, which is often found among insectivorous bat species in the temperate zone. While hibernating, bats are completely defenseless against both predators and ectoparasites, their immune and endocrine systems are diminished, and survival is dependent on the accumulated fat reserves. Differences in the health status or in the rate of consumption of the resources might also explain species-specific differences in ectoparasite abundance, especially between closely related host species, such as the greater mouse-eared bat (Myotis myotis) and the lesser mouse-eared bat (M. blythii) during hibernation. In the present study, the abundance of two ecologically distinct (summer and winter) types of ectoparasites was examined in terms of its influence on the body condition and hemoglobin content of the two host species. The effects of demographic factors, such as host sex and age, were also investigated. Despite a similar pattern of deteriorating body condition and hemoglobin concentration, M. myotis was more parasitized than was M. blythii. The marked decrease in hemoglobin content in first-year females of both host species correlated with the highest parasite load and indicated a risk of anemia. At the intraspecific level, ectoparasite abundance was not correlated with body condition (resources), but it negatively affected hemoglobin content; however, this mostly concerned M. blythii, which had a lower parasite load. Therefore, it can be concluded that interspecific differences in ectoparasite abundance may result from parasites selecting the host species that is less sensitive to their activity. In turn, in summer ectoparasites, the preference for female hosts is probably attributable to the likelihood of reinfection rather than to an effect of host resources or health status. The absence of sex-based preferences in winter ectoparasites could be explained by equal host availability.

This article will be positioned on our previous work demonstrating the importance of adhering to a carefully selected set of criteria when choosing the suitable method from those available ensuring its adequate performance when applied to real temporal signals, such as fMRI BOLD, to evaluate one important facet of their behavior, fractality. Earlier, we have reviewed on a range of monofractal tools and evaluated their performance. Given the advance in the fractal field, in this article we will discuss the most widely used implementations of multifractal analyses, too. Our recommended flowchart for the fractal characterization of spontaneous, low frequency fluctuations in fMRI BOLD will be used as the framework for this article to make certain that it will provide a hands-on experience for the reader in handling the perplexed issues of fractal analysis. The reason why this particular signal modality and its fractal analysis has been chosen was due to its high impact on today's neuroscience given it had powerfully emerged as a new way of interpreting the complex functioning of the brain (see "intrinsic activity"). The reader will first be presented with the basic concepts of mono and multifractal time series analyses, followed by some of the most relevant implementations, characterization by numerical approaches. The notion of the dichotomy of fractional Gaussian noise and fractional Brownian motion signal classes and their impact on fractal time series analyses will be thoroughly discussed as the central theme of our application strategy. Sources of pitfalls and way how to avoid them will be identified followed by a demonstration on fractal studies of fMRI BOLD taken from the literature and that of our own in an attempt to consolidate the best practice in fractal analysis of empirical fMRI BOLD signals mapped throughout the brain as an exemplary case of potentially wide interest.

Regulator of G-protein signaling 18 (RGS18) is a GTPase-activating protein that turns off Gq signaling in platelets. RGS18 is regulated by binding to the adaptor protein 14-3-3 via phosphorylated serine residues S49 and S218 on RGS18. In this study we confirm that thrombin, thromboxane A2, or ADP stimulate the interaction of RGS18 and 14-3-3 by increasing the phosphorylation of S49. Cyclic AMP- and cyclic GMP-dependent kinases (PKA, PKG) inhibit the interaction of RGS18 and 14-3-3 by phosphorylating S216. To understand the effect of S216 phosphorylation we studied the phosphorylation kinetics of S49, S216, and S218 using Phos-tag gels and phosphorylation site-specific antibodies in transfected cells and in platelets. Cyclic nucleotide-induced detachment of 14-3-3 from RGS18 coincides initially with double phosphorylation of S216 and S218. This is followed by dephosphorylation of S49 and S218. Dephosphorylation of S49 and S218 might be mediated by protein phosphatase 1 (PP1) which is linked to RGS18 by the regulatory subunit PPP1R9B (spinophilin). We conclude that PKA and PKG induced S216 phosphorylation triggers the dephosphorylation of the 14-3-3 binding sites of RGS18 in platelets.

Executive functions are frequently a weakness in children born preterm. We examined associations of executive functions and general cognitive abilities with brain structure in preterm born adolescents who were born with appropriate weight for gestational age and who have no radiological signs of preterm brain injury on neuroimaging.

MYH9-related disease patients with mutations in the contractile protein nonmuscle myosin heavy chain IIA display, among others, macrothrombocytopenia and a mild-to-moderate bleeding tendency. In this study, we used three mouse lines, each with one point mutation in the Myh9 gene at positions 702, 1424, or 1841, to investigate mechanisms underlying the increased bleeding risk. Agonist-induced activation of Myh9 mutant platelets was comparable to controls. However, myosin light chain phosphorylation after activation was reduced in mutant platelets, which displayed altered biophysical characteristics and generated lower adhesion, interaction, and traction forces. Treatment with tranexamic acid restored clot retraction in the presence of tPA and reduced bleeding. We verified our findings from the mutant mice with platelets from patients with the respective mutation. These data suggest that reduced platelet forces lead to an increased bleeding tendency in patients with MYH9-related disease, and treatment with tranexamic acid can improve the hemostatic function.

The immunoreceptor tyrosine-based inhibition motif (ITIM)-containing receptor G6b-B is critical for platelet production and activation. Loss of G6b-B results in severe macrothrombocytopenia, myelofibrosis and aberrant platelet function in mice and humans. Using a combination of immunohistochemistry, affinity chromatography and proteomics, we identified the extracellular matrix heparan sulfate (HS) proteoglycan perlecan as a G6b-B binding partner. Subsequent in vitro biochemical studies and a cell-based genetic screen demonstrated that the interaction is specifically mediated by the HS chains of perlecan. Biophysical analysis revealed that heparin forms a high-affinity complex with G6b-B and mediates dimerization. Using platelets from humans and genetically modified mice, we demonstrate that binding of G6b-B to HS and multivalent heparin inhibits platelet and megakaryocyte function by inducing downstream signaling via the tyrosine phosphatases Shp1 and Shp2. Our findings provide novel insights into how G6b-B is regulated and contribute to our understanding of the interaction of megakaryocytes and platelets with glycans.

Individuals with developmental prosopagnosia (DP) experience face recognition impairments despite normal intellect and low-level vision and no history of brain damage. Prior studies using diffusion tensor imaging in small samples of subjects with DP (n=6 or n=8) offer conflicting views on the neurobiological bases for DP, with one suggesting white matter differences in two major long-range tracts running through the temporal cortex, and another suggesting white matter differences confined to fibers local to ventral temporal face-specific functional regions of interest (fROIs) in the fusiform gyrus. Here, we address these inconsistent findings using a comprehensive set of analyzes in a sample of DP subjects larger than both prior studies combined (n=16). While we found no microstructural differences in long-range tracts between DP and age-matched control participants, we found differences local to face-specific fROIs, and relationships between these microstructural measures with face recognition ability. We conclude that subtle differences in local rather than long-range tracts in the ventral temporal lobe are more likely associated with developmental prosopagnosia.

Traumatic spinal cord injury (SCI) leads to disruption of axonal architecture and macroscopic tissue loss with impaired information flow between the brain and spinal cord-the presumed basis of ensuing clinical impairment.

In diffusion MRI, the actual b-value played out on the scanner may deviate from the nominal value due to magnetic field imperfections. A simple image-based correction method for this problem is presented.