Virtual in vivo interactive dissection of white matter fasciculi in the human brain.

This work reports the use of diffusion tensor magnetic resonance tractography to visualize the three-dimensional (3D) structure of the major white matter fasciculi within living human brain. Specifically, we applied this technique to visualize in vivo (i) the superior longitudinal (arcuate) fasciculus, (ii) the inferior longitudinal fasciculus, (iii) the superior fronto-occipital (subcallosal) fasciculus, (iv) the inferior fronto-occipital fasciculus, (v) the uncinate fasciculus, (vi) the cingulum, (vii) the anterior commissure, (viii) the corpus callosum, (ix) the internal capsule, and (x) the fornix. These fasciculi were first isolated and were then interactively displayed as a 3D-rendered object. The virtual tract maps obtained in vivo using this approach were faithful to the classical descriptions of white matter anatomy that have previously been documented in postmortem studies. Since we have been able to interactively delineate and visualize white matter fasciculi over their entire length in vivo, in a manner that has only previously been possible by histological means, virtual in vivo interactive dissection (VIVID) adds a new dimension to anatomical descriptions of the living human brain

Fractal and stereological analyses of insulin-induced rat exocrine pancreas remodelling

Background: The effect of insulin on the endocrine pancreas has been the subject of extensive study, but quantitative morphometric investigations of the exocrine pancreas are scarce. This study was therefore undertaken to investigate the effect of acute and chronic insulin administration (two doses, 0.4 IU and 4 IU) on the morphology of rat pancreas acini. Materials and methods: Semi-fine sections stained with methylene blue and basic fuchsine or haematoxylin and eosin-stained 5-micrometer thick paraffin sections were used for fractal and stereological analysis of exocrine acini. Acute insulin treatment, independent of applied doses increased fractal dimension in line with decreased lacunarity of pancreas acini. Chronic low dose insulin decreased fractal dimension and increased lacunarity of pancreas acini, but a high dose had the opposite effect. The volume densities (Vv) of cytoplasm, granules and nucleus are affected differently: acute low dose and high chronic dose significantly decreased granules Vv, and in line increased cytoplasmic Vv, whereas other examined structures showed slight changes without statistical significance. Results: The results obtained from this investigation indicate that insulin treatment induced structural remodelling of the exocrine pancreas suggesting a substantial role of insulin in its functioning. Conclusions: Additionally, we showed that fine architectural changes in acini could be detected by fractal analysis, suggesting this method as an alternative or addition to routine stereology

Random noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections

The empirical origin of random noise is described, its influence on DTI variables is illustrated by a review of numerical and in vivo studies supplemented by new simulations investigating high noise levels. A stochastic model of noise propagation is presented to structure noise impact in DTI. Finally, basics of voxelwise and spatial denoising procedures are presented. Recent denoising procedures are reviewed and consequences of the stochastic model for convenient denoising strategies are discussed

Measuring latency distribution of transcallosal fibers using transcranial magnetic stimulation

Background: Neuroimaging technology is being developed to enable non-invasive mapping of the latency distribution of cortical projection pathways in white matter, and correlative clinical neurophysiological techniques would be valuable for mutual verification. Interhemispheric interaction through the corpus callosum can be measured with interhemispheric facilitation and inhibition using transcranial magnetic stimulation. Objective: To develop a method for determining the latency distribution of the transcallosal fibers with transcranial magnetic stimulation. Methods: We measured the precise time courses of interhemispheric facilitation and inhibition with a conditioning-test paired-pulse magnetic stimulation paradigm. The conditioning stimulus was applied to the right primary motor cortex and the test stimulus was applied to the left primary motor cortex. The interstimulus interval was set at 0.1 ms resolution. The proportions of transcallosal fibers with different conduction velocities were calculated by measuring the changes in magnitudes of interhemispheric facilitation and inhibition with interstimulus interval. Results: Both interhemispheric facilitation and inhibition increased with increment in interstimulus interval. The magnitude of interhemispheric facilitation was correlated with that of interhemispheric inhibition. The latency distribution of transcallosal fibers measured with interhemispheric facilitation was also correlated with that measured with interhemispheric inhibition. Conclusions: The data can be interpreted as latency distribution of transcallosal fibers. Interhemispheric interaction measured with transcranial magnetic stimulation is a promising technique to determine the latency distribution of the transcallosal fibers. Similar techniques could be developed for other cortical pathways

Retrospective Study of Serum Sclerostin Measurements in Bed Rest Subjects

Animal models and human studies suggest that osteocytes regulate the skeleton s response to mechanical unloading at the cellular level in part by an increase in sclerostin, an inhibitor of the anabolic Wnt pathway. However, few studies have reported changes in serum sclerostin in humans exposed to reduced mechanical loading. Thus, we determined changes in serum sclerostin and bone turnover markers in healthy adult men who participated in a controlled bed rest study. Seven healthy adult men (31 +/- 3 yrs old) underwent 90-day six-degree head down tilt bed rest at the University of Texas Medical Branch in Galveston's Institute for Translational Sciences - Clinical Research Center (ITS-CRC). Serum sclerostin, PTH, serum markers of bone turnover (bone specific alkaline phosphatase, RANKL/OPG, and osteocalcin), urinary calcium and phosphorus excretion, and 24 hour pooled urinary markers of bone resorption (NTX, DPD, PYD) were evaluated pre-bed rest (BL), bed rest day 28 (BR-28), bed rest day 60 (BR-60), and bed rest day 90 (BR-90). In addition, bone mineral density (BMD) was assessed by dual-energy X-ray absorptiometry (DXA) at BL, BR-60, and post bed rest day 5 (BR+5). Data are reported as mean +/- standard deviation. We used repeated measures ANOVA to compare baseline values to BR-28, BR-60, and BR-90. RESULTS Consistent with prior reports, BMD declined significantly (1-2% per month) at weight-bearing skeletal sites (spine, hip, femur neck, and calcaneus). Serum sclerostin levels were elevated above BL at BR-28 (+29% +/- 20%, p = 0.003), BR-60 (+42% +/- 31%, p < 0.001), and BR-90 (22% +/- 21%, p = 0.07). Serum PTH levels were reduced at BR-28 (-17% +/- 16%, p = 0.02), BR-60 (-24% +/- 14%, p = 0.03), and returned to baseline at BR-90 (-21% +/- 21%, p = 0.14). Serum bone turnover markers did not change, however urinary bone resorption markers and calcium were significantly elevated following bed rest (p < 0.01). CONCLUSION We observed an increase of serum sclerostin associated with decreased serum PTH and elevated bone resorption markers in otherwise healthy men subjected to long-term immobilization

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Attention on Weak Ties in Social and Communication Networks

Granovetter's weak tie theory of social networks is built around two central hypotheses. The first states that strong social ties carry the large majority of interaction events; the second maintains that weak social ties, although less active, are often relevant for the exchange of especially important information (e.g., about potential new jobs in Granovetter's work). While several empirical studies have provided support for the first hypothesis, the second has been the object of far less scrutiny. A possible reason is that it involves notions relative to the nature and importance of the information that are hard to quantify and measure, especially in large scale studies. Here, we search for empirical validation of both Granovetter's hypotheses. We find clear empirical support for the first. We also provide empirical evidence and a quantitative interpretation for the second. We show that attention, measured as the fraction of interactions devoted to a particular social connection, is high on weak ties --- possibly reflecting the postulated informational purposes of such ties --- but also on very strong ties. Data from online social media and mobile communication reveal network-dependent mixtures of these two effects on the basis of a platform's typical usage. Our results establish a clear relationships between attention, importance, and strength of social links, and could lead to improved algorithms to prioritize social media content

Topological Strata of Weighted Complex Networks

The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and --more recently-- correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.Comment: 26 pages, 19 figures, 1 tabl

Efficient Network Reconstruction from Dynamical Cascades Identifies Small-World Topology of Neuronal Avalanches

Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics