Progressive dysgraphia in a case of posterior cortical atrophy

Dysgraphia (agraphia) is a common feature of posterior cortical atrophy (PCA). However, detailed analyses of these spelling and writing impairments are infrequently conducted. LM is a 59-year-old woman with dysgraphia associated with PCA. She presented with a two-year history of decline in her writing and dressmaking skills. A 3D T1-weighted MRI scan confirmed selective bi-parietal atrophy, with relative sparing of the hippocampi and other cortical regions. Analyses of LM's preserved and impaired spelling abilities indicated mild physical letter distortions and a significant spelling deficit characterised by letter substitutions, insertions, omissions, and transpositions that was systematically sensitive to word length while insensitive to real word versus nonword category, word frequency, regularity, imagery, grammatical class and ambiguity. Our findings suggest a primary graphemic buffer disorder underlies LM's spelling errors, possibly originating from disruption to the operation of a fronto-parietal network implicated in verbal working memory.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Automatic clustering and population analysis of white matter tracts using maximum density paths

We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.

Assessment of dynamic susceptibility contrast cerebral blood flow response to amphetamine challenge: A human pharmacological magnetic resonance imaging study at 1.5 and 4 T

Pharmacological MRI (phMRI) techniques can be used to monitor the neurophysiological effects of central nervous system (CNS) active drugs. In this study, we investigated whether dynamic susceptibility contrast (DSC) perfusion imaging employing the use of superparamagnetic iron oxide nanoparticles (Resovist) could be used to measure hemodynamic response to d-amphetamine challenge in human subjects at both 1.5 and 4 T. Significant changes in cerebral blood flow (CBF) were found in focal regions associated with the nigrostriatal circuit and mesolimbic and mesocortical dopaminergic pathways. More significant CBF responses were found at higher field strength, mainly within striatal structures. The results from this study indicate that DSC perfusion imaging using Resovist can be used to assess the efficacy of CNS-active drugs and may play a role in the development of novel psychiatric therapies at the preclinical level. © 2005 Wiley-Liss, Inc.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

Neuroimaging and genetics: Exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.

Interference from object part relations in spoken word production: Behavioural and fMRI evidence

Objects presented in categorically related contexts are typically named slower than objects presented in unrelated contexts, a phenomenon termed semantic interference. However, not all semantic relationships induce interference. In the present study, we investigated the influence of object part-relations in the blocked cyclic naming paradigm. In Experiment 1 we established that an object's parts do induce a semantic interference effect when named in context compared to unrelated parts (e.g., leaf, root, nut, bark; for tree). In Experiment 2) we replicated the effect during perfusion functional magnetic resonance imaging (fMRI) to identify the cerebral regions involved. The interference effect was associated with significant perfusion signal increases in the hippocampal formation and decreases in the dorsolateral prefrontal cortex. We failed to observe significant perfusion signal changes in the left lateral temporal lobe, a region that shows reliable activity for interference effects induced by categorical relations in the same paradigm and is proposed to mediate lexical-semantic processing. We interpret these results as supporting recent explanations of semantic interference in blocked cyclic naming that implicate working memory mechanisms. However, given the failure to observe significant perfusion signal changes in the left temporal lobe, the results provide only partial support for accounts that assume semantic interference in this paradigm arises solely due to lexical-level processes.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

How does angular resolution affect diffusion imaging measures?

A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Translation and psychometric properties of the Chinese version of the Leeds Attitudes to Concordance II scale

Background Concordance is characterised as a negotiation-like health communication approach based on an equal and collaborative partnership between patients and health professionals. The Leeds Attitudes to Concordance II (LATCon II) scale was developed to measure the attitudes towards concordance. The purpose of this study was to translate the LATCon II into Chinese and psychometrically test the Chinese version of LATCon II (C-LATCon II). Methods The study involved three phases: i) translation and cross-cultural adaptation; ii) pilot study, and; iii) a cross-sectional survey (n = 366). Systematic random sampling was used to recruit hypertensive patients from nine communities covering around 78,000 residents in China. Tests of psychometric properties included content validity, construct validity, criteria-related validity (correlation between the C-LATCon II and the Therapeutic Adherence Scale for Hypertensive Patients (TASHP)), internal reliability, and test-retest reliability (n = 30). Results The study found that the C-LATCon II had a satisfactory content validity (item-level Content Validity Index (CVI) = 0.83-1, scale-level CVI/universal agreement = 0.89, and scale-level CVI/averaging calculation = 0.98), construct validity (four components extracted explained 56.66% of the total variance), internal reliability (Cronbach’s alpha of overall scale and four components was 0.78 and 0.66-0.84, respectively), and test-retest reliability (Pearson’s correlation coefficient = 0.82, p < 0.001; interclass correlation coefficient = 0.82, p < 0.001; linear weighted kappa3 statistic for each item = 0.40-0.65, p < 0.05). Criteria-related validity showed a weak association (Pearson’s correlation coefficient = 0.11, p < 0.05) between patients’ attitudes towards concordance during health communication and their health behaviours for hypertension management. Conclusions The C-LATCon II is a validated and reliable instrument which can be used to evaluate the attitudes to concordance in Chinese populations. Four components (health professionals’ attitudes, partnership between two parties, therapeutic decision making, and patients’ involvement) describe the attitudes towards concordance during health communication.

Numerical computation of an Evans function for travelling waves

We demonstrate a geometrically inspired technique for computing Evans functions for the linearised operators about travelling waves. Using the examples of the F-KPP equation and a Keller–Segel model of bacterial chemotaxis, we produce an Evans function which is computable through several orders of magnitude in the spectral parameter and show how such a function can naturally be extended into the continuous spectrum. In both examples, we use this function to numerically verify the absence of eigenvalues in a large region of the right half of the spectral plane. We also include a new proof of spectral stability in the appropriate weighted space of travelling waves of speed c≥sqrt(2δ) in the F-KPP equation.

Multiple sulfur isotope analyses support a magmatic model for the volcanogenic massive sulfide deposits of the Teutonic Bore volcanic complex, Yilgarn Craton, Western Australia

We report sensitive high mass resolution ion microprobe, stable isotopes (SHRIMP SI) multiple sulfur isotope analyses (32S, 33S, 34S) to constrain the sources of sulfur in three Archean VMS deposits—Teutonic Bore, Bentley, and Jaguar—from the Teutonic Bore volcanic complex of the Yilgarn Craton, Western Australia, together with sedimentary pyrites from associated black shales and interpillow pyrites. The pyrites from VMS mineralization are dominated by mantle sulfur but include a small amount of slightly negative mass-independent fractionation (MIF) anomalies, whereas sulfur from the pyrites in the sedimentary rocks has pronounced positive MIF, with ∆33S values that lie between 0.19 and 6.20‰ (with one outlier at −1.62‰). The wall rocks to the mineralization include sedimentary rocks that have contributed no detectable positive MIF sulfur to the VMS deposits, which is difficult to reconcile with the leaching model for the formation of these deposits. The sulfur isotope data are best explained by mixing between sulfur derived from a magmatic-hydrothermal fluid and seawater sulfur as represented by the interpillow pyrites. The massive sulfide lens pyrites have a weighted mean ∆33S value of −0.27 ± 0.05‰ (MSWD = 1.6) nearly identical with −0.31 ± 0.08‰ (MSWD = 2.4) for pyrites from the stringer zone, which requires mixing to have occurred below the sea floor. We employed a two-component mixing model to estimate the contribution of seawater sulfur to the total sulfur budget of the two Teutonic Bore volcanic complex VMS deposits. The results are 15 to 18% for both Teutonic Bore and Bentley, much higher than the 3% obtained by Jamieson et al. (2013) for the giant Kidd Creek deposit. Similar calculations, carried out for other Neoarchean VMS deposits give value between 2% and 30%, which are similar to modern hydrothermal VMS deposits. We suggest that multiple sulfur isotope analyses may be used to predict the size of Archean VMS deposits and to provide a vector to ore deposit but further studies are needed to test these suggestions.

Scoring rules and abnormally low bids criteria in construction tenders: A taxonomic review

In the global construction context, the Best Value or Most Economically Advantageous Tender is becoming a widespread approach for contractor selection, as an alternative to other traditional awarding criteria such as the Lowest Price. In these multi-attribute tenders, the owner or auctioneer solicits proposals containing both a price bid and additional technical features. Once the proposals are received, each bidder's price bid is given an economic score according to a scoring rule, generally called an Economic Scoring Formula (ESF) and a technical score according to pre-specified criteria. Eventually, the contract is awarded to the bidder with the highest weighted overall score (economic + technical). However, Economic Scoring Formula selection by auctioneers is invariably and paradoxically a highly intuitive process in practice, involving few theoretical or empirical considerations, despite having being considered traditionally and mistakenly as objective, due to its mathematical nature. This paper provides a taxonomic classification of a wide variety of ESF and Abnormally Low Bid Criteria (ALBC) gathered in several countries with different tendering approaches. Practical implications concern the optimal design of price scoring rules in construction contract tenders, as well as future analyses of the effects of ESF and ALBC on competitive bidding behaviour.