A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

Mapping genetic influences on brain fiber architecture with high angular resolution diffusion imaging (HARDI)

We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.

Probabilistic multi-tensor estimation using the tensor distribution function

Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of 6 directions, second-order tensors can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve crossing fiber tracts. Recently, a number of high-angular resolution schemes with greater than 6 gradient directions have been employed to address this issue. In this paper, we introduce the Tensor Distribution Function (TDF), a probability function defined on the space of symmetric positive definite matrices. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the diffusion orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function.

Best individual template selection from deformation tensor minimization

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

Identifying rate-limiting nodes in large-scale cortical networks for visuospatial processing: An illustration using fMRI

With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Location and labor: Critical crossroads in global film and television

I approached the editorial prompt as an opportunity to work through some of the concerns driving my current research on creative labor in emergent or ‘peripheral’ media hubs, centers of production activity outside established media capitals that are nevertheless increasingly integrated into a global production apparatus. It builds from my research on the role that film, television and digital media production have played in the economic and cultural strategies of Glasgow, Scotland, and extends the focus on media work to other locations, including Prague and Budapest. I am particularly drawn to the spatial dynamics at play in these locations and how local producers, writers, directors and crew negotiate a sense of place and creative identity against the flows and counter-flows of capital and culture. This means not only asking questions about the growing ensemble of people, places, firms and policies that make international productions possible, but also studying the more quotidian relationships between media workers and the locations (both near and far) where they now find work. I do not see these tasks as unrelated. On the one hand, such queries underscore how international production depends on a growing constellation of interchangeable parts and is facilitated by various actors whose agendas may or may not converge. On the other hand, these questions also betray an even more complicated dynamic, a process that is shifting the spatial orientation of both location and labor around uneven and contested scales. As local industries reimagine themselves as global players, media practitioners are caught up in a new geography of creative labor: not only are personnel finding it increasingly necessary to hop from place to place to follow the work, but also place itself is changing, as locations morph into nebulous amalgamations of tax rebates, subsidized facilities, production services and (when it still matters) natural beauty.

The tensor distribution function

Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.

Resampling-based approaches to study variation in morphological modularity

Modularity has been suggested to be connected to evolvability because a higher degree of independence among parts allows them to evolve as separate units. Recently, the Escoufier RV coefficient has been proposed as a measure of the degree of integration between modules in multivariate morphometric datasets. However, it has been shown, using randomly simulated datasets, that the value of the RV coefficient depends on sample size. Also, so far there is no statistical test for the difference in the RV coefficient between a priori defined groups of observations. Here, we (1), using a rarefaction analysis, show that the value of the RV coefficient depends on sample size also in real geometric morphometric datasets; (2) propose a permutation procedure to test for the difference in the RV coefficient between a priori defined groups of observations; (3) show, through simulations, that such a permutation procedure has an appropriate Type I error; (4) suggest that a rarefaction procedure could be used to obtain sample-size-corrected values of the RV coefficient; and (5) propose a nearest-neighbor procedure that could be used when studying the variation of modularity in geographic space. The approaches outlined here, readily extendable to non-morphometric datasets, allow study of the variation in the degree of integration between a priori defined modules. A Java application – that will allow performance of the proposed test using a software with graphical user interface – has also been developed and is available at the Morphometrics at Stony Brook Web page (http://life.bio.sunysb.edu/morph/).

Association of variants in MMEL1 and CTLA4 with rheumatoid arthritis in the Han Chinese population

Background: The genome-wide association study era has made great progress in identifying susceptibility genes and genetic loci for rheumatoid arthritis (RA) in populations of White European ancestry. However, few studies have tried to dissect disease aetiopathogenesis in other ethnic populations. Objective: To investigate these associations in the Han Chinese population. Methods: Haplotypes from the HapMap database Chinese population were used to select tag-single-nucleotide polymorphisms (SNPs) (r2 =0.8) across 19 distinct RA genomic regions. A two phase case-control association study was performed, with 169 SNPs genotyped in phase I (n=571 cases, n=880 controls), and 64 SNPs achieving p<0.2 in the first phase being genotyped in phase II (n=464 cases, n=822 controls). Association statistics were calculated using permutation tests both unadjusted and adjusted for the number of markers studied. Results: Robust association was detected for MMEL1 and CTLA4 , and modest association was identified for another six loci: PADI4 , STAT4 , PRDM1 , CDK6 , TRAF1-C5 and KIF5A-PIP4K2C. All three markers genotyped in MMEL1 demonstrated association, with peak signal for rs3890745 (p=2.6×10 -5unadjusted, p=0.003 adjusted, OR=0.79). For CTLA4 , significance was detected for three of five variants showing association, with peak association for marker rs12992492 (p=4.3×10-5 unadjusted, p=0.0021 adjusted, OR=0.77). Lack of association of common variants in PTPN22 with RA in Han Chinese was confirmed. Conclusion: This study identifies MMEL1 and CTLA4 as RA susceptibility genes, provides suggestive evidence of association for a further six loci in the Han Chinese population and confirms lack of PTPN22 association in Asian populations. It also confirms the value of multiethnic population studies to help dissect disease aetiopathogenesis.

Improved linear cryptanalysis of reduced-round SIMON-32 and SIMON-48

In this paper we analyse two variants of SIMON family of light-weight block ciphers against variants of linear cryptanalysis and present the best linear cryptanalytic results on these variants of reduced-round SIMON to date. We propose a time-memory trade-off method that finds differential/linear trails for any permutation allowing low Hamming weight differential/linear trails. Our method combines low Hamming weight trails found by the correlation matrix representing the target permutation with heavy Hamming weight trails found using a Mixed Integer Programming model representing the target differential/linear trail. Our method enables us to find a 17-round linear approximation for SIMON-48 which is the best current linear approximation for SIMON-48. Using only the correlation matrix method, we are able to find a 14-round linear approximation for SIMON-32 which is also the current best linear approximation for SIMON-32. The presented linear approximations allow us to mount a 23-round key recovery attack on SIMON-32 and a 24-round Key recovery attack on SIMON-48/96 which are the current best results on SIMON-32 and SIMON-48. In addition we have an attack on 24 rounds of SIMON-32 with marginal complexity.

Destinations: 3 Large Cast Plays for Young People

This book is a collection of three large-cast plays written in response to a very specific problem. My work as a teacher of drama often required me to locate a script that would somehow miraculously work for a cast of unknown number and gender, and most likely uneven skills and enthusiasm, who I hadn’t even met yet. It’s a familiar dilemma for teachers and students of drama in education contexts, at whatever level you’re teaching. I’d first addressed this creative problem with scripts such as Gate 38 (2010). I had tried using scripts that already existed, but found they required such extensive editing to suit the parameters of cast and performance duration that I may as well have been writing them myself. Even in the setting of a closed studio, in altering these plays I felt I was bending the vision of the playwright, and certainly their narrative structure, out of shape. Everyone who’s attempted to stage a performance with a large cast of students in an educational setting knows it takes time to truly connect with a play, its social contexts, themes and characters. It also takes a lot of time to get on top of the practicalities of learning, rehearsing, directing and running a performance with young people. Often the curtain goes up on something unfinished and unstable. I was looking for ways to reduce the complexity of staging a script, while maintaining the potential of this process as a site of rich, enjoyable learning. Two of the plays (Duty Free and Please Be Seated) are comprised of multiple monologues, combined with music-driven ensemble sequences. The monologues enable individuals to develop and polish their own performances, work in small groups, and cut down on the laborious detail of directing naturalistic scenes based in character interaction. The third (Australian Drama) involves a lot of duologues, meaning that its rehearsal process can happily employ that mainstay of the drama classroom: small group work. There’s plenty of room to move in terms of gender-blind casting as well. Please be Seated is mainly young women. The scripts also contain ensemble-based interludes which are non-verbal, music driven, with a choreographic element. They have also springboarded further explorations in form. The ethical and aesthetic complexities of verbatim works; the interaction between music and theatre; and meta-concerns related to the performing of performance: ‘how can the act of acting ‘acted’. The narratives of all three of these plays are deliberately open, enabling the flexible casting and on-the hop editing that large-group, time-poor processes sometimes necessitate. Duty Free is about the overseas ‘adventures’ of young people. Please Be Seated is based in verbatim text about young people falling in and out of love. Australian Drama is about young people in a drama classroom trying to connect with each other and put their own shine on dull fragments of the theatrical canon. The plays were published as a collection in hardcopy and digital editions by Playlab Press in 2015. Please be Seated is a co-write with a large group. These co-author’s names are listed in the publication, and below in ‘additional information’.

Induced smoothing for rank regression with censored survival times

Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.

A versatile gene-based test for genome-wide association studies

We have derived a versatile gene-based test for genome-wide association studies (GWAS). Our approach, called VEGAS (versatile gene-based association study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. We show that for an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. We demonstrate proof-of-principle by using the gene-based test to replicate several genes known to be associated on the basis of results from a family-based GWAS for height in 11,536 individuals and a DNA-pooling-based GWAS for melanoma in approximately 1300 cases and controls. Our method has the potential to identify novel associated genes; provide a basis for selecting SNPs for replication; and be directly used in network (pathway) approaches that require per-gene association test statistics. We have implemented the approach in both an easy-to-use web interface, which only requires the uploading of markers with their association p-values, and a separate downloadable application.

Variants in EMX2 and PTEN do not contribute to risk of endometriosis

Endometriosis has a genetic component, and significant linkage has been found to a region on chromosome 10q. Two candidate genes, EMX2 and PTEN, implicated in both endometriosis and endometrial cancer, lie on chromosome 10q. We hypothesized that variation in EMX2 and/or PTEN could contribute to the risk of endometriosis and may account for some of the linkage signal on 10q. We genotyped single nucleotide polymorphisms (SNPs) in a case-control design to evaluate association between endometriosis and common variations in these two genes. The genotyping and statistical analysis were based on samples collected from Australian volunteers. The cases were 768 unrelated women with surgically confirmed endometriosis selected from affected sister pair (ASP) families participating in the Australian Genes behind Endometriosis Study. The controls were 768 female participants in twin studies who, based on screening questions, did not have a diagnosis of endometriosis. Genotypes of 22 SNPs in the EMX2 gene and 15 SNPs in the PTEN gene were the main outcome measures. Statistical analysis provided measures of linkage disequilibrium and association. Permutation testing showed no globally significant association between any SNPs or haplotypes and endometriosis for either gene. It is unlikely that the EMX2 or PTEN gene variants investigated contribute to risk for initiation and/or development of endometriosis.