False discovery rate analysis of brain diffusion direction maps

Diffusion tensor imaging (DTI) is a novel modality of magnetic resonance imaging that allows noninvasive mapping of the brain's white matter. A particular map derived from DTI measurements is a map of water principal diffusion directions, which are proxies for neural fiber directions. We consider a study in which diffusion direction maps were acquired for two groups of subjects. The objective of the analysis is to find regions of the brain in which the corresponding diffusion directions differ between the groups. This is attained by first computing a test statistic for the difference in direction at every brain location using a Watson model for directional data. Interesting locations are subsequently selected with control of the false discovery rate. More accurate modeling of the null distribution is obtained using an empirical null density based on the empirical distribution of the test statistics across the brain. Further, substantial improvements in power are achieved by local spatial averaging of the test statistic map. Although the focus is on one particular study and imaging technology, the proposed inference methods can be applied to other large scale simultaneous hypothesis testing problems with a continuous underlying spatial structure.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS133 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Optimal Clustering under Uncertainty

Classical clustering algorithms typically either lack an underlying probability framework to make them predictive or focus on parameter estimation rather than defining and minimizing a notion of error. Recent work addresses these issues by developing a probabilistic framework based on the theory of random labeled point processes and characterizing a Bayes clusterer that minimizes the number of misclustered points. The Bayes clusterer is analogous to the Bayes classifier. Whereas determining a Bayes classifier requires full knowledge of the feature-label distribution, deriving a Bayes clusterer requires full knowledge of the point process. When uncertain of the point process, one would like to find a robust clusterer that is optimal over the uncertainty, just as one may find optimal robust classifiers with uncertain feature-label distributions. Herein, we derive an optimal robust clusterer by first finding an effective random point process that incorporates all randomness within its own probabilistic structure and from which a Bayes clusterer can be derived that provides an optimal robust clusterer relative to the uncertainty. This is analogous to the use of effective class-conditional distributions in robust classification. After evaluating the performance of robust clusterers in synthetic mixtures of Gaussians models, we apply the framework to granular imaging, where we make use of the asymptotic granulometric moment theory for granular images to relate robust clustering theory to the application.Comment: 19 pages, 5 eps figures, 1 tabl

Check the Box Marked Other: Exploring Gender in Family Life

The concept of a traditional family structure has been fading over the last 50 years and with this decline the notion of responsibilities being determined by gender is also losing ground, though it still has a long way to go. This short story collection works to continue to normalize the increasing variety of family structures, especially variety that has its roots in new notions of gender challenging old conventions. The stories are all set in Nebraska, an ideal landscape for exploring tradition versus modernity. Though there are major cities in NE, most of the state is composed of smaller rural communities with a heavy emphasis on agriculture and ranching. Land and livestock pass through multiple generations of the same family, usually from father to son, not mother to daughter. The effect is a sort of timelessness, an aging farmhouse with a son bearing striking resemblance to his father, maintaining a ranch dog and driving a Chevy because that is the way he was taught and expected to behave. But modern families do exist in the area, standing out even more in a place where everyone runs into each other at some point at the only grocery store in town. Half of this collection focuses on this landscape, while the other half delves into traditional families encountering the more liberal world of Lincoln and Omaha in the southeast corner of the state

An Asymptotically Optimal Bound for Covering Arrays of Higher Index

A \emph{covering array} is an $N \times k$ array ($N$ rows, $k$ columns) with each entry from a $v$-ary alphabet, and for every $N\times t$ subarray, all $v^t$ tuples of size $t$ appear at least $\lambda$ times. The \emph{covering array number} is the smallest number $N$ for which such an array exists. For $\lambda = 1$, the covering array number is asymptotically logarithmic in $k$, when $v, t$ are fixed. Godbole, Skipper, and Sunley proved a bound of the form $\log k + \lambda \log \log k$ for the covering array number for arbitrary $\lambda$ and $v,t$ constant. The author proved a similar bound via a different technique, and conjectured that the $\log \log k$ term can be removed. In this short note we answer the conjecture in the affirmative with an asymptotically tight upper bound. In particular, we employ the probabilistic method in conjunction with the Lambert $W$ function

Creation of a CS1 Course with Modern C++ Principles

Best practices in programming need to be emphasized in a CS1 course as bad student habits persist if not reinforced well. The C++ programming language, although a relatively old language, has been regularly updated with new versions since 2011, on the pace of once every three years. Each new version contains important features that make the C++ language more complex for backwards compatibility, but often introduce new features to make common use cases simpler to implement. This poster contains experiences in designing a CS1 course that uses the C++ programming language that incorporates ``modern'' versions of the language from the start, as well as recent conferences about the language. Our goals were to prevent many common bad habits among C++ programmers.Comment: Accepted to SIGCSE TS 2024 (poster

Designing Theory of Computing Backwards

The design of any technical Computer Science course must involve its context within the institution's CS program, but also incorporate any new material that is relevant and appropriately accessible to students. In many institutions, theory of computing (ToC) courses within undergraduate CS programs are often placed near the end of the program, and have a very common structure of building off previous sections of the course. The central question behind any such course is ``What are the limits of computers?'' for various types of computational models. However, what is often intuitive for students about what a ``computer'' is--a Turing machine--is taught at the end of the course, which necessitates motivation for earlier models. This poster contains our experiences in designing a ToC course that teaches the material effectively ``backwards,'' with pedagogic motivation of instead asking the question ``What suitable restrictions can we place on computers to make their problems tractable?'' We also give recommendations for future course design.Comment: Accepted to SIGCSE TS 2024 (poster

Comparing and contrasting Escherichia coli and Mycobacterium tuberculosis mechanosensitive channels (MscL) - New gain of function mutations in the loop region

Sequence analysis of 35 putative MscL homologues was used to develop an optimal alignment for Escherichia coli and Mycobacterium tuberculosis MscL and to place these homologues into sequence subfamilies. By using this alignment, previously identified E. coli MscL mutants that displayed severe and very severe gain of function phenotypes were mapped onto the M. tuberculosis MscL sequence. Not all of the resulting M. tuberculosis mutants displayed a gain of function phenotype; for instance, normal phenotypes were noted for mutations at Ala20, the analogue of the highly sensitive Gly22 site in E. coli. A previously unnoticed intersubunit hydrogen bond in the extracellular loop region of the M. tuberculosis MscL crystal structure has been analyzed. Cross-linkable residues were substituted for the residues involved in the hydrogen bond, and cross-linking studies indicated that these sites are spatially close under physiological conditions. In general, mutation at these positions results in a gain of function phenotype, which provides strong evidence for the importance of the loop region in MscL channel function. No analogue to this interesting interaction could be found in E. coli MscL by sequence alignment. Taken together, these results indicate that caution should be exercised in using the M. tuberculosis MscL crystal structure to analyze previous functional studies of E. coli MscL

Maternal fluoxetine exposure alters cortical hemodynamic and calcium response of offspring to somatosensory stimuli

Epidemiological studies have found an increased incidence of neurodevelopmental disorders in populations prenatally exposed to selective serotonin reuptake inhibitors (SSRIs). Optical imaging provides a minimally invasive way to determine if perinatal SSRI exposure has long-term effects on cortical function. Herein we probed the functional neuroimaging effects of perinatal SSRI exposure in a fluoxetine (FLX)-exposed mouse model. While resting-state homotopic contralateral functional connectivity was unperturbed, the evoked cortical response to forepaw stimulation was altered in FLX mice. The stimulated cortex showed decreased activity for FLX versus controls, by both hemodynamic responses [oxyhemoglobin (Hb