Consistent Layout for Thematic Software Maps

Software visualizations can provide a concise overview of a complex software system. Unfortunately, since software has no physical shape, there is no “natural“ mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typical diverges from one visualization to another. We propose a consistent layout for software maps in which the position of a software artifact reflects its \emph{vocabulary}, and distance corresponds to similarity of vocabulary. We use Latent Semantic Indexing (LSI) to map software artifacts to a vector space, and then use Multidimensional Scaling (MDS) to map this vector space down to two dimensions. The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, since the vocabulary of software artifacts tends to be stable over time.

Understanding Neural Maps with Topographica

The biological function of neurons can often be understood only in the context of large, highly interconnected networks. These networks typically form two-dimensional topographic maps, such as the retinotopic maps in mammalian visual cortex. Computational simulations of these areas have led to valuable insights about how cortical topography develops and functions, but further progress has been hindered due to the lack of appropriate simulation tools. This paper introduces the freely available Topographica maplevel simulator, originally developed at the University of Texas at Austin and now maintained at the University of Edinburgh, UK. Topographica is designed to make large-scale, detailed models practical. The goal is to allow neuroscientists and computational scientists to work together to understand how topographic maps and their connections organize and operate. This understanding will be crucial for integrating experimental observations into a comprehensive theory of brain function.

Book Review of “Human Behaviour and the Social Environment: Models, Metaphors, and Maps for Applying Theoretical Perspectives to Practice”. 640 pages, Thomson Brooks/Cole, 2007, by James A. Forte

This voluminous book which draws on almost 1000 references provides an important theoretical base for practice. After an informative introduction about models, maps and metaphors, Forte provides an impressive presentation of several perspectives for use in practice; applied ecological theory, applied system theory, applied biology, applied cognitive science, applied psychodynamic theory, applied behaviourism, applied symbolic interactionism, applied social role theory, applied economic theory, and applied critical theory. Finally he completes his book with a chapter on “Multi theory practice and routes to integration.”

The bovine dilated cardiomyopathy locus maps to a 1.0-Mb interval on chromosome 18

Cardiomyopathies are myocardial diseases that lead to cardiac dysfunction, heart failure, arrhythmia, and sudden death. In human medicine, cardiomyopathies frequently warrant heart transplantation in children and adults. Bovine dilated cardiomyopathy (BDCMP) is a heart muscle disorder that has been observed during the last 30 years in cattle of Holstein-Friesian origin. In Switzerland BDCMP affects Swiss Fleckvieh and Red Holstein breeds. BDCMP is characterized by a cardiac enlargement with ventricular remodeling and chamber dilatation. The common symptoms in affected animals are subacute subcutaneous edema, congestion of the jugular veins, and tachycardia with gallop rhythm. A cardiomegaly with dilatation and hypertrophy of all heart chambers, myocardial degeneration, and fibrosis are typical postmortem findings. It was shown that all BDCMP cases reported worldwide traced back to a red factor-carrying Holstein-Friesian bull, ABC Reflection Sovereign. An autosomal recessive mode of inheritance was proposed for BDCMP. Recently, the disease locus was mapped to a 6.7-Mb interval MSBDCMP06-BMS2785 on bovine Chr 18 (BTA18). In the present study the BDCMP locus was fine mapped by using a combined strategy of homozygosity mapping and association study. A BAC contig of 2.9 Mb encompassing the crucial interval was constructed to establish the correct marker order on BTA18. We show that the disease locus is located in a gene-rich interval of 1.0 Mb and is flanked by the microsatellite markers DIK3006 and MSBDCMP51.

Arachnomelia in Brown Swiss cattle maps to chromosome 5

Arachnomelia in Brown Swiss cattle is a monogenic autosomal recessive inherited congenital disorder of the skeletal system giving affected calves a spidery look (OMIA ID 000059). Over a period of 20 years 15 cases were sampled in the Swiss and Italian Brown cattle population. Pedigree data revealed that all affected individuals trace back to a single acknowledged carrier founder sire. A genome scan using 240 microsatellites spanning the 29 bovine autosomes showed homozygosity at three adjacent microsatellite markers on bovine Chr 5 in all cases. Linkage analysis confirmed the localization of the arachnomelia mutation in the region of the marker ETH10. Fine-mapping and haplotype analysis using a total of 34 markers in this region refined the critical region of the arachnomelia locus to a 7.19-Mb interval on bovine Chr 5. The disease-associated IBD haplotype was shared by 36 proven carrier animals and allows marker-assisted selection. As the corresponding human and mouse chromosome segments do not contain any clear functional candidate genes for this disorder, the mutation causing arachnomelia in the Brown Swiss cattle might help to identify an unknown gene in bone development.

Microstates in language-related brain potential maps show noun-verb differences

Brain processing of grammatical word class was studied analyzing event-related potential (ERP) brain fields. Normal subjects observed a randomized sequence of single German nouns and verbs on a computer screen, while 20-channel ERP field map series were recorded separately for both word classes. Spatial microstate analysis was applied, based on the observation that series of ERP maps consist of epochs of quasi-stable map landscapes and based on the rationale that different map landscapes must have been generated by different neural generators and thus suggest different brain functions. Space-oriented segmentation of the mean map series identified nine successive, different functional microstates, i.e., steps of brain information processing characterized by quasi-stable map landscapes. In the microstate from 116 to 172 msec, noun-related maps differed significantly from verb-related maps along the left–right axis. The results indicate that different neural populations represent different grammatical word classes in language processing, in agreement with clinical observations. This word class differentiation as revealed by the spatial–temporal organization of neural activity occurred at a time after word input compatible with speed of reading.