Socio-economic factors and the journey to work: A case study of AT&T GIS employees

Individuals who must commute to work are often concerned with the spatial separation of their home and job site. In many of these cases the socio-economic characteristics of these individual\u27s lives play an important part in deciding how long this commute is, in terms of both time and distance. The following study seeks to identify the relationships between several selected socio-economic characteristics and the journey to work distances for employees at AT&T GIS. The factors being examined in this study are age, education level, number of dependents, income, length of service to the company, occupation type and gender. Significant differences in commuting distances were identified for the subgroups of employees being compared for five of the above factors. Only income and number of dependents were found to have no significant effect on commuting distances. However, when maximum commuting distances were compared for men and women separately, the number of dependents claimed by the individuals in the subgroups was found to affect the spatial separation of home and work for many of these individuals. Crosstabulations, difference of means t-tests and regression analyses were conducted to identify patterns and relationships inherent in the dataset provided by AT&T GIS. Unless stated otherwise, the confidence level selected for all statistical tests was 95%

Evaluation of atlas-based segmentation of hippocampi in healthy humans

Introduction and aim: Region of interest (ROI)-based functional magnetic resonance imaging (fMRI) data analysis relies on extracting signals from a specific area which is presumed to be involved in the brain activity being studied. The hippocampus is of interest in many functional connectivity studies for example in epilepsy as it plays an important role in epileptogenesis. In this context, ROI may be defined using different techniques. Our study aims at evaluating the spatial correspondence of hippocampal ROIs obtained using three brain atlases with hippocampal ROI obtained using an automatic segmentation algorithm dedicated to the hippocampus. Material and methods: High-resolution volumetric T1-weighted MR images of 18 healthy volunteers (five females) were acquired on a 3T scanner. Individual ROIs for both hippocampi of each subject were segmented from the MR images using an automatic hippocampus and amygdala segmentation software called SACHA providing the gold standard ROI for comparison with the atlas-derived results. For each subject, hippocampal ROIs were also obtained using three brain atlases: PickAtlas available as a commonly used software toolbox; automated anatomical labeling (AAL) atlas included as a subset of ROI into PickAtlas toolbox and a frequency-based brain atlas by Hammers et al. The levels of agreement between the SACHA results and those obtained using the atlases were assessed based on quantitative indices measuring volume differences and spatial overlap. The comparison was performed in standard Montreal Neurological Institute space, the registration being obtained with SPM5 (http://www.fil.ion.ucl.ac.uk/spm/). Results: The mean volumetric error across all subjects was 73% for hippocampal ROIs derived from AAL atlas; 20% in case of ROIs derived from the Hammers atlas and 107% for ROIs derived from PickAtlas. The mean false-positive and false-negative classification rates were 60% and 10% respectively for the AAL atlas; 16% and 32% for the Hammers atlas and 6% and 72% for the PickAtlas. Conclusion: Though atlas-based ROI definition may be convenient, the resulting ROIs may be poor representations of the hippocampus in some studies critical to under- or oversampling. Performance of the AAL atlas was inferior to that of the Hammers atlas. Hippocampal ROIs derived from PickAtlas are highly significantly smaller, and this results in the worst performance out of three atlases. It is advisable that the defined ROIs should be verified with knowledge of neuroanatomy before using it for further data analysis

The cost of prospecting for dispersal opportunities in a social bird

Understanding why individuals delay dispersal and become subordinates within a group is central to studying the evolution of sociality. Hypotheses predict that dispersal decisions are influenced by costs of extra-territorial prospecting that are often required to find a breeding vacancy. Little is known about such costs, partly because it is complicated to demonstrate them empirically. For example, prospecting individuals may be of inferior quality already before prospecting and/or have been evicted. Moreover, costs of prospecting are mainly studied in species where prospectors suffer from predation risk, so how costly prospecting is when predators are absent remains unclear. Here, we determine a cost of prospecting for subordinate Seychelles warblers, Acrocephalus sechellensis, in a population where predators are absent and individuals return to their resident territory after prospecting. Prospecting individuals had 5.2% lower body mass than non-prospecting individuals. Our evidence suggests this may be owing to frequent attacks by resident conspecifics, likely leading to reduced food intake by prospectors. These results support the hypothesis that energetic costs associated with dispersal opportunities are one factor influencing dispersal decisions and shaping the evolution of delayed dispersal in social animals

Sex-specific influence of communal breeding experience on parenting performance and fitness in a burying beetle

Communal breeding, wherein multiple conspecifics live and reproduce together, may generate short-term benefits in terms of defence and reproduction. However, its carry-over effects remain unclear. We experimentally tested the effects of communal breeding on parental care and reproduction in burying beetles (Nicrophorus vespilloides), which use carcasses as breeding resources and provide parental care to offspring. We subjected individuals to communal or non-communal breeding (i.e. pair breeding) during their first breeding event and to non-communal breeding during their second breeding event. We measured the parental care of individuals and of groups and the reproductive success of groups during both breeding events. In communal groups, large individuals became dominant and largely monopolized the carcass, whereas small individuals (i.e. subordinates) had restricted access to the carcass. At the first breeding event, large males in communal groups spent more time providing care than large males in non-communal groups, whereas such an effect was not observed for large females and small individuals. Reproductive successes were similar in communal and non-communal groups, indicating no short-term benefits of communal breeding in terms of reproduction. Compared with males from non-communal groups, males originating from communal groups produced a larger size of brood during their second breeding event, whereas such an effect was not observed for females. Our results demonstrate the sex-specific effects of communal breeding experience on parenting performance and fitness

On brain atlas choice and automatic segmentation methods: a comparison of MAPER & FreeSurfer using three atlas databases.

Several automatic image segmentation methods and few atlas databases exist for analysing structural T1-weighted magnetic resonance brain images. The impact of choosing a combination has not hitherto been described but may bias comparisons across studies. We evaluated two segmentation methods (MAPER and FreeSurfer), using three publicly available atlas databases (Hammers_mith, Desikan-Killiany-Tourville, and MICCAI 2012 Grand Challenge). For each combination of atlas and method, we conducted a leave-one-out cross-comparison to estimate the segmentation accuracy of FreeSurfer and MAPER. We also used each possible combination to segment two datasets of patients with known structural abnormalities (Alzheimer's disease (AD) and mesial temporal lobe epilepsy with hippocampal sclerosis (HS)) and their matched healthy controls. MAPER was better than FreeSurfer at modelling manual segmentations in the healthy control leave-one-out analyses in two of the three atlas databases, and the Hammers_mith atlas database transferred to new datasets best regardless of segmentation method. Both segmentation methods reliably identified known abnormalities in each patient group. Better separation was seen for FreeSurfer in the AD and left-HS datasets, and for MAPER in the right-HS dataset. We provide detailed quantitative comparisons for multiple anatomical regions, thus enabling researchers to make evidence-based decisions on their choice of atlas and segmentation method

Delayed dispersal and the cost and benefits of different routes to independent breeding in a cooperative breeding bird

Why sexually mature individuals stay in groups as non-reproductive subordinates is central to the evolution of sociality and cooperative breeding. To understand such delayed dispersal, its costs and benefits need to be compared with those of permanently leaving to float through the population. However, comprehensive comparisons, especially regarding differences in future breeding opportunities, are rare. Moreover, extra-territorial prospecting by philopatric individuals has generally been ignored, even though the factors underlying this route to independent breeding may differ from those of strict philopatry or floating. We use a comprehensive predictive framework to explore how various costs, benefits and intrinsic, environmental and social factors explain philopatry, prospecting and floating in Seychelles warblers (Acrocephalus sechellensis). Floaters more likely obtained an independent breeding position before the next season than strictly philopatric individuals, but also suffered higher mortality. Prospecting yielded similar benefits to floating but lower mortality costs, suggesting that it is overall more beneficial than floating and strict philopatry. Whereas prospecting is probably individual-driven, though limited by resource availability, floating likely results from eviction by unrelated breeders. Such differences in proximate and ultimate factors underlying each route to independent breeding highlight the need for simultaneous consideration when studying the evolution of delayed dispersal

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study