The Lantern Vol. 74, No. 1, Fall 2006

• Seven Haikus About Insomnia • Lunch Hour • Divorced Parents and Flower Guts • 24 • Lily • Growth • Narcissistically Admiring You • Mysterious Avocado • Aloha Roast • Summer • Lines • Internalizing • San Francisco • Numb Candle • Moments No. 1 • Tanka • Euphemism • We be Malllllll • Dragon Magic • Time for the Magic Show • Green • Job • The Shire • Venom • The Seasons of Love • The Position • Fragments of an Artist • Peace • Vagabond Nights • Rerum Concordia Discorshttps://digitalcommons.ursinus.edu/lantern/1169/thumbnail.jp

Is Poverty in our Genes?: A Reply to Ashraf and Galor

The extent to which a paper written by economists Quamrul Ashraf and Oded Galor, which is forthcoming in the American Economic Review, is flawed on both factual and methodological grounds is presented. Aside from claiming that there is a causal effect of genetic diversity on economic success, the paper also heavily suggests that too much or too little genetic diversity hampers development

Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer's disease.

Volume and change in volume of the hippocampus are both important markers of Alzheimer's disease (AD). Delineation of the structure on MRI is time-consuming and therefore reliable automated methods are required. We describe an improvement (multiple-atlas propagation and segmentation (MAPS)) to our template library-based segmentation technique. The improved technique uses non-linear registration of the best-matched templates from our manually segmented library to generate multiple segmentations and combines them using the simultaneous truth and performance level estimation (STAPLE) algorithm. Change in volume over 12months (MAPS-HBSI) was measured by applying the boundary shift integral using MAPS regions. Methods were developed and validated against manual measures using subsets from Alzheimer's Disease Neuroimaging Initiative (ADNI). The best method was applied to 682 ADNI subjects, at baseline and 12-month follow-up, enabling assessment of volumes and atrophy rates in control, mild cognitive impairment (MCI) and AD groups, and within MCI subgroups classified by subsequent clinical outcome. We compared our measures with those generated by Surgical Navigation Technologies (SNT) available from ADNI. The accuracy of our volumes was one of the highest reported (mean(SD) Jaccard Index 0.80(0.04) (N=30)). Both MAPS baseline volume and MAPS-HBSI atrophy rate distinguished between control, MCI and AD groups. Comparing MCI subgroups (reverters, stable and converters): volumes were lower and rates higher in converters compared with stable and reverter groups (p< or =0.03). MAPS-HBSI required the lowest sample sizes (78 subjects) for a hypothetical trial. In conclusion, the MAPS and MAPS-HBSI methods give accurate and reliable volumes and atrophy rates across the clinical spectrum from healthy aging to AD

Is Poverty in Our Genes?

We present a critique of a paper written by two economists, Quamrul Ashraf and Oded Galor, which is forthcoming in the American Economic Review and which was uncritically highlighted in Science magazine. Their paper claims there is a causal effect of genetic diversity on economic success, positing that too much or too little genetic diversity constrains development. In particular, they argue that “the high degree of diversity among African populations and the low degree of diversity among Native American populations have been a detrimental force in the development of these regions.” We demonstrate that their argument is seriously flawed on both factual and methodological grounds. As economists and other social scientists begin exploring newly available genetic data, it is crucial to remember that nonexperts broadcasting bold claims on the basis of weak data and methods can have profoundly detrimental social and political effects.Anthropolog

A comparison of voxel and surface based cortical thickness estimation methods

Cortical thickness estimation performed in-vivo via magnetic resonance imaging is an important technique for the diagnosis and understanding of the progression of neurodegenerative diseases. Currently, two different computational paradigms exist, with methods generally classified as either surface or voxel-based. This paper provides a much needed comparison of the surface-based method FreeSurfer and two voxel-based methods using clinical data. We test the effects of computing regional statistics using two different atlases and demonstrate that this makes a significant difference to the cortical thickness results. We assess reproducibility, and show that FreeSurfer has a regional standard deviation of thickness difference on same day scans that is significantly lower than either a Laplacian or Registration based method and discuss the trade off between reproducibility and segmentation accuracy caused by bending energy constraints. We demonstrate that voxel-based methods can detect similar patterns of group-wise differences as well as FreeSurfer in typical applications such as producing group-wise maps of statistically significant thickness change, but that regional statistics can vary between methods. We use a Support Vector Machine to classify patients against controls and did not find statistically significantly different results with voxel based methods compared to FreeSurfer. Finally we assessed longitudinal performance and concluded that currently FreeSurfer provides the most plausible measure of change over time, with further work required for voxel based methods. (c) 2011 Elsevier Inc. All rights reserved