Sexually dimorphic melanin-based colour polymorphism, feather melanin content, and wing feather structure in the barn owl (Tyto alba)

Feathers confer protection against biophysical agents and determine flying ability. The geometry and arrangement of the barbs, together with the keratin and pigments deposited in the feathers, determine the mechanical stability of the vane, and its stiffness and resistance to abrasive agents. In colour-polymorphic species, individuals display alternative colour morphs, which can be associated with different foraging strategies. Each morph may therefore require specific flying abilities, and their feathers may be exposed to different abrasive agents. Feathers of differently coloured individuals may thus have a specific structure, and colour pigments may help resist abrasive agents and improve stiffness. We examined these predictions in the barn owl (Tyto alba), a species for which the ventral body side varies from white to dark reddish pheomelanic, and in the number and size of black spots located at the tip of the feathers. White and reddish birds show different foraging strategies, and the size of black feather spots is associated with several phenotypic attributes. We found that birds displaying a darker reddish coloration on the ventral body side deposit more melanin pigments in their remiges, which also have fewer barbs. This suggests that wear resistance increases with darkness, whereas feathers of lighter coloured birds may bend less easily. Accordingly, individuals displaying a lighter reddish coloration on the ventral body side, and those displaying larger black spots, displayed more black transverse bars on their remiges: as larger-spotted individuals are heavier and longer-winged birds also have more transverse bars, these bars may reduce feather bending when flying. We conclude that differently coloured individuals produce wing feathers of different strengths to adopt alternative behavioural and life history strategies

Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease.

Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.