Nested expression domains for odorant receptors in zebrafish olfactory epithelium

The mapping of high-dimensional olfactory stimuli onto the two-dimensional surface of the nasal sensory epithelium constitutes the first step in the neuronal encoding of olfactory input. We have used zebrafish as a model system to analyze the spatial distribution of odorant receptor molecules in the olfactory epithelium by quantitative in situ hybridization. To this end, we have cloned 10 very divergent zebrafish odorant receptor molecules by PCR. Individual genes are expressed in sparse olfactory receptor neurons. Analysis of the position of labeled cells in a simplified coordinate system revealed three concentric, albeit overlapping, expression domains for the four odorant receptors analyzed in detail. Such regionalized expression should result in a corresponding segregation of functional response properties. This might represent the first step of spatial encoding of olfactory input or be essential for the development of the olfactory system.

Matchings and phylogenetic trees

This paper presents a natural coordinate system for phylogenetic trees using a correspondence with the set of perfect matchings in the complete graph. This correspondence produces a distance between phylogenetic trees, and a way of enumerating all trees in a minimal step order. It is useful in randomized algorithms because it enables moves on the space of trees that make random optimization strategies “mix” quickly. It also promises a generalization to intermediary trees when data are not decisive as to their choice of tree, and a new way of constructing Bayesian priors on tree space.

Measuring the thickness of the human cerebral cortex from magnetic resonance images

Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test–retest studies, as well as by comparison of cross-subject regional thickness measures with published values.