The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.

PURPOSE: This paper describes an approach for the three-dimensional (3D) shape and pose reconstruction of the human rib cage from few segmented two-dimensional (2D) projection images. Our work is aimed at supporting temporal subtraction techniques of subsequently acquired radiographs by establishing a method for the assessment of pose differences in sequences of chest radiographs of the same patient.

METHODS: The reconstruction method is based on a 3D statistical shape model (SSM) of the rib cage, which is adapted to binary 2D projection images of an individual rib cage. To drive the adaptation we minimize a distance measure that quantifies the dissimilarities between 2D projections of the 3D SSM and the projection images of the individual rib cage. We propose different silhouette-based distance measures and evaluate their suitability for the adaptation of the SSM to the projection images.

RESULTS: An evaluation was performed on 29 sets of biplanar binary images (posterior-anterior and lateral). Depending on the chosen distance measure, our experiments on the combined reconstruction of shape and pose of the rib cages yield reconstruction errors from 2.2 to 4.7 mm average mean 3D surface distance. Given a geometry of an individual rib cage, the rotational errors for the pose reconstruction range from 0.1 degrees to 0.9 degrees.

CONCLUSIONS: The results show that our method is suitable for the estimation of pose differences of the human rib cage in binary projection images. Thus, it is able to provide crucial 3D information for registration during the generation of 2D subtraction images.

In the last decade, the fruit fly Drosophila melanogaster, highly accessible to genetic, behavioral and molecular analyses, has been introduced as a novel model organism to help decipher the complex genetic, neurochemical, and neuroanatomical underpinnings of behaviors induced by drugs of abuse. Here we review these data, focusing specifically on cocaine-related behaviors. Several of cocaine's most characteristic properties have been recapitulated in Drosophila. First, cocaine induces motor behaviors in flies that are remarkably similar to those observed in mammals. Second, repeated cocaine administration induces behavioral sensitization a form of behavioral plasticity believed to underlie certain aspects of addiction. Third, a key role for dopaminergic systems in mediating cocaine's effects has been demonstrated through both pharmacological and genetic methods. Finally, and most importantly, unbiased genetic screens, feasible because of the simplicity and scale with which flies can be manipulated in the laboratory, have identified several novel genes and pathways whose role in cocaine behaviors had not been anticipated. Many of these genes and pathways have been validated in mammalian models of drug addiction. We focus in this review on the role of LIM-only proteins in cocaine-induced behaviors.

We present a fully automatic method for 3D segmentation of the mandibular bone from CT data. The method includes an adaptation of statistical shape models of the mandible, the skull base and the midfacial bones, followed by a simultaneous graph-based optimization of adjacent deformable models. The adaptation of the models to the image data is performed according to a heuristic model of the typical intensity distribution in the vincinity of the bone boundary, with special focus on an accurate discrimination of adjacent bones in joint regions. An evaluation of our method based on 18 CT scans shows that a manual correction of the automatic segmentations is not necessary in approx. 60% of the axial slices that contain the mandible.

We present a novel microscopy technique to measure the scattered wavefront emitted from an optically transparent microscopic object. The complex amplitude is decoded via phase stepping in a common-path interferometer, enabling high mechanical stability. We demonstrate theoretically and practically that the incoherent summation of multiple illumination directions into a single image increases the resolving power and facilitates image reconstruction in diffraction tomography. We propose a slice-by-slice object-scatter extraction algorithm entirely based in real space in combination with ordinary z-stepping. Thereby the computational complexity affiliated with tomographic methods is significantly reduced. Using the first order Born approximation for weakly scattering objects it is possible to obtain estimates of the scattering density from the exitwaves.

Selection of appropriate oviposition sites is essential for progeny survival and fitness in generalist insect species, such as Drosophila melanogaster, yet little is known about the mechanisms regulating how environmental conditions and innate adult preferences are evaluated and balanced to yield the final substrate choice for egg-deposition. Female D. melanogaster are attracted to food containing acetic acid (AA) as an oviposition substrate. However, our observations reveal that this egg-laying preference is a complex process, as it directly opposes an otherwise strong, default behavior of positional avoidance for the same food. We show that 2 distinct sensory modalities detect AA. Attraction to AA-containing food for the purpose of egg-laying relies on the gustatory system, while positional repulsion depends primarily on the olfactory system. Similarly, distinct central brain regions are involved in AA attraction and repulsion. Given this unique situation, in which a single environmental stimulus yields 2 opposing behavioral outputs, we propose that the interaction of egg-laying attraction and positional aversion for AA provides a powerful model for studying how organisms balance competing behavioral drives and integrate signals involved in choice-like processes.

Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest.