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Alexandra Badea

Publications and source records attributed to Alexandra Badea.

3 recordsLinked to original sources

Neuroanatomical phenotypes in the reeler mouse.

The reeler mouse (Reln) has been proposed as a neurodevelopmental model for certain neurological and psychiatric conditions and has been studied by qualitative histochemistry and electron microscopy. Using magnetic resonance microscopy (MRM), we have quantitated for the first time the neuromorphology of Reln mice at a resolution of 21.5 microm. The neuroanatomical phenotypes of heterozygous and homozygous mutant Reln mice were compared to those of wild type (WT) littermates using morphometry and texture analysis. The cortical, hippocampal, and cerebellar phenotypes of the heterozygous and homozygous mutant Reln mice were confirmed, and new features were revealed. The Reln(rl/rl) mice possessed a smaller brain, and both Reln(rl/+) and Reln(rl/rl) mice had increased ventricles compared to WT controls. Shape differences were found between WT and Reln(rl/rl) brains, specifically in cerebellum, olfactory bulbs, dorsomedial frontal and parietal cortex, certain regions of temporal and occipital lobes, as well as in the lateral ventricles and ventral hippocampus. These findings suggest that certain brain regions may be more severely impacted by the Reln mutation than others. Gadolinium-based active staining demonstrated that layers of the hippocampus were disorganized in Reln(rl/rl) mice and differences in thickness of these layers were identified between WT and Reln(rl/rl) mice. The intensity distributions characteristic to the dorsal, middle, and ventral hippocampus were altered in the Reln(rl/rl), especially in the ventral hippocampus. These differences were quantified using skewness and modeling the intensity distributions with a Gaussian mixture. Our results suggest that structural features of Reln(rl/rl) brain most closely phenocopy those of patients with Norman-Roberts lissencephaly.

Animals↗

Automated segmentation of neuroanatomical structures in multispectral MR microscopy of the mouse brain.

We present the automated segmentation of magnetic resonance microscopy (MRM) images of the C57BL/6J mouse brain into 21 neuroanatomical structures, including the ventricular system, corpus callosum, hippocampus, caudate putamen, inferior colliculus, internal capsule, globus pallidus, and substantia nigra. The segmentation algorithm operates on multispectral, three-dimensional (3D) MR data acquired at 90-microm isotropic resolution. Probabilistic information used in the segmentation is extracted from training datasets of T2-weighted, proton density-weighted, and diffusion-weighted acquisitions. Spatial information is employed in the form of prior probabilities of occurrence of a structure at a location (location priors) and the pairwise probabilities between structures (contextual priors). Validation using standard morphometry indices shows good consistency between automatically segmented and manually traced data. Results achieved in the mouse brain are comparable with those achieved in human brain studies using similar techniques. The segmentation algorithm shows excellent potential for routine morphological phenotyping of mouse models.

Algorithms↗

Surface visualization of electromagnetic brain activity.

Advances in hardware and software have made possible the reconstruction of brain activity from non-invasive electrophysiological measurements over a large part of the brain. The appreciation of the information content in the data is enhanced when relevant anatomical detail is also available for visualization. Different neuroscientific questions give rise to different requirements for optimal superposition of structure and function. Most available software deal with scalar measures of activity, especially hemodynamic changes. In contrast, the electrophysiological observables are generated by electrical activity, which depends on the synchrony of neuronal assemblies and the geometry of the local cortical surface. We describe methods for segmentation and visualization of spatio-temporal brain activity, which allow the interplay of geometry and scalar as well as vector properties of the current density directly in the representations. The utility of these methods is demonstrated through displays of tomographic reconstructions of early sensory processing in the somatosensory and visual modality extracted from magnetoencephalography (MEG) data. The activation course characteristic to a specific area could be observed as current density or statistical maps independently and/or contrasted to the activity in other areas or the whole brain. MEG and functional magnetic resonance imaging (fMRI) activations were simultaneously visualized. Integrating and visualizing complementary functional data into a single environment helps evaluating analysis and understanding structure/function relationships in normal and diseased brain.

Brain↗