4.4 Article

High-resolution paraventricular nucleus serial section model constructed within a traditional rat brain atlas

期刊

NEUROSCIENCE LETTERS
卷 438, 期 1, 页码 85-89

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.neulet.2008.04.057

关键词

brain model; brain regionalization; computer graphics; hypothalamus

资金

  1. NINDS NIH HHS [R01-NS16686, R01 NS016686, R01 NS016686-27, R01 NS050792-04, R01 NS050792, R01-NS050792] Funding Source: Medline

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As a starting point for constructing a high-resolution, resliceable computer graphics model for the extraction, quantitative analysis, display, and modeling of neuroanatomical data the outer border and the boundaries of inner divisions and parts of the paraventricular nucleus have been drawn for all 39 serial histological sections prepared for a published reference atlas of the rat brain. This careful parceling revealed three new features of paraventricular nucleus topography: the full rostral extent of the anterior parvicellular part, the caudal end of the medial magnocellular part, and a thin rostrolateral extension of the dorsal medial parvicellular part composed at least in part of neurons expressing corticotropin-releasing hormone. The vector graphics drawings were aligned using the already established alignment of nine consecutive, relevant Atlas Levels, and then contours were smoothed to eliminate nonlinear distortions associated with histological mounting. This dataset was then used to create three-dimensional contour and surface models of the paraventricular nucleus, as well as two-dimensional horizontal and sagittal projections of its outer border. The computer graphics files containing raw and smoothed drawings for all 39 serial sections are supplied for use by researchers interested in developing new or better computer graphics analysis tools involving the paraventricular nucleus. This work may also stimulate the long range goal of creating a high-resolution, resliceable, computer graphics model of the whole brain, and eventually the whole nervous system, that is useful for quantitative analysis and topological transformation. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

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