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Author Emorales, Juan ♦ Edefelipe, Javier ♦ Emerchanperez, Angel ♦ Erodriguez, Ángel ♦ Ealonsonanclares, Lidia ♦ Erodriguez, Josérodrigo
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher Frontiers Media S.A.
File Format HTM / HTML
Date Created 2014-05-22
Copyright Year ©2011
Language English
Subject Domain (in LCC) RC321-571 ♦ QM1-695
Subject Keyword Scanning electron microscopy ♦ Biological psychiatry ♦ Neurosciences ♦ Human anatomy ♦ Quantification ♦ Software ♦ Internal medicine ♦ Medicine ♦ 3D Reconstruction ♦ Neuropsychiatry ♦ Synapses ♦ Science ♦ Segmentation
Abstract The synapses in the cerebral cortex can be classified into two main types, Gray’s type I and type II, which correspond to asymmetric (mostly glutamatergic excitatory) and symmetric (inhibitory GABAergic) synapses, respectively. Hence, the quantification and identification of their different types and the proportions in which they are found, is extraordinarily important in terms of brain function. The ideal approach to calculate the number of synapses per unit volume is to analyze three-dimensional samples reconstructed from serial sections. However, obtaining serial sections by transmission electron microscopy is an extremely time consuming and technically demanding task. Using FIB/SEM microscopy, we recently showed that virtually all synapses can be accurately identified as asymmetric or symmetric synapses when they are visualized, reconstructed and quantified from large three-dimensional tissue samples obtained in an automated manner. Nevertheless, the analysis, segmentation and quantification of synapses is still a labor intensive procedure. Thus, novel solutions are currently necessary to deal with the large volume of data that is being generated by automated 3D electron microscopy. Accordingly, we have developed ESPINA, a software tool that performs the automated segmentation and counting of synapses in a reconstructed 3D volume of the cerebral cortex, and that greatly facilitates and accelerates these processes.
ISSN 16625129
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2011-03-01
e-ISSN 16625129
Journal Frontiers in Neuroanatomy
Volume Number 5


Source: Directory of Open Access Journals (DOAJ)