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Reichmann, F; Painsipp, E; Holzer, P; Kummer, D; Bock, E; Leitinger, G.
A novel unbiased counting method for the quantification of synapses in the mouse brain.
J Neurosci Methods. 2015; 240(6):13-21 Doi: 10.1016/j.jneumeth.2014.10.020 [OPEN ACCESS]
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Führende Autor*innen der Med Uni Graz
Leitinger Gerd
Reichmann Florian
Co-Autor*innen der Med Uni Graz
Bock Elisabeth
Holzer Peter
Kummer Daniel
Singewald Evelin

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The numerical density of synapses and their ultrastructural features are best assessed with electron microscopy. Counting is done within counting frames placed on a pair of sections (disector technique). But this requires that the thin sections are taken from comparable brain regions and the disectors are placed in a uniform random fashion. Small brain areas like the polymorph layer of the mouse dentate gyrus are difficult to encounter, and manually moving the microscope stage for placing the micrographs seems arbitrary. Here the polymorph layer was approximated with 20μm thin, Nissl-stained vibratome sections. The subsequent vibratome section was processed for electron microscopy and serially thin sectioned. The microscope stage was moved using a random number generator, placing at least 20 disectors onto a pair of sections. The numerical synapse density, the numerical density of dense-core vesicles, and other ultrastructural features were compared between mice that had been kept in an enriched environment and mice kept under standard housing conditions. Environmental enrichment significantly decreased the numerical density of dense-core vesicles and synaptic cleft widths within the polymorph layer, associated with behavioral improvement in the Morris water maze, a hippocampus-dependent task of spatial learning and memory. This procedure was easy to handle and enabled us to produce thin sections in small, defined brain areas. Furthermore, placing the disectors with random numbers excluded observer bias. Our procedure provides an uncomplicated way of assessing numerical densities in small brain areas in an unbiased manner. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
Find related publications in this database (using NLM MeSH Indexing)
Animals -
Dentate Gyrus - ultrastructure
Environment -
Female -
Housing, Animal -
Maze Learning -
Mice, Inbred C57BL -
Microscopy, Electron - methods
Pattern Recognition, Automated - methods
Secretory Vesicles - ultrastructure
Software -
Spatial Memory -
Synapses - ultrastructure

Find related publications in this database (Keywords)
Environmental enrichment
Electron microscopy
Dentate gyrus
Dense core vesicle
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