Maëllie Midroit1, Marc Thevenet1, Arnaud Fournel1, Joelle Sacquet1, Moustafa Bensafi1, Marine Breton1, Laura Chalençon1, Matthias Cavelius1, Anne Didier1, Nathalie Mandairon2. 1. CNRS, UMR 5292, INSERM, U1028, Lyon Neuroscience Research Center, Neuroplasticity and Neuropathology of Olfactory Perception Team, Lyon, F-69000, France; University Lyon, F-69000, France; University Lyon 1, Villeurbanne, F-69000, France. 2. CNRS, UMR 5292, INSERM, U1028, Lyon Neuroscience Research Center, Neuroplasticity and Neuropathology of Olfactory Perception Team, Lyon, F-69000, France; University Lyon, F-69000, France; University Lyon 1, Villeurbanne, F-69000, France. Electronic address: nathalie.mandairon@cnrs.fr.
Abstract
BACKGROUND: Cellular imagery using histology sections is one of the most common techniques used in Neuroscience. However, this inescapable technique has severe limitations due to the need to delineate regions of interest on each brain, which is time consuming and variable across experimenters. NEW METHOD: We developed algorithms based on a vectors field elastic registration allowing fast, automatic realignment of experimental brain sections and associated labeling in a brain atlas with high accuracy and in a streamlined way. Thereby, brain areas of interest can be finely identified without outlining them and different experimental groups can be easily analyzed using conventional tools. This method directly readjusts labeling in the brain atlas without any intermediate manipulation of images. RESULTS: We mapped the expression of cFos, in the mouse brain (C57Bl/6J) after olfactory stimulation or a non-stimulated control condition and found an increased density of cFos-positive cells in the primary olfactory cortex but not in non-olfactory areas of the odor-stimulated animals compared to the controls. COMPARISON WITH EXISTING METHOD(S): Existing methods of matching are based on image registration which often requires expensive material (two-photon tomography mapping or imaging with iDISCO) or are less accurate since they are based on mutual information contained in the images. Our new method is non-imaged based and relies only on the positions of detected labeling and the external contours of sections. CONCLUSIONS: We thus provide a new method that permits automated matching of histology sections of experimental brains with a brain reference atlas.
BACKGROUND: Cellular imagery using histology sections is one of the most common techniques used in Neuroscience. However, this inescapable technique has severe limitations due to the need to delineate regions of interest on each brain, which is time consuming and variable across experimenters. NEW METHOD: We developed algorithms based on a vectors field elastic registration allowing fast, automatic realignment of experimental brain sections and associated labeling in a brain atlas with high accuracy and in a streamlined way. Thereby, brain areas of interest can be finely identified without outlining them and different experimental groups can be easily analyzed using conventional tools. This method directly readjusts labeling in the brain atlas without any intermediate manipulation of images. RESULTS: We mapped the expression of cFos, in the mouse brain (C57Bl/6J) after olfactory stimulation or a non-stimulated control condition and found an increased density of cFos-positive cells in the primary olfactory cortex but not in non-olfactory areas of the odor-stimulated animals compared to the controls. COMPARISON WITH EXISTING METHOD(S): Existing methods of matching are based on image registration which often requires expensive material (two-photon tomography mapping or imaging with iDISCO) or are less accurate since they are based on mutual information contained in the images. Our new method is non-imaged based and relies only on the positions of detected labeling and the external contours of sections. CONCLUSIONS: We thus provide a new method that permits automated matching of histology sections of experimental brains with a brain reference atlas.