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JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

Ribes D, Parafita J, Charrier R, Magara F, Magistretti PJ, Thiran JP - PLoS ONE (2010)

Bottom Line: This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license.The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis.Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

View Article: PubMed Central - PubMed

Affiliation: Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

ABSTRACT
In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

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Activation results during learning (Day 1).A: JULIDE results. At Day 1, the hippocampus (HP) and the parietal associative cortex (PTLp) are the most activated regions during learning, whereas after the task they are no longer activated. t-test comparison between Day 1 trained mice and Active Control (AC). Uncorrected p-value  = 0.02. Clusters circled in red show significant activation after FWE and FDR corrections (corrected p-values <0.01). B: MCID results for the parietal associative cortex (PTLp). Increase in glucose consumption, measured as 2DG uptake, in the parietal cortex (PTL) the first (Day 1) day of training. t-test comparison between Day 1 trained mice (n = 7) and Active Control (AC; n = 8). *p-value <0.01.
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pone-0014094-g005: Activation results during learning (Day 1).A: JULIDE results. At Day 1, the hippocampus (HP) and the parietal associative cortex (PTLp) are the most activated regions during learning, whereas after the task they are no longer activated. t-test comparison between Day 1 trained mice and Active Control (AC). Uncorrected p-value  = 0.02. Clusters circled in red show significant activation after FWE and FDR corrections (corrected p-values <0.01). B: MCID results for the parietal associative cortex (PTLp). Increase in glucose consumption, measured as 2DG uptake, in the parietal cortex (PTL) the first (Day 1) day of training. t-test comparison between Day 1 trained mice (n = 7) and Active Control (AC; n = 8). *p-value <0.01.

Mentions: Figure 5A shows the activation map obtained with JULIDE during the first day of training. Clusters circled in red are the significantly activated ones (p-value lower than 1% after FWE and FDR correction. As we can see, the hippocampus, an area that is well known to be implicated in spatial memory, is activated during the learning task the first day of training. The other activated region we can see on this figure is the parietal associative cortex that integrates sensory information from different modalities as vision, touch and audition, being involved in spatial navigation and visual processing. The t-test comparison was done between trained mice for one day and Active Controls. In figure 5B, results obtained from the MCID software concerning the parietal associative cortex show an increase in glucose utilization (about 10% more) the first day of training (Day 1) when compared to the Active Control, which is corresponding to JULIDE results showing in figure 5A. Notice that a strong activation appears in the ventricles, which obviously reveals variability in periventricular shape across animals, preventing a perfect alignment of the datasets in this region.


JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

Ribes D, Parafita J, Charrier R, Magara F, Magistretti PJ, Thiran JP - PLoS ONE (2010)

Activation results during learning (Day 1).A: JULIDE results. At Day 1, the hippocampus (HP) and the parietal associative cortex (PTLp) are the most activated regions during learning, whereas after the task they are no longer activated. t-test comparison between Day 1 trained mice and Active Control (AC). Uncorrected p-value  = 0.02. Clusters circled in red show significant activation after FWE and FDR corrections (corrected p-values <0.01). B: MCID results for the parietal associative cortex (PTLp). Increase in glucose consumption, measured as 2DG uptake, in the parietal cortex (PTL) the first (Day 1) day of training. t-test comparison between Day 1 trained mice (n = 7) and Active Control (AC; n = 8). *p-value <0.01.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2991313&req=5

pone-0014094-g005: Activation results during learning (Day 1).A: JULIDE results. At Day 1, the hippocampus (HP) and the parietal associative cortex (PTLp) are the most activated regions during learning, whereas after the task they are no longer activated. t-test comparison between Day 1 trained mice and Active Control (AC). Uncorrected p-value  = 0.02. Clusters circled in red show significant activation after FWE and FDR corrections (corrected p-values <0.01). B: MCID results for the parietal associative cortex (PTLp). Increase in glucose consumption, measured as 2DG uptake, in the parietal cortex (PTL) the first (Day 1) day of training. t-test comparison between Day 1 trained mice (n = 7) and Active Control (AC; n = 8). *p-value <0.01.
Mentions: Figure 5A shows the activation map obtained with JULIDE during the first day of training. Clusters circled in red are the significantly activated ones (p-value lower than 1% after FWE and FDR correction. As we can see, the hippocampus, an area that is well known to be implicated in spatial memory, is activated during the learning task the first day of training. The other activated region we can see on this figure is the parietal associative cortex that integrates sensory information from different modalities as vision, touch and audition, being involved in spatial navigation and visual processing. The t-test comparison was done between trained mice for one day and Active Controls. In figure 5B, results obtained from the MCID software concerning the parietal associative cortex show an increase in glucose utilization (about 10% more) the first day of training (Day 1) when compared to the Active Control, which is corresponding to JULIDE results showing in figure 5A. Notice that a strong activation appears in the ventricles, which obviously reveals variability in periventricular shape across animals, preventing a perfect alignment of the datasets in this region.

Bottom Line: This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license.The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis.Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

View Article: PubMed Central - PubMed

Affiliation: Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

ABSTRACT
In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

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