Difference between revisions of "2014 Project Week:BrainAging"
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| − | Image: | + | Image:aging-1.jpg|[[2014_Winter_Project_Week#Projects|Brain regions with connectivity predictive of effective brain age]] |
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==Key Investigators== | ==Key Investigators== | ||
| − | + | Andrei Irimia, PhD (Institute for Neuroimaging and Informatics, University of Southern California) | |
| + | |||
| + | John D. Van Horn, PhD (Institute for Neuroimaging and Informatics, University of Southern California) | ||
==Project Description== | ==Project Description== | ||
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<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Objective</h3> | <h3>Objective</h3> | ||
| − | * | + | * Brain connectivity loss due to traumatic brain injury, stroke or multiple sclerosis can have serious consequences on life quality and a measurable impact upon neural and cognitive function. |
| + | * Though brain network properties are known to be affected disproportionately by traumatic brain injury to certain gray matter regions, the manner in which white matter insults affect such properties remains poorly understood | ||
| + | * In this project, we seek to use 3D Slicer as a tool for identifying the subset of macroscopic neural connections in the adult human brain which are particularly sensitive to network lesioning, and which lead to accelerated aging of the human brain | ||
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Approach, Plan</h3> | <h3>Approach, Plan</h3> | ||
| + | * MRI and DTI volumes will be co-registered in 3D Slicer before further analysis | ||
| + | * connectivity will be analyzed using 3D Slicer tractography tools | ||
| + | * a multivariate regression model will be implemented to understand which brain connections can be used as biomarkers of effective brain age | ||
* | * | ||
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Progress</h3> | <h3>Progress</h3> | ||
| − | * | + | * we have used 3D Slicer to assist the analysis of TBI effects upon brain connectivity |
| + | * we found that the integrity of WM connections which innervate the paracentral lobule, postcentral sulcus and parieto-occipital sulcus can be used as biomarkers of effective brain age | ||
</div> | </div> | ||
</div> | </div> | ||
Latest revision as of 06:10, 10 January 2014
Home < 2014 Project Week:BrainAging
Key Investigators
Andrei Irimia, PhD (Institute for Neuroimaging and Informatics, University of Southern California)
John D. Van Horn, PhD (Institute for Neuroimaging and Informatics, University of Southern California)
Project Description
Objective
- Brain connectivity loss due to traumatic brain injury, stroke or multiple sclerosis can have serious consequences on life quality and a measurable impact upon neural and cognitive function.
- Though brain network properties are known to be affected disproportionately by traumatic brain injury to certain gray matter regions, the manner in which white matter insults affect such properties remains poorly understood
- In this project, we seek to use 3D Slicer as a tool for identifying the subset of macroscopic neural connections in the adult human brain which are particularly sensitive to network lesioning, and which lead to accelerated aging of the human brain
Approach, Plan
- MRI and DTI volumes will be co-registered in 3D Slicer before further analysis
- connectivity will be analyzed using 3D Slicer tractography tools
- a multivariate regression model will be implemented to understand which brain connections can be used as biomarkers of effective brain age
Progress
- we have used 3D Slicer to assist the analysis of TBI effects upon brain connectivity
- we found that the integrity of WM connections which innervate the paracentral lobule, postcentral sulcus and parieto-occipital sulcus can be used as biomarkers of effective brain age
