We have located links that may give you full text access.
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Connectivity-Based Brain Parcellation: A Connectivity-Based Atlas for Schizophrenia Research.
Neuroinformatics 2016 January
Defining brain structures of interest is an important preliminary step in brain-connectivity analysis. Researchers interested in connectivity patterns among brain structures typically employ manually delineated volumes of interest, or regions in a readily available atlas, to limit the scope of connectivity analysis to relevant regions. However, most structural brain atlases, and manually delineated volumes of interest, do not take voxel-wise connectivity patterns into consideration, and therefore may not be ideal for anatomic connectivity analysis. We herein propose a method to parcellate the brain into regions of interest based on connectivity. We formulate connectivity-based parcellation as a graph-cut problem, which we solve approximately using a novel multi-class Hopfield network algorithm. We demonstrate the application of this approach using diffusion tensor imaging data from an ongoing study of schizophrenia. Compared to a standard anatomic atlas, the connectivity-based atlas supports better classification performance when distinguishing schizophrenic from normal subjects. Comparing connectivity patterns averaged across the normal and schizophrenic subjects, we note significant systematic differences between the two atlases.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app