From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder
We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us t...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2015
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| Online Access: | http://hdl.handle.net/1721.1/100421 https://orcid.org/0000-0003-2516-731X |
| _version_ | 1811078949488295936 |
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| author | Venkataraman, Archana Kubicki, Marek Golland, Polina |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Venkataraman, Archana Kubicki, Marek Golland, Polina |
| author_sort | Venkataraman, Archana |
| collection | MIT |
| description | We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. |
| first_indexed | 2024-09-23T11:07:47Z |
| format | Article |
| id | mit-1721.1/100421 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:07:47Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1004212022-10-01T01:27:04Z From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder Venkataraman, Archana Kubicki, Marek Golland, Polina Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Venkataraman, Archana Golland, Polina We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. National Alliance for Medical Image Computing (U.S.) (Grant NIH NIBIB NAMIC U54-EB005149) Neuroimaging Analysis Center (U.S.) (Grant NIH NCRR NAC P41-RR13218) Neuroimaging Analysis Center (U.S.) (Grant NIH NCRR NAC P41-EB015902) National Science Foundation (U.S.) (CAREER Grant 0642971) National Institutes of Health (U.S.) (R01MH074794) National Institutes of Health (U.S.). Advanced Multimodal Neuroimaging Training Program 2015-12-18T02:18:03Z 2015-12-18T02:18:03Z 2013-07 Article http://purl.org/eprint/type/JournalArticle 0278-0062 1558-254X http://hdl.handle.net/1721.1/100421 Venkataraman, Archana, Marek Kubicki, and Polina Golland. “From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder.” IEEE Trans. Med. Imaging 32, no. 11 (November 2013): 2078–2098. https://orcid.org/0000-0003-2516-731X en_US http://dx.doi.org/10.1109/tmi.2013.2272976 IEEE Transactions on Medical Imaging Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) PMC |
| spellingShingle | Venkataraman, Archana Kubicki, Marek Golland, Polina From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title | From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title_full | From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title_fullStr | From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title_full_unstemmed | From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title_short | From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder |
| title_sort | from connectivity models to region labels identifying foci of a neurological disorder |
| url | http://hdl.handle.net/1721.1/100421 https://orcid.org/0000-0003-2516-731X |
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