High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter
Abstract Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-21543-3 |
| _version_ | 1811223330253963264 |
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| author | Hari McGrath Hitten P. Zaveri Evan Collins Tamara Jafar Omar Chishti Sami Obaid Alexander Ksendzovsky Kun Wu Xenophon Papademetris Dennis D. Spencer |
| author_facet | Hari McGrath Hitten P. Zaveri Evan Collins Tamara Jafar Omar Chishti Sami Obaid Alexander Ksendzovsky Kun Wu Xenophon Papademetris Dennis D. Spencer |
| author_sort | Hari McGrath |
| collection | DOAJ |
| description | Abstract Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure–function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy’s Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions. |
| first_indexed | 2024-04-12T08:31:06Z |
| format | Article |
| id | doaj.art-ac3dd8becadc4d6d828271300d43d153 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-12T08:31:06Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-ac3dd8becadc4d6d828271300d43d1532022-12-22T03:40:13ZengNature PortfolioScientific Reports2045-23222022-11-0112111110.1038/s41598-022-21543-3High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeterHari McGrath0Hitten P. Zaveri1Evan Collins2Tamara Jafar3Omar Chishti4Sami Obaid5Alexander Ksendzovsky6Kun Wu7Xenophon Papademetris8Dennis D. Spencer9Department of Neurosurgery, Yale School of MedicineDepartment of Neurology, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineDepartment of Radiology and Biomedical Engineering, Yale School of MedicineDepartment of Neurosurgery, Yale School of MedicineAbstract Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure–function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy’s Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions.https://doi.org/10.1038/s41598-022-21543-3 |
| spellingShingle | Hari McGrath Hitten P. Zaveri Evan Collins Tamara Jafar Omar Chishti Sami Obaid Alexander Ksendzovsky Kun Wu Xenophon Papademetris Dennis D. Spencer High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter Scientific Reports |
| title | High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| title_full | High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| title_fullStr | High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| title_full_unstemmed | High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| title_short | High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| title_sort | high resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter |
| url | https://doi.org/10.1038/s41598-022-21543-3 |
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