Functional Neuroimaging in the New Era of Big Data
The field of functional neuroimaging has substantially advanced as a big data science in the past decade, thanks to international collaborative projects and community efforts. Here we conducted a literature review on functional neuroimaging, with focus on three general challenges in big data tasks:...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-08-01
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| Series: | Genomics, Proteomics & Bioinformatics |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1672022919301603 |
| _version_ | 1797369794138210304 |
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| author | Xiang Li Ning Guo Quanzheng Li |
| author_facet | Xiang Li Ning Guo Quanzheng Li |
| author_sort | Xiang Li |
| collection | DOAJ |
| description | The field of functional neuroimaging has substantially advanced as a big data science in the past decade, thanks to international collaborative projects and community efforts. Here we conducted a literature review on functional neuroimaging, with focus on three general challenges in big data tasks: data collection and sharing, data infrastructure construction, and data analysis methods. The review covers a wide range of literature types including perspectives, database descriptions, methodology developments, and technical details. We show how each of the challenges was proposed and addressed, and how these solutions formed the three core foundations for the functional neuroimaging as a big data science and helped to build the current data-rich and data-driven community. Furthermore, based on our review of recent literature on the upcoming challenges and opportunities toward future scientific discoveries, we envisioned that the functional neuroimaging community needs to advance from the current foundations to better data integration infrastructure, methodology development toward improved learning capability, and multi-discipline translational research framework for this new era of big data. Keywords: Big data, Neuroimaging, Machine learning, Health informatics, fMRI |
| first_indexed | 2024-03-08T17:52:02Z |
| format | Article |
| id | doaj.art-4f5808d8c9d44909a37031f1ce07518e |
| institution | Directory Open Access Journal |
| issn | 1672-0229 |
| language | English |
| last_indexed | 2024-03-08T17:52:02Z |
| publishDate | 2019-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Genomics, Proteomics & Bioinformatics |
| spelling | doaj.art-4f5808d8c9d44909a37031f1ce07518e2024-01-02T07:13:40ZengElsevierGenomics, Proteomics & Bioinformatics1672-02292019-08-01174393401Functional Neuroimaging in the New Era of Big DataXiang Li0Ning Guo1Quanzheng Li2Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USAMassachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USACorresponding author.; Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USAThe field of functional neuroimaging has substantially advanced as a big data science in the past decade, thanks to international collaborative projects and community efforts. Here we conducted a literature review on functional neuroimaging, with focus on three general challenges in big data tasks: data collection and sharing, data infrastructure construction, and data analysis methods. The review covers a wide range of literature types including perspectives, database descriptions, methodology developments, and technical details. We show how each of the challenges was proposed and addressed, and how these solutions formed the three core foundations for the functional neuroimaging as a big data science and helped to build the current data-rich and data-driven community. Furthermore, based on our review of recent literature on the upcoming challenges and opportunities toward future scientific discoveries, we envisioned that the functional neuroimaging community needs to advance from the current foundations to better data integration infrastructure, methodology development toward improved learning capability, and multi-discipline translational research framework for this new era of big data. Keywords: Big data, Neuroimaging, Machine learning, Health informatics, fMRIhttp://www.sciencedirect.com/science/article/pii/S1672022919301603 |
| spellingShingle | Xiang Li Ning Guo Quanzheng Li Functional Neuroimaging in the New Era of Big Data Genomics, Proteomics & Bioinformatics |
| title | Functional Neuroimaging in the New Era of Big Data |
| title_full | Functional Neuroimaging in the New Era of Big Data |
| title_fullStr | Functional Neuroimaging in the New Era of Big Data |
| title_full_unstemmed | Functional Neuroimaging in the New Era of Big Data |
| title_short | Functional Neuroimaging in the New Era of Big Data |
| title_sort | functional neuroimaging in the new era of big data |
| url | http://www.sciencedirect.com/science/article/pii/S1672022919301603 |
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