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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Yarkoni, Tal Poldrack, Russell A. Nichols, Thomas E. Van Essen, David C. Wager, Tor D. |
| Description | Country affiliation: United States Author Affiliation: Yarkoni T ( Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, Colorado, USA. tal.yarkoni@colorado.edu) |
| Abstract | The rapid growth of the literature on neuroimaging in humans has led to major advances in our understanding of human brain function but has also made it increasingly difficult to aggregate and synthesize neuroimaging findings. Here we describe and validate an automated brain-mapping framework that uses text-mining, meta-analysis and machine-learning techniques to generate a large database of mappings between neural and cognitive states. We show that our approach can be used to automatically conduct large-scale, high-quality neuroimaging meta-analyses, address long-standing inferential problems in the neuroimaging literature and support accurate 'decoding' of broad cognitive states from brain activity in both entire studies and individual human subjects. Collectively, our results have validated a powerful and generative framework for synthesizing human neuroimaging data on an unprecedented scale. |
| File Format | HTM / HTML |
| ISSN | 15487091 |
| e-ISSN | 15487105 |
| DOI | 10.1038/nmeth.1635 |
| Journal | Nature Methods |
| Issue Number | 8 |
| Volume Number | 8 |
| Language | English |
| Publisher | Nature Publishing Group |
| Publisher Date | 2011-06-26 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Discipline Clinical Laboratory Techniques Brain Mapping Brain Physiology Data Mining Magnetic Resonance Imaging Natural Language Processing Periodicals As Topic Research Support, N.i.h., Extramural |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cell Biology Biochemistry Molecular Biology Biotechnology |
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