Title |
Fast reproducible identification and large-scale databasing of individual functional cognitive networks
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Published in |
BMC Neuroscience, October 2007
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DOI | 10.1186/1471-2202-8-91 |
Pubmed ID | |
Authors |
Philippe Pinel, Bertrand Thirion, Sébastien Meriaux, Antoinette Jobert, Julien Serres, Denis Le Bihan, Jean-Baptiste Poline, Stanislas Dehaene |
Abstract |
Although cognitive processes such as reading and calculation are associated with reproducible cerebral networks, inter-individual variability is considerable. Understanding the origins of this variability will require the elaboration of large multimodal databases compiling behavioral, anatomical, genetic and functional neuroimaging data over hundreds of subjects. With this goal in mind, we designed a simple and fast acquisition procedure based on a 5-minute functional magnetic resonance imaging (fMRI) sequence that can be run as easily and as systematically as an anatomical scan, and is therefore used in every subject undergoing fMRI in our laboratory. This protocol captures the cerebral bases of auditory and visual perception, motor actions, reading, language comprehension and mental calculation at an individual level. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 6 | 3% |
United States | 3 | 1% |
Netherlands | 3 | 1% |
Belgium | 2 | <1% |
United Kingdom | 2 | <1% |
Cuba | 1 | <1% |
Australia | 1 | <1% |
Germany | 1 | <1% |
Japan | 1 | <1% |
Other | 1 | <1% |
Unknown | 194 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 57 | 27% |
Student > Ph. D. Student | 47 | 22% |
Student > Master | 25 | 12% |
Professor | 17 | 8% |
Student > Bachelor | 9 | 4% |
Other | 32 | 15% |
Unknown | 28 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 62 | 29% |
Agricultural and Biological Sciences | 29 | 13% |
Neuroscience | 29 | 13% |
Medicine and Dentistry | 21 | 10% |
Engineering | 7 | 3% |
Other | 26 | 12% |
Unknown | 41 | 19% |