A distributed brain network predicts general intelligence from resting-state human neuroimaging data
-
- Julien Dubois
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
-
- Paola Galdi
- Department of Management and Innovation Systems, University of Salerno, Fisciano Salerno, Italy
-
- Lynn K. Paul
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
-
- Ralph Adolphs
- Division of Humanities and Social Sciences, Pasadena, CA 91125, USA
Description
<jats:p>Individual people differ in their ability to reason, solve problems, think abstractly, plan and learn. A reliable measure of this general ability, also known as intelligence, can be derived from scores across a diverse set of cognitive tasks. There is great interest in understanding the neural underpinnings of individual differences in intelligence, because it is the single best predictor of long-term life success. The most replicated neural correlate of human intelligence to date is total brain volume; however, this coarse morphometric correlate says little about function. Here, we ask whether measurements of the activity of the resting brain (resting-state fMRI) might also carry information about intelligence. We used the final release of the Young Adult Human Connectome Project (<jats:italic>N</jats:italic>= 884 subjects after exclusions), providing a full hour of resting-state fMRI per subject; controlled for gender, age and brain volume; and derived a reliable estimate of general intelligence from scores on multiple cognitive tasks. Using a cross-validated predictive framework, we predicted 20% of the variance in general intelligence in the sampled population from their resting-state connectivity matrices. Interestingly, no single anatomical structure or network was responsible or necessary for this prediction, which instead relied on redundant information distributed across the brain.</jats:p><jats:p>This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive abilities’.</jats:p>
Journal
-
- Philosophical Transactions of the Royal Society B: Biological Sciences
-
Philosophical Transactions of the Royal Society B: Biological Sciences 373 (1756), 20170284-, 2018-08-13
The Royal Society
- Tweet
Details 詳細情報について
-
- CRID
- 1360857597410177152
-
- ISSN
- 14712970
- 09628436
-
- Data Source
-
- Crossref