bioRxiv preprint doi: https://doi.org/10.1101/257865; this version posted January 31, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A distributed brain network predicts general intelligence from resting-state human neuroimaging data 1,4 5 1,3 1,2,3 Julien Dubois , Paola Galdi , Lynn K. Paul , Ralph Adolphs 1 Division of Humanities and Social Sciences, California Institute of Technology, Pasadena CA 91125, USA 2 Division of Biology and Biological Engineering, California Institute of Technology, Pasadena CA 91125, USA 3 Chen Neuroscience Institute, California Institute of Technology, Pasadena CA 91125, USA 4 Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA 5 Department of Management and Innovation Systems, University of Salerno, Fisciano, Salerno, Italy Correspondence: Julien Dubois Department of Neurosurgery Cedars-Sinai Medical Center, Los Angeles, CA 90048
[email protected] bioRxiv preprint doi: https://doi.org/10.1101/257865; this version posted January 31, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract 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, since it is the single best predictor of long-term life success, and since individual differences in a similar broad ability are found across animal species.