Psychology

Task (project management)

Economics

Effects of sleep deprivation on cognitive performance

Geometry

Functional connectivity

Correlation

Neuroscience

Mathematics

Management

Default mode network

Cognitive psychology

Elementary cognitive task

Cognition

Working memory

Connectome

Human Connectome Project

Neuroimaging

Human Brain Mapping

General cognitive ability (GCA) refers to a trait‐like ability that contributes to performance across diverse cognitive tasks. Identifying brain‐based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole‐brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N ‐back working memory task as well as six other tasks in the Human Connectome Project dataset ( n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2 ‐ back versus 0 ‐ back contrast achieved a 0.50 correlation with GCA scores in 10‐fold cross‐validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation—a brain activation pattern associated with executive processing and higher cognitive demand—are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain‐based prediction of GCA.

Toward a “treadmill test” for cognition: Improved prediction of general cognitive ability from the task activated brain