Schedule of Events | Symposia

Regional, But Not Brain-Wide, Graph Theoretic Metrics Are Robustly and Reproducibly Linked to General Cognitive Ability

Poster Session A - Saturday, March 29, 2025, 3:00 – 5:00 pm EDT, Back Bay Ballroom/Republic Ballroom

M. Fiona Molloy¹ (mfionamolloy@gmail.com), Aman Taxali¹, Mike Angstadt¹, Tristan Greathouse¹, Katherine Toda-Thorne¹, Katherine M. McCurry¹, Alexander Weigard¹, Omid Kardan¹, Lily Burchell¹, Maria Dziubinski¹, Jason Choi¹, Melanie Vandersluis¹, Cleanthis Michael¹, Mary M. Heitzeg¹, Chandra Sripada¹; ¹University of Michigan

General cognitive ability (GCA), also called “general intelligence”, is thought to depend on network properties of the brain, which can be quantified through graph theoretic measures such as small worldness and module degree. An extensive set of studies examined links between GCA and graphical properties of resting state fMRI connectomes. However, these studies often involved small samples, applied just a few graph theory metrics in each study, and yielded inconsistent results, making it challenging to identify the architectural underpinnings of GCA. Here, we address these limitations by systematically investigating univariate and multivariate relationships between GCA and 17 whole-brain and node-level graph theory measures in individuals from the Adolescent Brain Cognitive Development study (N=5,937). GCA was computed using bifactor modeling of a battery of neurocognitive tasks, spanning a range of domains including learning and memory, language, and cognitive control. We demonstrate that whole-brain graph theory measures, including small worldness and global efficiency, fail to exhibit meaningful relationships with GCA. In contrast, multiple node-level graphical measures, especially within-module degree (within-network connectivity), exhibit strong associations with GCA. We establish the robustness of these results by replicating them in a second large sample, the Human Connectome Project (N=847) and across a variety of modeling choices. This study provides the most comprehensive and definitive account to date of complex interrelationships between GCA and graphical properties of the brain’s intrinsic functional architecture.

Topic Area: EXECUTIVE PROCESSES: Other