Weak structural connectivity nonlinearly underlying human cognitive abilities
Rong Wang, Zhao Chang, Xuechun Liu, Daniel Kristanto, \'Etienne G\'erard Guy Gartner, Xinyang Liu, Mianxin Liu, Ying Wu, Ming Lui, Changsong Zhou

TL;DR
This study reveals that weak brain structural connectivity, previously ignored as noise, plays a crucial nonlinear role in supporting human cognitive abilities, influencing individual variability, functional connectivity, and brain network capacity.
Contribution
It introduces a new approach to preserve and analyze weak connectivity, demonstrating its importance in cognition and providing a more reliable method for brain structural connectivity analysis.
Findings
Weak connectivity correlates with cognitive abilities and memory.
Weak links expand brain network capacity for integration and segregation.
A specific weak connection links visual/motor to limbic areas with negative gene co-expression.
Abstract
Human cognition is supported by brain structural connectivity wherein weak connectivity with weights several orders of magnitude smaller than those of strong connectivity, has been treated as noise and ignored from analysis over a long time. We here propose that weak connectivity plays roles to cognitive abilities by nonlinearly amplifying its small weights. Using the HCP dataset (n=999) and multiple tractography algorithms, we found that weak connectivity involves high individual variability and contributes to predictions of general cognitive ability and memory, and it is also critical for brain functional connectivity simulation and structure-function coupling. Importantly, we fused two post-tractography filtering methods to generate more reliable connectivity that preserves weak links and outperforms conventional thresholding. At the network level, we showed that weak connectivity…
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Taxonomy
TopicsCognitive Abilities and Testing · Cognitive Science and Mapping
