Negatively Linking Connector Networks in Cognitive Control of Affective Pictures
Wenhai Zhang1,2, Jing Chen3, Guofang Ren4
1College of Education Science, The Big Data Centre for Cognitive Neuroscience and AI, Hengyang Normal University, Hengyang, China.
Abstract:
Cognitive control of emotions depends on intermodular long-distance communications. However, negative connections between connector hubs are removed by traditional hard-thresholding approach in graph-theoretical research. Using soft-thresholding approach to reserve negative links, we explore time-varying features of connector hubs in intermodular communications during cognitive control of affective pictures. We develop a novel approach to sparse functional networks and construct negatively linking connector networks for positive, negative, and neutral pictures. We find that consisting of flexible hubs, the frontoparietal system dynamically top-down inhibits neural activities through negative connections from the salience subnetwork and visual processing area. Moreover, the shared connectors form functional backbones that dynamically reconfigure according to differently-valenced pictures in order to coordinate both stability and flexibility of cognitive connector networks. These results reveal the necessity of conserving negative links between intermodular communications in chronnectome research and deepen the understanding of how connector networks dynamically evolute during cognitive control of affective processing.
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