On quantification and maximization of information transfer in network dynamical systems
Abstract Information flow among nodes in a complex network describes the overall cause-effect relationships among the nodes and provides a better understanding of the contributions of these nodes individually or collectively towards the underlying network dynamics. Variations in network topologies r...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-32762-7 |
| _version_ | 1797850110835556352 |
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| author | Moirangthem Sailash Singh Ramkrishna Pasumarthy Umesh Vaidya Steffen Leonhardt |
| author_facet | Moirangthem Sailash Singh Ramkrishna Pasumarthy Umesh Vaidya Steffen Leonhardt |
| author_sort | Moirangthem Sailash Singh |
| collection | DOAJ |
| description | Abstract Information flow among nodes in a complex network describes the overall cause-effect relationships among the nodes and provides a better understanding of the contributions of these nodes individually or collectively towards the underlying network dynamics. Variations in network topologies result in varying information flows among nodes. We integrate theories from information science with control network theory into a framework that enables us to quantify and control the information flows among the nodes in a complex network. The framework explicates the relationships between the network topology and the functional patterns, such as the information transfers in biological networks, information rerouting in sensor nodes, and influence patterns in social networks. We show that by designing or re-configuring the network topology, we can optimize the information transfer function between two chosen nodes. As a proof of concept, we apply our proposed methods in the context of brain networks, where we reconfigure neural circuits to optimize excitation levels among the excitatory neurons. |
| first_indexed | 2024-04-09T18:55:04Z |
| format | Article |
| id | doaj.art-94a00260d18d4393a63ae9f7a77c8294 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T18:55:04Z |
| publishDate | 2023-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-94a00260d18d4393a63ae9f7a77c82942023-04-09T11:14:48ZengNature PortfolioScientific Reports2045-23222023-04-0113111110.1038/s41598-023-32762-7On quantification and maximization of information transfer in network dynamical systemsMoirangthem Sailash Singh0Ramkrishna Pasumarthy1Umesh Vaidya2Steffen Leonhardt3Electrical Department, IIT MadrasElectrical Department, IIT MadrasMechanical Department, Clemson UniversityChair for Medical Information Technology, RWTH Aachen UniversityAbstract Information flow among nodes in a complex network describes the overall cause-effect relationships among the nodes and provides a better understanding of the contributions of these nodes individually or collectively towards the underlying network dynamics. Variations in network topologies result in varying information flows among nodes. We integrate theories from information science with control network theory into a framework that enables us to quantify and control the information flows among the nodes in a complex network. The framework explicates the relationships between the network topology and the functional patterns, such as the information transfers in biological networks, information rerouting in sensor nodes, and influence patterns in social networks. We show that by designing or re-configuring the network topology, we can optimize the information transfer function between two chosen nodes. As a proof of concept, we apply our proposed methods in the context of brain networks, where we reconfigure neural circuits to optimize excitation levels among the excitatory neurons.https://doi.org/10.1038/s41598-023-32762-7 |
| spellingShingle | Moirangthem Sailash Singh Ramkrishna Pasumarthy Umesh Vaidya Steffen Leonhardt On quantification and maximization of information transfer in network dynamical systems Scientific Reports |
| title | On quantification and maximization of information transfer in network dynamical systems |
| title_full | On quantification and maximization of information transfer in network dynamical systems |
| title_fullStr | On quantification and maximization of information transfer in network dynamical systems |
| title_full_unstemmed | On quantification and maximization of information transfer in network dynamical systems |
| title_short | On quantification and maximization of information transfer in network dynamical systems |
| title_sort | on quantification and maximization of information transfer in network dynamical systems |
| url | https://doi.org/10.1038/s41598-023-32762-7 |
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