Functional and spatial rewiring principles jointly regulate context-sensitive computation.
Adaptive rewiring provides a basic principle of self-organizing connectivity in evolving neural network topology. By selectively adding connections to regions with intense signal flow and deleting underutilized connections, adaptive rewiring generates optimized brain-like, i.e. modular, small-world,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2023-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1011325 |
| _version_ | 1797674053275746304 |
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| author | Jia Li Ilias Rentzeperis Cees van Leeuwen |
| author_facet | Jia Li Ilias Rentzeperis Cees van Leeuwen |
| author_sort | Jia Li |
| collection | DOAJ |
| description | Adaptive rewiring provides a basic principle of self-organizing connectivity in evolving neural network topology. By selectively adding connections to regions with intense signal flow and deleting underutilized connections, adaptive rewiring generates optimized brain-like, i.e. modular, small-world, and rich club connectivity structures. Besides topology, neural self-organization also follows spatial optimization principles, such as minimizing the neural wiring distance and topographic alignment of neural pathways. We simulated the interplay of these spatial principles and adaptive rewiring in evolving neural networks with weighted and directed connections. The neural traffic flow within the network is represented by the equivalent of diffusion dynamics for directed edges: consensus and advection. We observe a constructive synergy between adaptive and spatial rewiring, which contributes to network connectedness. In particular, wiring distance minimization facilitates adaptive rewiring in creating convergent-divergent units. These units support the flow of neural information and enable context-sensitive information processing in the sensory cortex and elsewhere. Convergent-divergent units consist of convergent hub nodes, which collect inputs from pools of nodes and project these signals via a densely interconnected set of intermediate nodes onto divergent hub nodes, which broadcast their output back to the network. Convergent-divergent units vary in the degree to which their intermediate nodes are isolated from the rest of the network. This degree, and hence the context-sensitivity of the network's processing style, is parametrically determined in the evolving network model by the relative prominence of spatial versus adaptive rewiring. |
| first_indexed | 2024-03-11T21:53:31Z |
| format | Article |
| id | doaj.art-3c25ce2d107843aa99ab2cdc3e9d9dc3 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-03-11T21:53:31Z |
| publishDate | 2023-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-3c25ce2d107843aa99ab2cdc3e9d9dc32023-09-26T05:30:56ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582023-08-01198e101132510.1371/journal.pcbi.1011325Functional and spatial rewiring principles jointly regulate context-sensitive computation.Jia LiIlias RentzeperisCees van LeeuwenAdaptive rewiring provides a basic principle of self-organizing connectivity in evolving neural network topology. By selectively adding connections to regions with intense signal flow and deleting underutilized connections, adaptive rewiring generates optimized brain-like, i.e. modular, small-world, and rich club connectivity structures. Besides topology, neural self-organization also follows spatial optimization principles, such as minimizing the neural wiring distance and topographic alignment of neural pathways. We simulated the interplay of these spatial principles and adaptive rewiring in evolving neural networks with weighted and directed connections. The neural traffic flow within the network is represented by the equivalent of diffusion dynamics for directed edges: consensus and advection. We observe a constructive synergy between adaptive and spatial rewiring, which contributes to network connectedness. In particular, wiring distance minimization facilitates adaptive rewiring in creating convergent-divergent units. These units support the flow of neural information and enable context-sensitive information processing in the sensory cortex and elsewhere. Convergent-divergent units consist of convergent hub nodes, which collect inputs from pools of nodes and project these signals via a densely interconnected set of intermediate nodes onto divergent hub nodes, which broadcast their output back to the network. Convergent-divergent units vary in the degree to which their intermediate nodes are isolated from the rest of the network. This degree, and hence the context-sensitivity of the network's processing style, is parametrically determined in the evolving network model by the relative prominence of spatial versus adaptive rewiring.https://doi.org/10.1371/journal.pcbi.1011325 |
| spellingShingle | Jia Li Ilias Rentzeperis Cees van Leeuwen Functional and spatial rewiring principles jointly regulate context-sensitive computation. PLoS Computational Biology |
| title | Functional and spatial rewiring principles jointly regulate context-sensitive computation. |
| title_full | Functional and spatial rewiring principles jointly regulate context-sensitive computation. |
| title_fullStr | Functional and spatial rewiring principles jointly regulate context-sensitive computation. |
| title_full_unstemmed | Functional and spatial rewiring principles jointly regulate context-sensitive computation. |
| title_short | Functional and spatial rewiring principles jointly regulate context-sensitive computation. |
| title_sort | functional and spatial rewiring principles jointly regulate context sensitive computation |
| url | https://doi.org/10.1371/journal.pcbi.1011325 |
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