Reduced spatial spread of nodes in geometric network models improves topology associated with increased computational capabilities DOI Creative Commons
Nicholas Christiansen, Ioanna Sandvig, Axel Sandvig

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 12, 2024

Biological neural networks are characterized by short average path lengths, high clustering, and modular hierarchical architectures. These complex network topologies strike a balance between local specialization global synchronization via long-range connections, resulting in highly efficient communication. Here, we use geometric model with either an intermediate or connection probability to investigate the effects of wiring cost principles on complexity for different spatial conformations. We find that both probabilities only conform small-world architectures neurons dense clusters due decrease within clusters. Furthermore, small-worldness modularity were reduced systems connections caused reduction allowing novel insight into mechanisms underlying adaptive maladaptive alterations. Our findings corroborate previous work showing distributions play key role development.

Язык: Английский

Reduced spatial spread of nodes in geometric network models improves topology associated with increased computational capabilities DOI Creative Commons
Nicholas Christiansen, Ioanna Sandvig, Axel Sandvig

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 12, 2024

Biological neural networks are characterized by short average path lengths, high clustering, and modular hierarchical architectures. These complex network topologies strike a balance between local specialization global synchronization via long-range connections, resulting in highly efficient communication. Here, we use geometric model with either an intermediate or connection probability to investigate the effects of wiring cost principles on complexity for different spatial conformations. We find that both probabilities only conform small-world architectures neurons dense clusters due decrease within clusters. Furthermore, small-worldness modularity were reduced systems connections caused reduction allowing novel insight into mechanisms underlying adaptive maladaptive alterations. Our findings corroborate previous work showing distributions play key role development.

Язык: Английский

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