A system consisting of interconnected networks, or a network of networks (NoN), appears diversely in many real-world systems, including the brain. In this study, we consider NoNs consisting of heterogeneous phase oscillators and investigate how the topology of subnetworks affects the global synchrony of the network. The degree of synchrony and the effect of subnetwork topology are evaluated based on the Kuramoto order parameter and the minimum coupling strength necessary for the order parameter to exceed a threshold value, respectively. In contrast to an isolated network in which random connectivity is favorable for achieving synchrony, NoNs synchronize with weaker interconnections when the degree distribution of subnetworks is heterogeneous, suggesting the major role of the high-degree nodes. We also investigate a case in which subnetworks with different average natural frequencies are coupled to show that direct coupling of subnetworks with the largest variation is effective for synchronizing the whole system. In real-world NoNs like the brain, the balance of synchrony and asynchrony is critical for its function at various spatial resolutions. Our work provides novel insights into the topological basis of coordinated dynamics in such networks.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882810PMC
http://dx.doi.org/10.3389/fncom.2018.00017DOI Listing

Publication Analysis

Top Keywords

subnetwork topology
8
interconnected networks
8
phase oscillators
8
order parameter
8
effective subnetwork
4
topology synchronizing
4
synchronizing interconnected
4
networks
4
networks coupled
4
coupled phase
4

Similar Publications

Patients with Moyamoya disease (MMD) exhibit significant alterations in brain structure and function, but knowledge regarding gray matter networks is limited. The study enrolled 136 MMD patients and 99 healthy controls (HCs). Clinical characteristics and gray matter network topology were analyzed.

View Article and Find Full Text PDF

Reconfigured metabolism brain network in asymptomatic Creutzfeldt-Jakob disease.

Neurobiol Dis

January 2025

Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China; National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China. Electronic address:

Background: Investigating brain metabolic networks is crucial for understanding the pathogenesis and functional alterations in Creutzfeldt-Jakob disease (CJD). However, studies on presymptomatic individuals remain limited. This study aimed to examine metabolic network topology reconfiguration in asymptomatic carriers of the PRNP G114V mutation.

View Article and Find Full Text PDF

Of mice and men: Dendritic architecture differentiates human from mice neuronal networks.

bioRxiv

December 2024

Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands.

The organizational principles that distinguish the human brain from other species have been a long-standing enigma in neuroscience. Focusing on the uniquely evolved human cortical layers 2 and 3, we computationally reconstruct the cortical architecture for mice and humans. We show that human pyramidal cells form highly complex networks, demonstrated by the increased number and simplex dimension compared to mice.

View Article and Find Full Text PDF

Converging evidence indicates that the heterogeneity of cognitive profiles may arise through detectable alternations in brain functional connectivity. Despite an unprecedented opportunity to uncover neurobiological subtypes through clustering or subtyping analyses on multi-state functional connectivity, few existing approaches are applicable to accommodate the network topology and unique biological architecture. To address this issue, we propose an innovative Bayesian nonparametric network-variate clustering analysis to uncover subgroups of individuals with homogeneous brain functional network patterns under multiple cognitive states.

View Article and Find Full Text PDF
Article Synopsis
  • The U.S. swine industry faces disease spread risks due to structural issues, and integrating human movement data with animal movement models provides a more accurate understanding of these risks.
  • An analysis of a year’s worth of farm visit data from three swine management companies revealed a highly connected network with 455 properties, demonstrating that human movements significantly enhance network connectivity compared to animal movements alone.
  • The study suggests that certain properties act as 'hubs' making them potential points for disease spread, indicating that swine farm networks are more vulnerable to disease outbreaks than previously thought based solely on animal movement.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!