Wiring cost in the organization of a biological network

Abstract

To find out the role of the wiring cost in the organization of the neural network of the nematode \textit{Caenorhapditis elegans} (\textit{C. elegans}), we build the neuronal map of \textit{C. elegans} based on geometrical positions of neurons and define the cost as inter-neuronal Euclidean distance \textit{d}. We show that the wiring probability decays exponentially as a function of \textit{d}. Using the edge exchanging method and the component placement optimization scheme, we show that positions of neurons are not randomly distributed but organized to reduce the total wiring cost. Furthermore, we numerically study the trade-off between the wiring cost and the performance of the Hopfield model on the neural network.

References in corpus (15)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• The structure and function of complex networks
• The diameter of the world wide web
• The large-scale organization of metabolic networks
• Evolution of networks
• Specificity and stability in topology of protein networks
• Mean-field theory for scale-free random networks
• Scale-free brain functional networks
• Modeling the Internet's Large-Scale Topology
• Scale-free Networks from Optimal Design
• Spatial Growth of Real-world Networks
• Modulated Scale-free Network in the Euclidean Space
• Performance of networks of artificial neurons: The role of clustering
• Dynamical Motifs: Building Blocks of Complex Network Dynamics

Cited by in corpus (16)

• Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems
• The evolutionary origins of modularity
• The evolutionary origins of hierarchy
• Mesoscopic organization reveals the constraints governing C. elegans nervous system
• Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network
• Navigable maps of structural brain networks across species
• Dynamic behaviors in directed networks
• Detecting the ultra low dimensionality of real networks
• Developmental trajectory of Caenorhabditis elegans nervous system governs its structural organization
• Emergence of geometric Turing patterns in complex networks
• Percolation and the effective structure of complex networks
• Information-theoretic neuro-correlates boost evolution of cognitive systems
• Scale-free behavior of weight distributions of connectomes
• Effect of clustering on Turing instability in complex networks
• A distance constrained synaptic plasticity model of C. elegans neuronal network
• Cost-efficiency trade-offs of the human brain network revealed by a multiobjective evolutionary algorithm