Structural Models of Cortical Networks with Long-Range Connectivity. (20th November 2011)

• Record Type: Journal Article
• Authors: Voges, Nicole; Aertsen, Ad; Rotter, Stefan
• Other Names: Wang Zidong Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2012(2012)
• Publication Date: 2011-11-20
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2012/484812
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Most current studies of neuronal activity dynamics in cortex are based on network models with completely random wiring. Such models are chosen for mathematical convenience, rather than biological grounds, and additionally reflect the notorious lack of knowledge about the neuroanatomical microstructure. Here, we describe some families of new, more realistic network models and explore some of their properties. Specifically, we consider spatially embedded networks and impose specific distance-dependent connectivity profiles. Each of these network models can cover the range from purely local to completely random connectivity, controlled by a single parameter. Stochastic graph theory is then used to describe and analyze the structure and the topology of these networks.