POSTER PRESENTATION Open Access Aspects of randomness in biological neural graph structures

In the past two decades, significant advances have been made in understanding the structural and functional prop-erties of biological networks using graph-theoretic analy-sis. In general, most graph-theoretic studies are conducted in the presence of serious uncertainties, such as major undersampling of the experimental data. In the specific case of neural systems, however, a few moderately robust experimental reconstructions do exist, and these have long served as fundamental prototypes for studying connectiv-ity patterns in the nervous system. Here, we provide a comparative analysis of several “historical ” graphs, includ-ing areal connectivity graphs of the cat and macaque mon-key cortex [1-3], as well as the neural connectivity graph of the nematode C. elegans [4,5]. While it is a common practice in applying graph-theore