<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. Haeusler</style></author><author><style face="normal" font="default" size="100%">K. Schuch</style></author><author><style face="normal" font="default" size="100%">W. Maass</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Motif distribution and computational performance of two data-based cortical microcircuit templates</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Physiology (Paris)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.igi.tugraz.at/maass/psfiles/185.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1-2</style></number><volume><style face="normal" font="default" size="100%">103</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;div&gt;The neocortex is a continuous sheet composed of rather stereotypical local   microcircuits that consist of neurons on several laminae with characteristic   synaptic connectivity patterns. An understanding of the structure and   computational function of these cortical microcircuits may hold the key for   understanding the enormous computational power of the neocortex. Two   templates for the structure of laminar cortical microcircuits have recently   been published by Thomson et al. and Binzegger et al., both resulting from   long-lasting experimental studies (but based on different methods). We   analyze and compare in this article the structure and computational   properties of these two microcircuit templates. In particular, we examine the   distribution of network motifs, i.e. of subcircuits consisting of a small   number of neurons. The distribution of these building blocks of complex   networks has recently emerged as a method for characterizing similarities and   differences among complex networks. We show that the two microcircuit   templates have quite different distribution of network motifs, although they   both show a characteristic small-world property. In order to understand the   computational properties of these two microcircuit templates, we have   generated computer models of them, consisting of Hodgkin-Huxley point neurons   with conductance based synapses that have a biologically realistic short-term   plasticity. The performance of these two cortical microcircuit models was   studied for 7 generic computational tasks that require accumulation and   merging of information contained in two afferent spike inputs. Although the   two models exhibit a different performance for some of these tasks, their   average computational performance is very similar. When we changed the   connectivity structure of these two microcircuit models in order to see which   aspects of it are essential for computational performance, we found that the   distribution of degrees of nodes is a key factor for their computational   performance.&lt;/div&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">73</style></section></record></records></xml>
