Universal principles of topology governing both of structural and effective connectivity

Abstract

Event Abstract Back to Event Universal principles of topology governing both of structural and effective connectivity Masanori Shimono1* and John Beggs2 1 University of Tokyo, Japan 2 Indiana University, United States Since the era of Hebb, the importance and mysterious role that neuronal ensembles play in has been a main concern of the neuroscience [Hebb, 1949]. Recently, much work using structural connectivity has revealed patterns of synaptic connections in neuron ensembles [Bock et al., 2011]. Structural connectivity information is extremely valuable, as it indicates pathways through which one neuron could possibly influence spiking in another. In contrast, effective connectivity aims to describe the pathways through which influence actually occurs. The concept of effective connectivity was initially described in regard to local neuronal networks [Aertsen et al., 1989]. However, almost all research on effective connectivity has been done in macroscopic dynamics recorded using fMRI, MEG, and EEG [Friston, 1994]. Furthermore, even out of the studies on microcircuits, almost no work has been done on effective connectivity in local cortical networks at the timescale of typical synaptic delays within the cortex (1-20 ms). This is unfortunate, as direct influence between neurons would be expected to occur at these time delays. Structural connectivity studies have shown that groups of 3-7 cortical neurons are more likely than chance to be synaptically connected to each other if they have synapses onto a common neighbor neuron [Perin et al., 2011]. This led to the question whether effective connectivity also shows this pattern. In order to investigate these topics, we used a 512 electrode array system to record spontaneous activity in 9 slice cultures that included neocortex and portions of hippocampus. On average, we recorded over ~120 neurons from each culture for 1 hr or more. Although many metrics of effective connectivity have been proposed, we selected transfer entropy because several studies found it to compare favorably in accuracy to other metrics. In the comparison between the topological properties of structural neuronal networks and the topological properties of the reconstructed effective connectivities, we could find universal principles of topology governing both of structural and effective connectivity. Keywords: Large scale modeling, structural connectivity, effective connectivity, topology, neuronal networks Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012. Presentation Type: Poster Topic: Neuroinformatics Citation: Shimono M and Beggs J (2014). Universal principles of topology governing both of structural and effective connectivity. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00119 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2013; Published Online: 27 Feb 2014. * Correspondence: Dr. Masanori Shimono, University of Tokyo, unset, Japan, shimono@brain.k.u-tokyo.ac.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Masanori Shimono John Beggs Google Masanori Shimono John Beggs Google Scholar Masanori Shimono John Beggs PubMed Masanori Shimono John Beggs Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.