Event Abstract Back to Event Graph coloring predicts the dynamics of neuronal networks Neuronal networks exhibit a rich dynamical repertoire, a consequence of both the intrinsic properties of neurons and the geometry of the network. A number of recent studies have devised measures that characterize the global structure of networks. In contrast, a vast body of work is devoted to examining the dynamics of individual neurons and synapses at varying levels of detail. The confluence of these two lines of research, structure-dynamics relationships in networks, is yet restricted to two classes of networks : those with simple structure that are capable of complex dynamics or those with elaborate structure but completely synchronous dynamics. Neuronal networks, more often than not, fall outside these classes. The dynamical repertoire of a neuronal network is enriched considerably by the action of inhibitory interneurons that corral principal neurons into synchronously firing groups and impose precise temporal relationships between these groups. The dynamics of an inhibitory network is necessarily constrained by its structure. Using a realistic computational model of the insect olfactory system, we establish a relationship between a structural property of the network, namely, its coloring [A coloring of a network is the assignment of colors to the nodes of the network such that nodes that are directly connected to each other are assigned different colors], and the dynamics it constrains. We show that inhibitory neurons associated with the same color tend to spike synchronously. Each synchronous group switches between an active and a quiescent state after a time determined by intrinsic neuronal properties and specific features of the network geometry. The inclusion of excitatory principal neurons into the network does not compromise the coloring-based dynamics of the inhibitory sub-network. In fact, excitation serves to increase the coherence within groups of synchronously firing inhibitory interneurons. The principal neurons, in turn, exhibit patterns of synchrony that are strongly dependent on pre-synaptic inhibition they receive. Principal neurons that receive similar inhibitory input evolve along similar trajectories. This observation, in conjunction with our knowledge of the coloring of the inhibitory sub-network allowed us to implement a novel construction, a space in which the collective spiking activity of all principal neurons in a random network reliably formed a series of orthogonally propagating traveling waves. By reordering the neurons according to a prescription dictated by the network structure, we were able to extract low dimensional dynamics (synchrony, clustering and traveling waves) from a randomly connected network. While we use insect olfaction to elucidate the relationship between the geometry of the network and the dynamics it constrains, our results are general enough to be applicable to a wide variety of neuronal networks. Conference: Computational and systems neuroscience 2009, Salt Lake City, UT, United States, 26 Feb - 3 Mar, 2009. Presentation Type: Poster Presentation Topic: Poster Presentations Citation: (2009). Graph coloring predicts the dynamics of neuronal networks. Front. Syst. Neurosci. Conference Abstract: Computational and systems neuroscience 2009. doi: 10.3389/conf.neuro.06.2009.03.097 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: 02 Feb 2009; Published Online: 02 Feb 2009. 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 Google Google Scholar PubMed 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.