Abstract
Event Abstract Back to Event 3D reverse engineering and simulation of signal flow in anatomically realistic neuronal networks Marcel Oberlaender1*, Christiaan DeKock2, Randy Bruno3, Stefan Lang4 and Bert Sakmann1 1 Max Planck Florida Institute, United States 2 VU University Amsterdam, Netherlands 3 Columbia University, United States 4 Heidelberg University, IWR, Germany Soma location, dendrite morphology and presynaptic innervation represent key determinants of functional responses of individual neurons, such a sensory-evoked spiking. Here, we reverse engineer the three-dimensional networks formed by thalamocortical afferents from the lemniscal pathway and excitatory neurons of an anatomically defined cortical column in rat vibrissal cortex. We objectively classify nine cell types and quantify the number and distribution of their somata, dendrites and thalamocortical synapses. Somata and dendrites of most cell types intermingle, while thalamocortical connectivity depends strongly upon the cell type and the three-dimensional soma location of the postsynaptic neuron. Our dataset provides the first three-dimensional anatomical description of the cell type-specific lemniscal synaptic wiring diagram and elucidates structure-function relationships of this physiologically relevant pathway at single-cell resolution. Simulation of signal flow, evoked by passive whisker touch, revealed that the three-dimensional structure of thalamocortical networks in a cortical column can account for cell type- and location-specific subthreshold and spiking responses. Thus, the present approach may allow investigating the cellular and subcellular mechanisms that underlie whisker-mediated behaviors. Figure 1 Keywords: computational neuroscience Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Computational neuroscience Citation: Oberlaender M, DeKock C, Bruno R, Lang S and Sakmann B (2011). 3D reverse engineering and simulation of signal flow in anatomically realistic neuronal networks. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00005 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: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Marcel Oberlaender, Max Planck Florida Institute, Jupiter, United States, marcel.oberlaender@maxplanckflorida.org 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 Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann Google Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann Google Scholar Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann PubMed Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann 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.
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