Numerical simulation of large-scale neuron networks with
NeuroDUNE and its application to a cortical column in
primary somatosensory cortex
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1
University of Heidelberg, Interdisciplinary Center for Scientific Computing, Germany
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2
Max Planck Institute for Neurobiology, Germany
A fundamental challenge in neuroscience is to determine a mechanistic understanding of how the brain processes sensory information about its environment and how this can be related to behavior. Recently available methods, such as high-speed cameras, in vivo physiology and mosaic/optical-sectioning microscopy, allow to relate behavioral tasks with anatomically and functionally well defined brain regions. Specifically, the information related to the deflection of a single facial whisker on the snout of rodents (e.g. mice and rats) is processed by a network of approximately 15000 neurons (in rat), organized within a so called cortical column. The electrophysiological output from this network is sufficient to trigger simple behaviors, such as the crossing of a gap. By reengineering the detailed 3D anatomy and connectivity of individual neurons, and neuron populations, an average model network (cortical column in silico) is established. By animating this network with in vivo measured input will help to understand the sub cellular mechanisms of simple sensory evoked behaviors.
In the presented work we introduce the simulation framework, NeuroDUNE, which enables modeling and simulation of signal processing in such large-scale, full-compartmental neuron networks on sub cellular basis. The fundamental equation for signal propagation, the well-known passive cable equation, is discretized in space with a second order correct Finite-Volume scheme (FV). Time discretization includes implicit schemes such as Backward Euler and Crank-Nicholson. Via error estimation a precise control of the simulation parameters is possible. Modeling of active components supports Hodgkin-Huxley type channels with an arbitrary number of gating particles. Furthermore, specific biophysical relevant ion concentrations, e.g. intracellular calcium ions, can be simulated on demand to capture advanced channel behavior.
Generation of networks is based on an ensemble of recorded neurons that were reconstructed in 3D. Neurons were classified, according to the distance of their cell body from the cortical surface (pia) and the branch pattern of their apical dendrites in eight cell-types. These cell types are three dimensionally interconnected based upon measured anatomical and functional data. An example for such a quantitatively determined microcircuit within a cortical column is given by reconstructing the major thalamocortical pathway, giving excitatory input to more or less every cell in the cortical network.
The methods provided by NeuroDUNE will enable us to perform large-scale network simulations with a high degree of spatial and temporal detail. This will yield in silico experiments that potentially shed light on sub cellular mechanisms and constraints about the synapse distribution, for large functional units within the brain.
Conference:
Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, 30 Sep - 2 Oct, 2009.
Presentation Type:
Poster Presentation
Topic:
Information processing in neurons and networks
Citation:
Lang
S,
Oberlaender
M,
Bastian
P and
Sakmann
B
(2009). Numerical simulation of large-scale neuron networks with
NeuroDUNE and its application to a cortical column in
primary somatosensory cortex.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.neuro.10.2009.14.167
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Received:
07 Sep 2009;
Published Online:
07 Sep 2009.
*
Correspondence:
Stefan Lang, University of Heidelberg, Interdisciplinary Center for Scientific Computing, Heidelberg, Germany, stefan.lang@iwr.uni-heidelberg.de