BMC Neuroscience
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Poster presentation
Implications of the specific cortical circuitry for the network dynamics of a layered cortical network model Tobias C Potjans*1,2, Tomoki Fukai1,3 and Markus Diesmann1,3,4 Address: 1Brain and Neural Systems Team, RIKEN Computational Science Research Program, Wako City, Saitama, Japan, 2Institute of Neurosciences and Medicine, Research Center Jülich, Jülich, Germany, 3Theoretical Neuroscience Group, RIKEN Brain Science Institute, Wako City, Saitama, Japan and 4Bernstein Center for Computational Neuroscience, Albert-Ludwigs University, Freiburg, Germany Email: Tobias C Potjans* -
[email protected] * Corresponding author
from Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18–23 July 2009 Published: 13 July 2009 BMC Neuroscience 2009, 10(Suppl 1):P159
doi:10.1186/1471-2202-10-S1-P159
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009
Don H Johnson Meeting abstracts – A single PDF containing all abstracts in this Supplement is available
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This abstract is available from: http://www.biomedcentral.com/1471-2202/10/S1/P159 © 2009 Potjans et al; licensee BioMed Central Ltd.
The local cortical network consists of specifically interconnected neuronal populations (see [1] for review). This microcircuitry determines the possible interactions between neurons and thus may play a crucial role in shaping neuronal activity. We investigate the dynamical implications of the specificity of connections in the local network by means of large-scale simulations [2] of a spiking layered network model. To this end, we quantify the specificity of connections measured by diverse experimental techniques. We identify a hierarchy of specificity (Figure 1): Layer-specific connections (A) depend on the layers of the pre- and post-synaptic populations. Among the most prominent layer-specific connection profiles is a feed-forward pattern of connections (layer 4 (L4) to L2/3 to L5 to L6) which is closely linked to the tuning properties of cells in the primary visual cortex [1]. Target-specific connections (B), in addition, depend on the neuronal type of the target neuron [3]. Projection-specificity (C), finally, classifies neuronal subpopulations of a layer according to the main target layer of their axonal projection (see [4] for review). Our layered cortical network model consists of 80,000 I&F neurons and explains about 90% of the synapses constituting the local cortical microcircuit. As we focus on the relationship of connectivity and network activity, we use identical dynamics and parameters for all neuron types in the network. Despite this homogeneity, we observe that
the layer specific connections alone cause layer- and typespecific firing rates: excitatory firing rates are lowest in L2/ 3 (often below 1 Hz, comparable to [5]) and highest in L5 and inhibitory firing exceeds excitatory rates. Furthermore we find that a small subset of target-specific connections [3] is relevant for the stability of network activity. Finally, the incorporation of projection-specificity enables us to investigate the influence of fine-scale connectivity on global activity patterns. We conclude that specific connections represent a structural correlate of the experimentally observed network dynamics.
Acknowledgements Partially funded by EU Grant 15879 (FACETS), BMBF Grant 01GQ0420 to BCCN Freiburg, Next-Generation Supercomputer Project of MEXT, Japan, and the Helmholtz Alliance on Systems Biology.
References 1. 2. 3.
4. 5.
Douglas RJ, Martin KAC: Neuronal circuits of the neocortex. Annu Rev Neurosci 2004, 27:419-451. Gewaltig M-O, Diesmann M: NEST (neural simulation tool). Scholarpedia 2007, 2:1430. Potjans TC, Diesmann M: Consistency of in vitro and in vivo connectivity estimates: statistical assessment and application to cortical network modeling. 38th Soc for Neurosci Meeting 2008, 16:1. Thomson AM, Lamy C: Functional maps of neocortical local circuitry. Front Neurosci 2007, 1:1-42. Greenberg DS, Houweling AR, Kerr JND: Population imaging of ongoing neuronal activity in the visual cortex of awake rats. Nat Neurosci 2008, 11:749-751.
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BMC Neuroscience 2009, 10(Suppl 1):P159
http://www.biomedcentral.com/1471-2202/10/S1/P159
Figure The hierarchy 1 of specificity in the layered cortical network model The hierarchy of specificity in the layered cortical network model.
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