Identification of functional information subgraphs in cultured neural networks Metadata
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- Main Title Identification of functional information subgraphs in cultured neural networks
Author: Gintautas, VadasCreator Type: PersonalCreator Info: Los Alamos National Laboratory
Author: Bettencourt, LuisCreator Type: PersonalCreator Info: Los Alamos National Laboratory
Author: Ham, Michael I.Creator Type: PersonalCreator Info: University of North Texas
Name: BioMed Central Ltd.Place of Publication: [London, United Kingdom]
- Creation: 2009-07-13
- Content Description: This paper accompanies an oral presentation on the identification of functional information subgraphs in cultured neural networks.
- Physical Description: 1 p.
- Keyword: neuronal networks
- Keyword: subgraphs
- Keyword: nodes
- Conference: Eighteenth Annual Computational Neuroscience Meeting: CNS, 2009, Berlin, Germany
- Publication Title: BMC Neuroscience
- Volume: 10
- Issue: Suppl 1
- Peer Reviewed: True
Name: UNT Scholarly WorksCode: UNTSW
Name: UNT College of Arts and SciencesCode: UNTCAS
- Rights Access: public
- DOI: 10.1186/1471-2202-10-S1-012
- Archival Resource Key: ark:/67531/metadc122146
- Academic Department: Center for Network Neuroscience
- Display Note: Abstract: We present a general information theoretic approach for identifying functional subgraphs in complex neuronal networks where the spiking dynamics of a subset of nodes (neurons) are observable. We show that the uncertainty in the state of each node can be written as a sum of information quantities involving a growing number of variables at other nodes. We demonstrate that each term in this sum is generated by successively conditioning mutual information on new measured variables, in a way analogous to a discrete differential calculus.