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  Subsampling impact on the inferred properties of cortical networks

Hasanpour, M., Massorbio, P., & Levina, A. (2019). Subsampling impact on the inferred properties of cortical networks. Poster presented at DPG-Frühjahrstagung 2019, Regensburg, Germany.

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Hasanpour, M1, 2, Author              
Massorbio, P, Author
Levina, A1, 2, Author              
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Uncovering the topological properties of the brain network is essential for understanding brain function. Typically network structure is inferred from observations of a tiny fraction of the system, resulting in a severe subsampling of the whole network. How this inevitable subsampling influences the inferred network properties, such as the widely used small-world index, remains mostly unknown. The small-world index is defined as a clustering coefficient divided by diameter. For random, small-word, and scale-free networks we demonstrate analytically and numerically that the subsampling preserves the clustering coefficient. However, the diameter is strongly influenced by the subsampling, biasing the inference of small-worldness in subsampled networks. Our primary goal is to understand how to correct for such bias rigorously. Brain networks have a highly complex structure that is not captured by simple random networks we consider in theoretical studies. For a more realistic comparison, we investigate functional networks extracted from the High-Density Multi-Electrode Array recordings from cortical cultures using transfer entropy. The extracted network contains 4096 nodes, allowing for a further subsampling. We demonstrate that already the thresholding procedure used for extraction of the binary network is strongly influenced by subsampling.

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 Dates: 2019-04
 Publication Status: Published online
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Title: DPG-Frühjahrstagung 2019
Place of Event: Regensburg, Germany
Start-/End Date: 2019-03-31 - 2019-04-05

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Title: DPG-Frühjahrstagung 2019
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: BP 12.47 Start / End Page: - Identifier: -