2014年11月
A Statistical Method of Identifying Interactions in Neuron-Glia Systems Based on Functional Multicell Ca2+Imaging
PLOS COMPUTATIONAL BIOLOGY
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- 巻
- 10
- 号
- 11
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1371/journal.pcbi.1003949
- 出版者・発行元
- PUBLIC LIBRARY SCIENCE
Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron-glia network. We attempted to identify neuron-glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron-glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron-glia systems.
- リンク情報
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- DOI
- https://doi.org/10.1371/journal.pcbi.1003949
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000345454400030&DestApp=WOS_CPL
- URL
- http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003949
- ID情報
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- DOI : 10.1371/journal.pcbi.1003949
- ISSN : 1553-734X
- eISSN : 1553-7358
- Web of Science ID : WOS:000345454400030