A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging.
| Autor: | Ken Nakae, Yuji Ikegaya, Tomoe Ishikawa, Shigeyuki Oba, Hidetoshi Urakubo, Masanori Koyama, Shin Ishii |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | PLoS Computational Biology, Vol 10, Iss 11, p e1003949 (2014) |
| Druh dokumentu: | article |
| ISSN: | 1553-734X 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1003949 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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