A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging.
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.
Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.
Ken
K
Nakae
Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Bunkyo-ku, Tokyo, Japan; Center for Information and Neural Networks, Suita City, Osaka, Japan.
Yuji
Y
Ikegaya
Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
Tomoe
T
Ishikawa
Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.
Shigeyuki
S
Oba
Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.
Hidetoshi
H
Urakubo
Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.
Masanori
M
Koyama
Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.
Shin
S
Ishii
D000818:Animals; D056654:CA3 Region, Hippocampal / Q000166:cytology* / Q000378:metabolism; D002118:Calcium / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D009457:Neuroglia / Q000378:metabolism*; D009474:Neurons / Q000378:metabolism*; D051381:Rats; D017208:Rats, Wistar
D002118:Calcium