A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging

PLoS Comput Biol. 2014 Nov 13;10(11):e1003949. doi: 10.1371/journal.pcbi.1003949. eCollection 2014 Nov.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • CA3 Region, Hippocampal / cytology*
  • CA3 Region, Hippocampal / metabolism
  • Calcium / metabolism*
  • Computational Biology / methods*
  • Models, Neurological
  • Models, Statistical
  • Neuroglia / metabolism*
  • Neurons / metabolism*
  • Rats
  • Rats, Wistar

Substances

  • Calcium

Grant support

This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas, ‘Mesoscopic neurocircuitry: towards understanding of the functional and structural basis of brain information processing’ (MEXT KAKENHI Grant Number 22115012), and the Strategic Research Program for Brain Sciences (SRPBS) (http://brainprogram.mext.go.jp/missionG/), both of which are from the Ministry of Education, Culture, Sports, Science, and Technology, Japan, and partly by CREST (http://www.jst.go.jp/kisoken/crest/project/35/35_03.html) from Japan Science and Technology Agency, Japan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.