A Statistical Method of Identifying Interactions in Neuron-Glia Systems Based on Functional Multicell Ca2+ Imaging

Ken Nakae, Yuji Ikegaya, Tomoe Ishikawa, Shigeyuki Oba, Hidetoshi Urakubo, Masanori Koyama, Shin Ishii

Abstract: Author Summary Many neuroscientists believe that neurons mainly perform information processing in the brain. Glial cells have traditionally been regarded as passive cells, whose roles have been limited to mechanical support and energy transfer to neurons. However, some studies have recently demonstrated the existence of interactions between neurons and glial cells and implied the involvement of crosstalk between neuronal and glial systems in information processing. Nevertheless, the details on neuron–glia communication largely remain unknown. One way of addressing this issue is to use a powerful statistical methodology to identify the network structure based on high-throughput time-lapse imaging from neuron–glia networks. We developed a new statistical method for functional connectivity analysis that was suitable for examining neuron–glia interactions. We applied the method to multicellular Ca2+ imaging data, where neurons and glial cells carried out spontaneous activities in a rat hippocampal CA3 culture. We found in a data-driven manner that each glial cell facilitated the activities of neighboring neurons with a peak latency of 500 ms. Our study is the first of its kind to present a statistical framework to investigate the functional connectivity between neurons and glial cells. Our statistical method is thus capable of identifying neuron–glia interactions by utilizing the high-throughput imaging technique.