Physiological and mathematical modeling of periodic synchronized neural firing phenomenon by data driven approach

2014 Fiscal Year Final Research Report

• Project/Area Number: 24300108
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Statistical science
• Research Institution: The Institute of Statistical Mathematics
• Principal Investigator: ISHIGURO Makio 統計数理研究所, 大学共同利用機関等の部局等, 名誉教授 (10000217)
• Co-Investigator(Kenkyū-buntansha): MIWAKEICHI Fumikazu 統計数理研究所, モデリング研究系, 准教授 (30360647) ; OKU Yoshitaka 兵庫医科大学, 医学部, 教授 (20252512) ; OKADA Yasumasa 独立行政法人国立病院機構村山医療センター(臨床研究センター), 内科, 医長 (80160688)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 時系列解析 / 神経情報学 / 生体イメージングデータ解析

Outline of Final Research Achievements

We have developed practical preprocessing methods to correct incompleteness of the image such as non-uniform illumination, motion artifact and so on. Further, we suggested an efficient strategy to discriminate neurons and astrocytes in the respiratory-related region in the brainstem using statistical maps such as variances, time-lagged cross correlation coefficients and so on. From the physiological point of view, we obtained findings suggesting the existence of slowly oscillating astrocytic network weakly coupled with neuronal network and stochastic activation among inspiratory neurons within the respiratory rhythm-generating kernel. These results will provide us new paradigms for further mathematical studies of neuronal network exhibiting synchronous bursting activity.

Free Research Field

情報量統計学