Development of system identification methods of mesoscopic neurocircuitry based on multi-dimensional imaging data

2014 Fiscal Year Final Research Report

• Project Area: Mesoscopic neurocircuitry: towards understanding of the functional and structural basis of brain information processing
• Project/Area Number: 22115012
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Biological Sciences
• Research Institution: Kyoto University
• Principal Investigator: ISHII Shin 京都大学, 情報学研究科, 教授 (90294280)
• Co-Investigator(Renkei-kenkyūsha): OBA Shigeyuki 京都大学, 大学院情報学研究科, 講師 (80362838) ; MAEDA Shinichi 京都大学, 大学院情報学研究科, 助教 (20379530) ; YOSHIMOTO Junichiro 沖縄科学技術大学院大学, 研究員 (10403346) ; SAKUMURA Yuichi 愛知県立大学, 情報科学部 情報科学科, 准教授 (50324968)
• Project Period (FY): 2010-04-01 – 2015-03-31
• Keywords: システム同定 / ベイズ推定 / 超解像 / 構造可視化 / シミュレーション

Outline of Final Research Achievements

We developed a 3D image registration method and a super-resolution method, and applied them to detection of synaptic structure changes during mice motor learning. We also developed a functional connectivity analysis method to identify rats’ neuron-neuron or neuron-glia networks based on functional multi-neuron calcium imaging. We found firing rate of neighboring neurons was elevated after glial activities increased. Similar functional connectivity analysis was performed on calcium imaging on fly larvae motor circuits, and we found there were neural clusters which exhibited different activity phases within larvae motor behaviors.

Free Research Field

計算神経科学、ニューロインフォマティクス、機械学習、画像処理