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演題詳細

Symposium

コネクトミクス研究の動向と課題
Achievements and Agendas of Connectmics Analysis

開催日 2014/9/13
時間 15:00 - 17:00
会場 Room F(302)
Chairperson(s) 伊藤 啓 / Kei Ito (東京大学 分子細胞生物学研究所 / Institute of Molecular and Cellular Biosciences, The University of Tokyo, Japan)

ヒトマクロコネクトームにおけるダイナミクス研究
Dynamics of human macro connectome

  • S3-F-2-4
  • 山下 宙人 / Okito Yamashita:1 
  • 1:国際電気通信基礎技術研究所 脳情報解析研究所 / ATR Neural Information Analysis Laboratories, Japan 

In the last two decades, the study of human brain function had a lot of achievement due to development of new measurement and experimental methodology. In the first ten years, development of fMRI has led functional brain mapping study in which brain regions related to its brain functions were revealed. Recent development of resting-state fMRI experiment and diffusion MRI measurement are leading a new paradigm so-called "human macro connectome" where brain functions are characterized by the network of multiple brain regions. This paradigm is further extending to "dynamics of human macro connectome" where the dynamically changing functional network is investigated. However, the methodology to address this issue has not been developed yet and it is a very challenging task to develop such methodology under requirement of non-invasiveness for human subjects.

In the department of computational brain imaging in ATR, we are developing analysis methodology to identify macro-scale whole-brain dynamics in sub-second order by integrating multiple experimental measurements through a dynamics model. More specifically, we construct a network dynamics model of current sources (population neural activities) of magnetoencephalography (MEG) on structural connections obtained from diffusion MRI. fMRI activity map information is also incorporated to make activity localization more reliable. With this model setting, we present the algorithm to estimate the network dynamics parameters as well as spatio-temporal patterns of current sources from experimental data. Preliminary results of simulation and real experimental data analysis show possibility of our approach. In the end of my talk, several challenges in "dynamics of human macro connectome" will be discussed.


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