平成19（2007）年度　一般研究２実施報告書

課題番号	19−共研−2013		分野分類			統計数理研究所内分野分類			a
						主要研究分野分類			3
研究課題名	Dynamical inverse solution for the analysis of synchrony in human scalp electrical brain activity
フリガナ 代表者氏名	アンドレアス　ガルカ Andreas Galka				ローマ字		ANDREAS GALKA
所属機関	Kiel University
所属部局
職　　名	研究員
配分経費	研究費	40千円		旅　費		10千円		研究参加者数		10　人

研究目的と成果（経過）の概要

　A study purpose and a summary of the result (progress)

The aim of the project is an application of the dynamical inverse solution based on Kalman filter for research of interactions between brain areas in human scalp EEG. The main advantages of such approach are as follows: 1) the inverse solution provides a three-dimensional picture of the brain activity and therefore offers a unique opportunity to evaluate brain interactions in 3D space; 2) the high spatial resolution of the inverse solution allows estimating the interactions on a higher spatial scale than that available from the scalp EEG; 3) the inverse solution eliminates volume conduction which is a main obstacle in scalp EEG synchrony researches.

The project comprises two methodologically different parts and is accordingly divided within our team:

Part I. Application of the dynamical inverse solution based on Kalman filter to the real EEG data: the part of our team from ISM and Kiel University (Andreas Galka and his student Philipp Stern) under supervision of Prof. T. Ozaki.

The aim of this part was to test Kalman inverse solution in real human data localizing the sources of alpha activity during rest, eye closed condition. P. Stern spent 1 month (Feb. 2008) in RIKEN BSI localizing the alpha sources in EEG recordings contained high and low alpha activity. He elaborated the software package for fast and easy evaluation of the results of Kalman inverse solution in 3D space and comparison with other source localization techniques (e.g. LORETA). He applied the inverse solution to the data of 7 subjects. The results will be included in his diploma thesis. We have expected to find the most of alpha sources in the rest condition in the occipital areas; however, at the current stage the localization is not accurate enough. The work is in progress.

Part II. Synchronization analysis of three-dimensional EEG data (RIKEN part of our team).

The aim of this part is to devise a method to evaluation of synchrony between brain signals in 3D space (voxels) obtained using Kalman inverse solution. To evaluate the synchrony between the signals we elaborated the 3D
version of S-estimator. S-estimator method estimates the contraction of the embedding dimension of the statespace: such contraction is a consequence of synchronization and may be used as its measure (Carmeli et al 2005). New member of our lab George Fedorov devised the application of S-estimator for 3D source signals obtained with the inverse solution. He studied the effect of different number of neighboring voxels on synchrony estimation. He created the software for convenient visualization of synchronization between large numbers of voxels in 3D space. He is approaching statistical evaluation of the synchronization results.

For interpretation of the synchronization results we (A. Nikolaev, S. Gepshtein, P. Gong, C. van Leeuwen) developed a method for analysis of the quasi-stable synchrony intervals in close spaced electrodes/voxels, continuing the line of our studies started by Nikolaev et al. (2005). We applied this method to the high-density scalp EEG recorded during perceptual grouping task. We found that duration of the intervals of quasi-stable synchrony is longer in grouping of unambiguous than ambiguous stimuli, because the former carry more stimulus information which requires longer time to be communicated between brain areas. This finding was reported in several conferences and described in the submitted paper. We are going to apply this approach to the voxels in 3D space obtained using Kalman inverse solution.

当該研究に関する情報源（論文発表、学会発表、プレプリント、ホームページ等）

The source of information about the study concerned（Article announcement, society announcement, a pre-print, a homepage）

The submitted paper:

Andrey R Nikolaev, Sergei Gepshtein, Pulin Gong, & Cees van Leeuwen. Duration of coherence intervals in electrical cortical activity in perceptual organization. Subm.

The presentations on the topics of the project:

by Andreas Galka:
Date: 17.7.2007
Place: Institute of Mathematics, University of Luebeck, Germany
Title: "Time Series Modelling for the Neurosciences: The Innovation Approach"

Date: 24.7.2007
Place: Conference "Waves 2007", minisymposium on "Brain waves", University of Reading, UK
Title: "A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filtering"

Date: 11.9.2007
Place: Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
Title: "Time Series Modelling for the Neurosciences: The Innovation Approach"

Date: 13.9.2007
Place: Workshop on "Probabilistic formulation of the inverse problem and application to image reconstruction", Neuroscience Research Institute, University of Manchester, UK
Title: "Dynamical inverse problem of EEG source reconstruction"

Date: 14.9.2007
Place: Institute of Computer Science and Applied Mathematics, University of Kiel, Germany
Title: "Time Series Modelling for the Neurosciences: The Innovation Approach"

Date: 15.1.2008
Place: Freiburg Center for Data Analysis and Modeling, University of Freiburg, Germany
Title: "Time Series Modelling for the Neurosciences: The Innovation Approach"

by Andrey Nikolaev:
A.R. Nikolaev, S. Gepshtein, P. Gong, & C. van Leeuwen. Dynamical properties of EEG synchrony correlated with behavior. Poster # MON-285 on IBRO International Congress of Neuroscience. Melbourne, Australia, July 12-17, 2007.
A.R. Nikolaev, S. Gepshtein, P. Gong, & C. van Leeuwen. Duration of quasi-stable EEG synchrony reflects both stimulus properties and phenomenological reports in perceptual organization. Oral presentation in RIKEN Symposium “Brain activity and information integration”, September 13, 2007.

研究会を開催した場合は、テーマ・日時・場所・参加者数を記入してください。

When I held a meeting for the study, in a theme, a holding fixed date, please make entry of a held place, the number of the participants.

研究参加者一覧
氏名	所属機関
Nikolaev Andrey	理化学研究所
Wong, K.F. Kevin	統計数理研究所
尾崎　統	統計数理研究所
Gepshtein Sergei	理化学研究所
Gong Pulin	理化学研究所
DeWees James	理化学研究所
中谷　智恵	理化学研究所
van Leeuwen Cees	理化学研究所
Jurica Peter	理化学研究所