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Multi-aspect Data Analysis in Brain Informatics

  • Ning Zhong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

In order to investigate human information processing mechanism systematically, various methods of brain data measurement and analysis are required. It has been observed that multiple brain data such as fMRI brain images and EEG brain waves extracted from human multi-perception mechanism involved in a particular task are peculiar ones with respect to a specific state or the related part of a stimulus. Based on this point of view, we propose a way of peculiarity oriented mining for multi-aspect analysis in multiple human brain data, without using conventional image processing to fMRI brain images and frequency analysis to brain waves. The proposed approach provides a new way in Brain Informatics for automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientists from a single type of experimental data analysis towards a holistic view.

Keywords

Brodmann Area Brain Wave Experimental Data Analysis fMRI Image Brain Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ning Zhong
    • 1
  1. 1.The International WIC Institute & Department of Information EngineeringMaebashi Institute of TechnologyMaebashi-CityJapan

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