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Aiming at the characteristics of human-thinking-centric studies, brain informatics (BI) emphasizes a systematic methodology, in which systematic brain data analysis is a key issue. In this paper, a multiagent system, namely, the global learning scheme for BI, is proposed to perform a data-brain driven process planning. Utilizing the obtained three types of mining workflows, a three-step analytical...
Aiming at the characteristics of human thinking centric studies, Brain Informatics (BI) adopts a multi-aspect data analysis approach for realizing systematic human brain data analysis. However, the existing expert-driven and individual capabilities based approach cannot realize a holistic multi-aspect brain data analysis because of the limitation of individual capabilities of researchers. In this...
Peculiarity-oriented mining (POM) is a new data mining method consisting of peculiar data identification and peculiar data analysis. Peculiarity factor (PF) and local peculiarity factor (LPF) are important concepts employed to describe the peculiarity of points in the identification step. One can study the notions at both attribute and record levels. In this paper, a new record LPF called distance...
Brain activation detection is an important problem in fMRI data analysis. In this paper, we propose a data-driven activation detection method called neighborhood one-class SVM (NOC-SVM). By incorporating the idea of neighborhood consistency into one-class SVM, the method classifies a voxel as an activated or non-activated voxel by its neighbor weighted distance to a hyperplane in a high- dimensional...
In the paper, we propose a multi-aspect data mining process for investigating a more whole human information process mechanism systematically. As an example to demonstrate the proposed mining process, we explain how to design the experiment of an ERP mental arithmetic task with visual and auditory stimuli, and describe how to do multiaspect analysis in the obtained ERP data, respectively. Furthermore,...
As two related emerging fields of research, Web intelligence (WI) and brain informatics (BI) mutually support each other. Their synergy will yield profound advances in the analysis and understanding of data, knowledge, intelligence and wisdom, as well as their relationships, organization and creation process. When WI meets BI, it is possible to have a unified and holistic framework for the study of...
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