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Data-Brain Modeling for Systematic Brain
Informatics
Jianhui Chen 1 and Ning Zhong 1 , 2
1 International WIC Institute, Beijing University of Technology, Beijing,
100124, P.R. China
2 Dept of Life Science and Informatics, Maebashi Institute of Technology,
Maebashi-City, 371-0816, Japan
chenjhnh@gmail.com, zhong@maebashi-it.ac.jp
Abstract. In order to understand human intelligence in depth and find
the cognitive models needed by Web Intelligence (WI), Brain Informat-
ics (BI) adopts systematic methodology to study human “thinking cen-
tric” cognitive functions, and their neural structures and mechanisms
in which the brain operates. For supporting systematic BI study, we
propose a new conceptual brain data model, namely Data-Brain, which
explicitly represents various relationships among multiple human brain
data sources, with respect to all major aspects and capabilities of hu-
man information processing systems (HIPS). On one hand, constructing
such a Data-Brain is the requirement of systematic BI study. On the
other hand, BI methodology supports such a Data-Brain construction.
In this paper, we design a multi-dimension framework of Data-Brain and
propose a BI methodology based approach for Data-Brain modeling. By
this approach, we can construct a formal Data-Brain which provides a
long-term, holistic vision to understand the principles and mechanisms
of HIPS.
1
Introduction
Brain Informatics (BI) [13,14] is a new interdisciplinary field to study human
information processing mechanism systematically from both macro and micro
points of view by cooperatively using experimental/computational cognitive neu-
roscience and Web Intelligence (WI) and data mining centric advanced informa-
tion technologies. It can be regarded as brain sciences in the WI centric IT
age [12,14].
The capabilities of human intelligence can be broadly divided into two main
aspects: perception and thinking. Though it is not appropriate to say that think-
ing centric cognitive functions are superior to perception oriented functions,
thinking centric functions obviously reflect more intelligence of HIPS than per-
ception oriented functions. Thus, for getting cognitive models needed by WI,
our BI study focuses on the “thinking centric” cognitive functions, which are
complex and involved with multiple inter-related cognitive functions with re-
spect to activated brain areas for a given task, and neurobiological processes of
 
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