Brain Informatics

Ning Zhong is currently head of Knowledge Information Systems Laboratory, and a professor in Department of Systems and Information Engineering, Graduate School, Maebashi Institute of Technology, Japan. He is also CEO of Web Intelligence Laboratory, Inc., a new type of venture intelligent IT business company. Before moving to Maebashi Institute of Technology, he was an associate professor in Department of Computer Science and Systems Engineering, Yamaguchi University, Japan. He is also a guest professor of Beijing University of Technology since 1998. He is the co-founder and co-chair of Web Intelligence Consortium (WIC), vice chair of the executive committee of the IEEE Computer Society Technical Committee on Computational Intelligence (TCCI), the advisory board of ACM SIGART, steering committee of IEEE International Conferences on Data Mining (ICDM), the advisory board of International Rough Set Society, steering committee of Pacific-Asia Conferences on Knowledge Discovery and Data Mining (PAKDD), coordinator and member of advisory board of a Special Interest Group on Granular Computing in Berkeley Initiative in Soft Computing (BISC/SIG-GrC).

This volume contains the papers selected for presentation at The 2009 Inter- tional Conference on Brain Informatics (BI 2009) held at Beijing University of Technology, China, on October 22-24, 2009. It was organized by the Web Int- ligence Consortium (WIC) and IEEE Computational Intelligence Society Task Force on Brain Informatics (IEEE TF-BI). The conference was held jointly with The 2009 International Conference on Active Media Technology (AMT 2009). Brain informatics (BI) has emergedas an interdisciplinaryresearch?eld that focuses on studying the mechanisms underlying the human information proce- ing system (HIPS). It investigates the essential functions of the brain, ranging from perception to thinking, and encompassing such areas as multi-perception, attention,memory,language,computation,heuristicsearch,reasoning,planning, decision-making, problem-solving, learning, discovery, and creativity. The goal of BI is to develop and demonstrate a systematic approach to achieving an integrated understanding of both macroscopic and microscopic level working principles of the brain, by means of experimental, computational, and cognitive neuroscience studies, as well as utilizing advanced Web Intelligence (WI) centric information technologies. BI represents a potentially revolutionary shift in the way that research is undertaken. It attempts to capture new forms of c- laborative and interdisciplinary work. Following this vision, new kinds of BI methods and global research communities will emerge, through infrastructure on the wisdom Web and knowledge grids that enables high speed and d- tributed, large-scale analysis and computations, and radically new ways of sh- ing data/knowledge.

Keynote Talks.- Using Neural Imaging to Inform the Instruction of Mathematics.- Distributed Human-Machine Systems: Progress and Prospects.- Large Scale Reasoning on the Semantic Web: What to Do When Success Is Becoming a Problem.- How Midazolam Can Help Us Understand Human Memory: 3 Illustrations and a Proposal for a New Methodology.- Research on Brain-Like Computer.- A Framework for Machine Learning with Ambiguous Objects.- Special Session on Information Processing Meets Brain Sciences.- Data Compression and Data Selection in Human Vision.- Do Brain Networks Correlate with Intelligence?.- How Were Intelligence and Language Created in Human Brain.- Affective Learning with an EEG Approach.- Some Web Intelligence Oriented Brain Informatics Studies.- Thinking and Perception-centric Investigations of Human Information Processing Systems.- Modelling the Reciprocal Interaction between Believing and Feeling from a Neurological Perspective.- Information Hypothesis: On Human Information Capability Study.- Correlated Size Variations Measured in Human Visual Cortex V1/V2/V3 with Functional MRI.- Effects of Attention on Dynamic Emotional Expressions Processing.- Simulating Human Heuristic Problem Solving: A Study by Combining ACT-R and fMRI Brain Image.- EEG/ERP Meets ACT-R: A Case Study for Investigating Human Computation Mechanism.- Evaluation of Probabilities and Brain Activity - An EEG-Study.- Human Factors Affecting Decision in Virtual Operator Reasoning.- The Effect of Information Forms and Floating Advertisements for Visual Search on Web Pages: An Eye-Tracking Study.- Figural Effects in Syllogistic Reasoning with Evaluation Paradigm: An Eye-Movement Study.- Structured Prior Knowledge and Granular Structures.- Multisensory Interaction of Audiovisual Stimuli on the Central andPeripheral Spatial Locations: A Behavioral Study.- A Functional Model of Limbic System of Brain.- Information Technologies for the Management and Use of Brain Data.- Data Explosion, Data Nature and Dataology.- Reading What Machines "Think".- Using SVM to Predict High-Level Cognition from fMRI Data: A Case Study of 4*4 Sudoku Solving.- Data-Brain Modeling for Systematic Brain Informatics.- Cognition-inspired Applications.- Combine the Objective Features with the Subjective Feelings in Personal Multi-alternative Decision Making Modeling.- Automatic and Semi-automatic Approaches for Selecting Prominent Spatial Filters of CSP in BCI Applications.- Boosting Concept Discovery in Collective Intelligences.- Segmentation of Heart Image Sequences Based on Human Way of Recognition.