TY - GEN
T1 - Cognitive neuroscience and web intelligence
AU - Wu, Jinglong
PY - 2006
Y1 - 2006
N2 - Cognitive neuroscience is an interdisciplinary research field to study human information processing mechanism from both macro and micro views. Web intelligence is a new direction for scientific research and development of emerging web-based artificial intelligence technology. As two related important research fields, cognitive neuroscience and web intelligence mutually support each other strongly. The discovery of cognitive neuroscience can propose a new human intelligence model and to support web intelligence developments. Furthermore, web intelligence technology is useful to discover more advanced human cognitive models. In order to develop the web intelligence systems which match human ability, it is necessary to investigate human cognitive mechanism systematically. The key issues are how to design the psychological, functional Magnetic Resonance Imaging (fMRI) and Electroencephalograph (EEG) experiments for obtaining various data from human cognitive mechanism, as well as how to analyze such data from multiple aspects for discovering new models of human cognition. In our studies, we propose a new methodology with a multi-step process, in which various psychological experiments, physiological measurements and data mining techniques are cooperatively used to investigate human cognitive mechanism. This talk mainly introduces some cognitive neuroscience researches and the related intelligent mechanical systems in my laboratory. The researches include vision, auditory, memory, language and attention, etc. More specifically, I will talk about the relationship between cognitive neuroscience and web intelligence with using some examples.
AB - Cognitive neuroscience is an interdisciplinary research field to study human information processing mechanism from both macro and micro views. Web intelligence is a new direction for scientific research and development of emerging web-based artificial intelligence technology. As two related important research fields, cognitive neuroscience and web intelligence mutually support each other strongly. The discovery of cognitive neuroscience can propose a new human intelligence model and to support web intelligence developments. Furthermore, web intelligence technology is useful to discover more advanced human cognitive models. In order to develop the web intelligence systems which match human ability, it is necessary to investigate human cognitive mechanism systematically. The key issues are how to design the psychological, functional Magnetic Resonance Imaging (fMRI) and Electroencephalograph (EEG) experiments for obtaining various data from human cognitive mechanism, as well as how to analyze such data from multiple aspects for discovering new models of human cognition. In our studies, we propose a new methodology with a multi-step process, in which various psychological experiments, physiological measurements and data mining techniques are cooperatively used to investigate human cognitive mechanism. This talk mainly introduces some cognitive neuroscience researches and the related intelligent mechanical systems in my laboratory. The researches include vision, auditory, memory, language and attention, etc. More specifically, I will talk about the relationship between cognitive neuroscience and web intelligence with using some examples.
KW - Auditory
KW - Cognitive neuroscience
KW - EEG
KW - Human mechanisms of vision
KW - Memory and language
KW - Web intelligence
KW - fMRI
UR - http://www.scopus.com/inward/record.url?scp=33746701351&partnerID=8YFLogxK
U2 - 10.1007/11795131_11
DO - 10.1007/11795131_11
M3 - Conference contribution
AN - SCOPUS:33746701351
SN - 3540362975
SN - 9783540362975
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 68
BT - Rough Sets and Knowledge Technology - First International Conference, RSKT 2006, Proceedings
PB - Springer Verlag
T2 - First International Conference on Rough Sets and Knowledge Technology, RSKT 2006
Y2 - 24 July 2006 through 26 July 2006
ER -