2005-12-13: Human SCINT Seminar (13) - 1
Poster Mihoko Otake Registed 2005-12-25 22:29 (1974 hits) Date: 2005.12.13 (Tue) 11:00-15:00 Place: Informatics Education Building 4F, Conference Room Time: 11:00-12:00 Speaker: Mihoko Otake Title: Integrative and collaborative research through the development of multiscale neural simulator, human science integration seminar, and a hundred hour workshop Keywords: platform simulator, neuroinformatics, computer supported collaborative learning (CSCL), science integration program (SCINT), center of excellence (COE) Affiliation: Science Integration Program - Humans, Department of Frontier Sciences and Science Integration, Division of Project Coordination, PRESTO JST
Position: Lecturer Collaborator: Toshihisa Takagi, Takagi Lababoratory Disciplines: Robotics, Polymer Science, Neuroinformatics, Data Science, Collaborative Learning Societies and Conferences: IEEE, Robotics Society of Japan (RSJ), Information Processing Society of Japan (IPSJ), Japanese Society of Bioinformatics (JSBI), IEEE International Conference on Robotics and Automation, SPIE Electroactive Polymer Actuators and Devices (EAPAD), Intelligent Autonomous Systems, Genome Informatics Workshop, ACM SIGCHI Designing Interactive Systems Bibliography: Mihoko Otake, Integrative and collaborative research through the development of multiscale neural simulator, human science integration seminar, and a hundred hour workshop, Human Science Integration Seminar Abstracts, No. 13, pp. 1, 2005. (Please use this bibliography when you cite this abstract.) Abstract: It is widely recognized that integrating fundamental knowledge is very important for the progress of science. Also, scientists must work out to make scientific data and information much more accessible and useful for real-world decision-making in this information society. The Science Integration (SCINT) Program - Humans was established in April 2005 under the direction of University of Tokyo President, Hiroshi Komiyama, in order to meet these needs. In this program, the speaker has been developing multiscale neural simulator, where data, information and knowledge of neuroscience are integrated. The strategy for building neural simulator is to combine top down approach and bottom up approach. This talk is organized according to these approaches. Top down approach includes building macroscopic anatomical nervous systems model which can be connected to the musculoskeletal model. Bottom up approach includes interfacing microscopic anatomical and physiological neural models to the macroscopic model. The proposed method was successfully applied to the neural models registered on one of the typical biological model database, ModelDB. In the end, two collaborative activities lead by the speaker are introduced, human science integration seminar project and a hundred hour workshop project. The philosophy of the program has been in action through these efforts. References: [1] Iwata, S. and Chen, R. S., Science and the Digital Divide, Science, 310(5747): 405, 2005. [2] Otake, M. and Takagi, T., Reassembly and Interfacing Neural Models Registered on Biological Model Databases, Genome Informatics, vol. 16, no. 2, pp.76-85, 2005. [3] Beeman, D. and Bower, J.M., Simulator-independent representation of ionic conductance models with ChannelDB, Neurocomputing, 58-60:1085-1090, 2004. [4] Bower, J.M., Beeman, D. and Hucka, M., The GENESIS Simulation System, The Handbook of Brain Theory and Neural Networks, Second edition (M.A. Arbib, Ed.), Cambridge, MA, MIT Press, 475-478, 2003. [5] Chicurel, M., Databasing the brain., Nature, 406(6798):822-5, 2000. [6] Delorme, A. and Thorpe, S., SpikeNET: An Event-driven Simulation Package for Modeling Large Networks of Spiking Neurons, Network, Comput. Neural Syst., 14:613-627, 2003. [7] Doi, M., Challenge in polymer physics, Pure Appl. Chem., 75(10):1359-1615, 2003 [8] Doi, T., Kuroda, S., Michikawa, T., and Kawato, M., Spike-Timing Detection by Calcium Signaling Pathways of Cerebellar Purkinje Cells in Different Forms of Long-Term Depression, J. Neurosci. 25 (4):950-961, 2005. [9] Goddard, N.H., Hucka, M., Howell, F., Cornelis, H., Shankar, K., and Beeman, D., Towards NeuroML: model description methods for collaborative modelling in neuroscience, Philos. Trans. R. Soc. Lond. B Biol. Sci., 356(1412):1209-28, 2001. [10] Hines, M.L. and Carnevale, N.T., The NEURON simulation environment, Neural Computation, 9:1179-1209, 1997. [11] Hucka, M., Finney, A., Sauro, H.M., Bolouri, H., Doyle, J.C., Kitano, H. et. al., The Systems Biology Markup Language (SBML): A Medium for Representation and Exchange of Biochemical Network Models, Bioinformatics, 19(4):524-531, 2003. [12] Joshi-Tope, G., Gillespie, M., Vastrik, I., D'Eustachio, P., Schmidt, E., de Bono, B. et.al., Reactome: a knowledgebase of biological pathways, Nucleic Acids Res., 33 Database Issue:D428-32, 2005. [13] Kanehisa, M. and Goto, S., KEGG: Kyoto Encyclopedia of Genes and Genomes, Nucleic Acids Res., 28:27-30, 2000. [14] Koslow, S.H., Should the neuroscience community make a paradigm shift to sharing primary data?, Nat. Neurosci., 3(9):863-5, 2000. [15] Magee, J.C. and Cook, E.P., Somatic EPSP amplitude is independent of synapse location in hippocampal pyramidal neurons, Nat. Neurosci., 3(9):895-903, 2000. [16] Migliore, M., Morse, T.M., Davison, A.P., Marenco, L., Shepherd, G.M., and Hines, M.L., ModelDB: making models publicly accessible to support computational neuroscience, Neuroinformatics, 1(1):135-9, 2003. [17] Shepherd, G.M., Mirsky, J.S., Healy, M.D., and Singer, M.S., The Human Brain Project: neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data, Trends Neurosci., 21(11):460-8, 1998. [18] Tomita, M., Hashimoto, K., Takahashi, K., and Shimizu, T.S., E-CELL: software environment for whole-cell simulation, Bioinformatics, 15(1):72-84, 1999. [19] Usui, S., Visiome: neuroinformatics research in vision project, Neural Netw., 16(9):1293-300, 2003. [20] Otake, M. and Nakamura, Y., Anatomical model of the spinal nervous system and its application to the coordination analysis for motor learning support system, Proceedings of the IEEE International Conference on Intelligent Robots and Systems, pp. 847-853, 2005. [21] Otake, M., From Muscle to Brain: Modelling and Control of Functional Materials and Living Systems, Intelligent Autonomous Systems 9 T. Arai et al. (Eds.), In Press, 2006. [22] Otake, M., Fukano, R., Sako, S., Sugi, M., Kotani, K., Hayashi, J., Noguchi, H., Yoneda, R., Taura, K., Otsu, N. and Sato, T., Autonomous Collaborative Environment for Project Based Learning, Intelligent Autonomous Systems 9 T. Arai et al. (Eds.), In Press, 2006. [23] Otake, M., NEUROSCINT Project, http://www.neuroscint.org/, 2004-. [24] Otake, M., Fukano, R., Sako, S., Sugi, M., Kotani, K., Hayashi, J., Noguchi, H., Yoneda, R., Taura, K., Otsu, N. and Sato, T., A Hundred Hour Workshop, http://uticoe.ws100h.net/, 2005-. [25] Otake, M., Makino, T., Hoshiyama, D., Kraines, S., Takagi, T., Human Science Integration Seminar (this website), http://human.ws100h.net/, 2005-. |