Brain Network Analysis
Main Lab Location:
CiNet (Main bldg.)
Guest Associate Professor, Osaka University
1-4 Yamadaoka, Suita City Osaka, 565-0871
I am interested in the theoretical analysis and performance evaluation of networks, which can be found in almost all forms of biological and engineered systems. Especially, the human brain with its huge number of connected neurons shows great computational abilities and high complexity, which make it a remarkable study object in the field of networks.
My research focuses on the analysis of brain functional networks obtained from fMRI or MEG experimental data by using methods from graph theory and network science. I am particularly interested in studying how the network is decomposed in modules (communities) and how the network adapts itself to different situations under the presence of fluctuations.
Inspired by the mechanisms observed in the brain, I aim to design distributed and noise-assisted strategies that can be implemented in future information networks in order to improve their adaptability and robustness.
Leibnitz, K., Shimokawa, T., Ihara, A., Fujimaki, N., Peper, F. On the Topological Changes of Brain Functional Networks under Priming and Ambiguity. IEICE Transactions on Communications, Special Section on Progress on Information Network Science, vol. E96-B, no. 11, pp. 2741-2748, Nov. 2013.
Leibnitz, K., Shimokawa, T., Umehara, H., Murata, T. Topological Comparison of Brain Functional Networks and Internet Service Providers. IEICE Transactions on Communications, Special Section on Frontiers of Information Networks Science, vol. E95-B, no. 5, pp. 1539-1546, 2012.
Balasubramaniam, S., Leibnitz, K., Lio', P., Botvich, D., Murata, M. Biological Principles for Future Internet Architecture Design. IEEE Communications Magazine, Special Issue on Future Internet Architectures: Design and Deployment Perspectives, vol. 49, no. 7, pp. 44-52, July 2011.
Leibnitz, K., Murata, M. Attractor Selection and Perturbation for Robust Networks in Fluctuating Environments. IEEE Network, Special Issue on Biologically Inspired Networking, vol. 24, no. 3, pp. 14-18, May/June 2010.
Leibnitz, K., Wakamiya, N., Murata, M. Biologically-Inspired Self-Adaptive Multi-Path Routing in Overlay Networks, Communications of the ACM, Special Issue on Self-Managed Systems and Services, vol. 49, no.3, pp. 62-67, March 2006