Brain-inspired Cognitive Intelligence Engine for Brain Simulation and Brain-inspired Artificial Intelligence
BrainCog
Brain-inspired Cognitive Intelligence Engine (BrainCog) is a brain-inspired spiking neural network based platform for simulating the cognitive brains of different animal species at multiple scales and realizing brain-inspired Artificial Intelligence. The long term goal of BrainCog is to provide a comprehensive theory and system to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living machines in future human-machine society.
Simulation of Hippocampus and Memory
Brain-inspired Reinforcement Learning
Multi-Scale Whole Mouse Brain Point Neuron Simulation
Tielin Zhang, Yi Zeng, Dongcheng Zhao, Liwei Wang, Yuxuan Zhao, Bo Xu. HMSNN: Hippocampus inspired Memory Spiking Neural Network. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2301-2306, IEEE Press, Budapest, Hungary, October 9-12, 2016.
Qingqun Kong, Yi Zeng, Qiulei Dong. Biologically Inspired Deep Stereo Model. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP 2015), 3700-3704, Quebec City, Canada, 2015.
Tielin Zhang, Yi Zeng, Bo Xu. Neural Spike Prediction based on Spreading Activation. The Twenty-Third Annual Computational Neuroscience Meeting (CNS 2014), Québec City, Canada, July 26-31, 2014, BMC Neuroscience, 15(Suppl 1): P7, 2014.
Yi Zeng, Weida Bi, Yun Wang, Xuan Tang and Bo Xu. Automatic Recovery of Z-Jumps for Neuronal Morphology Reconstruction. Frontiers in Neuroinformatics. Conference Abstract: The 7th Neuroinformatics Congress (Neuroinformatics 2014), Leiden, the Netherlands, August 25-27, 2014.