Research Areas----Laboratory of Brain Cognition and Brain-inspired Intelligence

Research Areas

Research Areas

Brainnetome Research

Research Directions: (1) Research on digital twin brain based on brainnetome atlas; (2) Research and development of bidirectional closed-loop brain-computer interface technology and systems; (3) Precise diagnosis and treatment of brain diseases based on brain-computer interface technology.

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Microscale Reconstruction and Intelligent Analysis

Team of Microscale Reconstruction and Intelligent Analysis is primarily dedicated to deciphering brain network structures at the microscale and exploring brain-inspired computational intelligence. Established in August 2015, team of Microscale Reconstruction and Intelligent Analysis is one of the first team in China to carry out the research and development of microscale brain connectomics technology

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Brain-inspired Cognitive AI

The Brain-inspired Cognitive AI Lab was founded in June 2013. The main objective of this lab is to create Brain-inspired Artificial General Intelligence based on understandings, theories, and inspirations of natural evolution and human intelligence. To realize this vision, the lab is devoted to creating the Brain-inspired Cognitive Intelligence Engine (BrainCog), a community based brain-inspired spiking neural network platform, to realize brain-inspired Artificial Intelligence (AI) and simulate cognitive brains of different animal species. The long term goal of this lab is to provide a comprehensive theory and AI system to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living AI for symbiotic human-AI society.

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Brain-inspired Computational Intelligence

My research focuses on brain-inspired computational intelligence, with the aim of developing intelligent systems capable of autonomous learning and adaptation in complex environments by simulating and drawing inspiration from the structure and function of the brain. Specifically, my research interests include: (1) Modeling Brain-like Structures and Functions: Investigating the simulation of neural and synaptic networks in the brain, with a particular focus on spatiotemporal dynamic modeling of biological neurons, spiking neural networks (SNNs), and synaptic plasticity mechanisms.

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Neural Computation and Brain-Computer Interaction

Our group (NeuBCI) belongs to the interdisciplinary field of neuroscience, pattern recognition and biomedical engineering. The research team is positioned at the forefront of basic research. It will combine the experimental research methods of cognitive neuroscience and modern artificial intelligence technology to reveal the information coding mechanism in the process of brain information processing and motion control, study the neural signal decoding technology, develop a new high-speed brain computer interface platform, and realize the real "what you think is what you get".

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Brain-Computer Interface and Integrated Intelligence

The Brain-Computer Interface and Integrated Intelligence Lab aims to systematically develop invasive brain-computer interfaces, elucidate the neural mechanisms of brain function, and advance brain-inspired computing. These technologies will be applied to fundamental neuroscience research and personalized diagnosis and treatment of brain diseases, driving the advancement of brain-computer intelligence.

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Neuroengineering & NeuroAI

We develop advanced optical technologies to interface with the primate brain, leveraging them to uncover the neural mechanisms underlying higher-order perceptual attributes—such as those related to speech, music, and the cocktail party effect—and to generate high-throughput functional data for training and aligning biologically realistic machine models with primate brain activity.

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AI for Life Science

For many years, our team has been focusing on AI for life science research, forming a research system with theoretical algorithms, intelligent systems, and AI applications in the scientific field as the core. In recent years, we have conducted in-depth research on multimodal artificial intelligence algorithms and system development, cross-domain autonomous evolutionary intelligence and applications, and published a number of high-level SCI papers and artificial intelligence conference papers including Nature, Nature Commun., IEEE TMI, AAAI, etc. as the first and correspondence (including parallel).

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