北京雁栖湖应用数学研究院

丘成栋

卢萌

2024年11月20日 21:00 至 22:00

Online

Intelligence emerges from the intricate structural and dynamic organization of the neuronal system. From a bottom-up perspective, this system is hierarchically constructed, progressing from single molecules to cells, and ultimately to neuronal networks. Understanding the structural dynamics at each level, from a combined perspective of biology, physics, and mathematics, is crucial for uncovering the physical and functional basis of intelligence. At the molecular level, super-resolution microscopy, combined with coupled diffusion-advection equations and fractal geometry, revealed a phase-dependent mechanism of aggregate formation: active transport transitions to diffusion as aggregates grow, providing new insights into neurodegenerative disease markers. At the cellular level, using state-of-the-art deep learning models and graph theory, we uncovered a causal relationship between the structure of the endoplasmic reticulum (ER) and lysosomal motion. Our findings demonstrate that lysosomes actively regulate ER reshaping, a process critical for both metabolic adaptation and neuronal development. At the network level, we developed a multi-scale recording system based on an integrated optical-electrode device, enabling simultaneous high-resolution spatial and temporal measurements of neuronal activity and structure. This system captured the structural dynamics of neurons, spanning from large-scale network organization involving thousands of neurons to detailed calcium activity at individual synapses. In this talk, I will present our multidisciplinary approach to studying intelligence, spanning from single-molecule dynamics to large-scale neuronal networks, providing a holistic view of the structural dynamics underlying neuronal system.

本人于2024年1月在北京大学成立人工智能与动态结构实验室，致力于通过理论与实验相结合的方法探索智能的本质。实验上，我们开发先进的工具，获取高质量的数据并基于此构建理论，通过理论对实验进行指导从而获得更好的数据，推动理论的不断完善。本人希望通过跨学科的协同研究，促进人工智能与神经科学领域的深度融合与发展，逐步深入对智能本质的探索。近五年发表相关论文20篇，其中在Nature Methods、Science Advances等期刊以独立一作发表论文8篇，受邀于瑞士联邦理工（EPFL）、国际理论物理研究中心（ICTP）等知名机构和国际学术会议做报告，任英国阿尔兹海默研究基金会（Alzheimer’s Research UK）基金评委，并于2023年受剑桥大学出版社之邀成为生物成像和分析领域的国际期刊Biological Imaging 的副编辑（Associate Editor）。 Science for AI: 探索构建基于黎曼几何的智能与意识理论框架，研究智能的几何化本质，核心思想可总结为：the geometry of intelligence guides how the consciousness navigate, the consciousness dictates how the geometry of intelligence evolves. AI for Science: 开发先进的人工智能工具，并将其与其他技术结合，研究神经元网络的结构动力学。主要成果包括：1）研发了基于石墨烯微电极阵列的多模态神经元结构与活动检测系统，实现了光学成像与电生理记录的同步，首次实现了神经元动作电位与突触级亚结构形变的同时检测；2）结合超分辨成像技术开发了人工智能视频图像分析工具ERnet，成功解决了内质网结构的精确识别与定量分析难题，精准量化了其在不同疾病模型中的形态变化。