主要研究方向及内容
神经系统中大量神经元通过突触联结形成的环路体系承载了大脑认知过程的表达和身体生理功能的调控，其结构和活动的复杂性跨越多个时空尺度，是人们理解脑功能原理的重大挑战。神经物理学与生理学实验室通过发展和应用跨尺度显微成像等前沿技术，解析从突触到环路的复杂结构和动态变化，以破译大脑学习的计算规则和生物机制，发现身体器官生理功能调控的基本原理和神经通路，并为理解相关疾病机理、发展诊疗新技术提供新的视角。具体研究内容如下：
1、神经系统的跨尺度解析
以亚分子分辨率解析突触联结的分子组织构架与功能状态，以亚细胞分辨率绘制从大脑到全身的介观神经联结图谱，在此基础上建立神经突触和环路的跨尺度结构功能大模型，为理解认知和生理功能机制及相关疾病机理提供精准数据基盘，并进而启发类脑计算和具身智能的结构框架。
2、可塑性与生物学习机制
学习记忆是智能的基础过程，依赖于神经突触可塑性变化及其与神经元网络活动相互作用而形成的复杂有序的动态系统。我们综合应用跨尺度成像等多种前沿技术，在离体培养的神经元中探索突触可塑性的规则和细胞机制，并通过活体动物实验发现生物学习的神经环路表达和动力学原理。
3、神经环路解析前沿技术
通过跨学科交叉合作，我们致力于发展与应用解析神经突触与环路结构功能的技术与方法，包括冷冻电镜断层成像（CryoET）、光电关联成像（CLEM）、超高速三维荧光显微技术（VISoR）、超微型头戴式显微镜（TINIscope）和多通道光纤记录（MuFi）等前沿技术，以及基于AI的大数据分析算法。
Main Research Interest
The intricate circuitry formed by vast neurons interconnected through synapses in the nervous system underlies both the expression of cognitive processes and the regulation of physiological functions. Its structural and functional complexity spans multiple spatiotemporal scales, presenting a major challenge to understanding the principles of brain function. The lab of neurophysics and neurophysiology develops and employs cutting-edge technologies—such as cross-scale microscopic imaging—to decipher the complex architecture and dynamics spanning from synapses to circuits. This enables us to reveal computational rules and biological mechanisms of brain learning, uncover fundamental principles and neural pathways regulating organ physiology, and provide novel insights for understanding disease mechanisms and developing diagnostic and therapeutic innovations. Specific research areas include:
1. Cross-Scale Analysis of Neural Systems
We resolve synaptic molecular architecture and functional states at submolecular resolution, map mesoscale connectivity from the brain to the periphery at subcellular resolution, and construct cross-scale structural-functional models of synapses and circuits. These efforts establish a precise data foundation for elucidating cognitive and physiological mechanisms and related pathologies, while inspiring structural frameworks for brain-inspired computing and embodied intelligence.
2. Plasticity and Biological Learning Mechanisms
Learning and memory—foundational to intelligence—rely on synaptic plasticity and its interaction with neuronal network dynamics to form complex, ordered systems. Using cross-scale imaging and other advanced techniques, we investigate synaptic plasticity rules and cellular mechanisms in cultured neurons and reveal neural circuit dynamics underlying biological learning in live animals.
3. Advanced Technologies for Neural Circuit Analysis
Through interdisciplinary collaboration, we develop and apply novel methods for structure-function analysis of synapes and circuits, including: cryo-electron tomography (CryoET), correlative light-electron microscopy (CLEM), volumetric imaging with synchronized on-the-fly-scan and readout (VISoR), ultracompact head-mounted microscopy (TINIscope), multichannel fiber photometry (MuFi) and AI-based big-data analytics algorithms.