LICONN(基于光学显微镜的连接组学)

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新显微镜技术清晰重现大脑复杂网络 分辨率比传统的光学镜高16倍
Ke Ji Ri Bao· 2025-05-11 23:33
Core Insights - A new microscopy technology called "LICONN" has been developed by the Austrian Institute of Science and Technology (ISTA) and Google Research, which allows for the precise observation of neural connections in the brain [1][2] - LICONN can reproduce all synaptic connections between neurons and visualize complex molecular mechanisms, achieving a resolution of less than 20 nanometers, significantly improving upon traditional optical microscopy which has a resolution of 250-300 nanometers [1] - The technology utilizes the chemical and physical properties of hydrogels to preserve the fine microstructure of brain cells for observation [1] Technology and Methodology - LICONN employs standard optical microscopy for image acquisition and accurately connects each synaptic connection to its corresponding neuron, effectively assembling a complex brain network [1] - Google’s AI technology aids in the automatic identification of neurons and their intricate structures, making the reconstruction of all cellular components feasible [2] - The team has created a 3D rendering of the brain network, which not only accurately reproduces brain tissue but also visualizes neuron connections and networks [2] Implications - LICONN brings scientists closer to assembling a comprehensive map of mammalian brains, enhancing the understanding of brain functions in both healthy and diseased states [2]
新显微镜技术清晰重现大脑复杂网络
news flash· 2025-05-11 23:15
Core Insights - A new microscopy technology called "LICONN" has been developed by the Institute of Science and Technology Austria (ISTA) and Google Research, which aids in understanding the complex network of the human brain [1] Group 1 - The human brain consists of billions of interconnected nerve cells that process various signals, enabling cognition, thought, memory, and physical activity [1] - Precise observation of how these nerve cells are arranged and connected is essential for understanding the brain's complexity [1] - The related research paper was published on May 7 in the journal "Nature" [1]