人类画了100年的脑图，AI仅用几小时！还绘制出新脑区

Core Viewpoint - The article discusses the innovative machine learning algorithm CellTransformer developed by a neuroscience team at the University of California, San Francisco, which can classify and map the brain of five mice in just a few hours, potentially applicable to human brains in the future [1][4]. Group 1: Technology Overview - CellTransformer is an encoder-decoder architecture that significantly simplifies the process of brain mapping, which traditionally required manual drawing by scientists [5][10]. - The algorithm processes gene data from 10.4 million cells across five mice, identifying known brain regions and discovering new areas [3][20]. - The model employs a self-supervised learning approach, predicting gene expression based on neighboring cells, allowing for efficient and accurate mapping [11][15]. Group 2: Performance and Results - CellTransformer completed spatial modeling of 10.4 million cells in hours, outperforming traditional methods in both time and scale [20]. - It accurately aligns known brain structures, defining between 25 to 1300 neural regions without using brain region labels, demonstrating high alignment with existing anatomical and functional partitions [21][22]. - The algorithm also identifies and maps previously unrecognized brain regions, enhancing the understanding of brain structure and function [26][30]. Group 3: Broader Implications - The technology is not limited to mouse brains; it can be extended to other animals and potentially to human brains, with researchers optimistic about future applications [35][38]. - The algorithm could also be utilized in mapping other organs, such as kidneys, aiding in the differentiation between healthy and diseased tissues [41].