论文标题
深静脉：使用几何深度学习从结构MRI数据中预测人类视觉皮层的功能组织
DeepRetinotopy: Predicting the Functional Organization of Human Visual Cortex from Structural MRI Data using Geometric Deep Learning
论文作者
论文摘要
无论是在人造机器还是生物系统中，形式和功能通常都是直接相关的。然而，在后者中，由于生物学的复杂性，这种特殊关系通常不清楚。在这里，我们开发了一个几何深度学习模型，能够利用皮质的实际结构，从结构和功能MRI数据中学习脑功能与解剖学之间的复杂关系。我们的模型不仅能够仅凭解剖学特性来预测人类视觉皮层的功能组织，而且还能够预测个人之间细微的变化。
Whether it be in a man-made machine or a biological system, form and function are often directly related. In the latter, however, this particular relationship is often unclear due to the intricate nature of biology. Here we developed a geometric deep learning model capable of exploiting the actual structure of the cortex to learn the complex relationship between brain function and anatomy from structural and functional MRI data. Our model was not only able to predict the functional organization of human visual cortex from anatomical properties alone, but it was also able to predict nuanced variations across individuals.
